Sensors, Vol. 20, Pages 328: A Multi-Task Framework for Facial Attributes Classification through End-to-End Face Parsing and Deep Convolutional Neural Networks
un Chung Human face image analysis is an active research area within computer vision. In this paper we propose a framework for face image analysis, addressing three challenging problems of race, age, and gender recognition through face parsing. We manually labeled face images for training an end-to-end face parsing model through Deep Convolutional Neural Networks. The deep learning-based segmentation model parses a face image into seven dense classes. We use the probabilistic classification method and created probability maps for each face class. The probability maps are used as feature descriptors. We trained another ...
Source: Sensors - January 7, 2020 Category: Biotechnology Authors: Khalil Khan Muhammad Attique Rehan Ullah Khan Ikram Syed Syed Tae-Sun Chung Tags: Article Source Type: research

Sensors, Vol. 20, Pages 333: Ball Tracking and Trajectory Prediction for Table-Tennis Robots
This study thus employed machine learning to learn the flight trajectories of ping-pong balls, which consist of two parabolic trajectories: one beginning at the serving point and ending at the landing point on the table, and the other beginning at the landing point and ending at the striking point of the robot. We established two artificial neural networks to learn these two trajectories. We conducted a simulation experiment using 200 real-world trajectories as training data. The mean errors of the proposed dual-network method and a single-network model were 39.6 mm and 42.9 mm, respectively. The results indicate that the ...
Source: Sensors - January 7, 2020 Category: Biotechnology Authors: Hsien-I Lin Zhangguo Yu Yi-Chen Huang Tags: Article Source Type: research

Sensors, Vol. 20, Pages 335: Evaluation of Recent Advanced Soft Computing Techniques for Gully Erosion Susceptibility Mapping: A Comparative Study
acher Bui Gully erosion is a problem; therefore, it must be predicted using highly accurate predictive models to avoid losses caused by gully development and to guarantee sustainable development. This research investigates the predictive performance of seven multiple-criteria decision-making (MCDM), statistical, and machine learning (ML)-based models and their ensembles for gully erosion susceptibility mapping (GESM). A case study of the Dasjard River watershed, Iran uses a database of 306 gully head cuts and 15 conditioning factors. The database was divided 70:30 to train and verify the models. Their performance wa...
Source: Sensors - January 7, 2020 Category: Biotechnology Authors: Arabameri Blaschke Pradhan Pourghasemi Tiefenbacher Bui Tags: Article Source Type: research

Sensors, Vol. 20, Pages 342: Face Recognition Systems: A Survey
Atri Over the past few decades, interest in theories and algorithms for face recognition has been growing rapidly. Video surveillance, criminal identification, building access control, and unmanned and autonomous vehicles are just a few examples of concrete applications that are gaining attraction among industries. Various techniques are being developed including local, holistic, and hybrid approaches, which provide a face image description using only a few face image features or the whole facial features. The main contribution of this survey is to review some well-known techniques for each approach and to give the...
Source: Sensors - January 7, 2020 Category: Biotechnology Authors: Kortli Jridi Falou Atri Tags: Review Source Type: research

Sensors, Vol. 20, Pages 343: Enhancing the Sensor Node Localization Algorithm Based on Improved DV-Hop and DE Algorithms in Wireless Sensor Networks
e Mello The Distance Vector-Hop (DV-Hop) algorithm is the most well-known range-free localization algorithm based on the distance vector routing protocol in wireless sensor networks; however, it is widely known that its localization accuracy is limited. In this paper, DEIDV-Hop is proposed, an enhanced wireless sensor node localization algorithm based on the differential evolution (DE) and improved DV-Hop algorithms, which improves the problem of potential error about average distance per hop. Introduced into the random individuals of mutation operation that increase the diversity of the population, random mutation is ...
Source: Sensors - January 7, 2020 Category: Biotechnology Authors: Dezhi Han Yunping Yu Kuan-Ching Li Rodrigo Fernandes de Mello Tags: Article Source Type: research

Machine learning for detecting mesial temporal lobe epilepsy by structural and functional neuroimaging
AbstractMesial temporal lobe epilepsy (mTLE), the most common type of focal epilepsy, is associated with functional and structural brain alterations. Machine learning (ML) techniques have been successfully used in discriminating mTLE from healthy controls. However, either functional or structural neuroimaging data are mostly used separately as input, and the opportunity to combine both has not been exploited yet. We conducted a multimodal ML study based on functional and structural neuroimaging measures. We enrolled 37 patients with left mTLE, 37 patients with right mTLE, and 74 healthy controls and trained a support vecto...
Source: Frontiers of Medicine - January 7, 2020 Category: General Medicine Source Type: research

Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut –Currier and [3+2] annulation sequence
Chem. Commun., 2020, Advance Article DOI: 10.1039/C9CC08526B, CommunicationMasaru Kondo, H. D. P. Wathsala, Makoto Sako, Yutaro Hanatani, Kazunori Ishikawa, Satoshi Hara, Takayuki Takaai, Takashi Washio, Shinobu Takizawa, Hiroaki Sasai A highly atom-economical enantioselective Rauhut –Currier and [3+2] annulation has been established by flow system and machine-learning-assisted exploration of suitable conditions. To cite this article before page numbers are assigned, use the DOI form of citation above. The content of this RSS Feed (c) The Royal Society of Chemistry (Source: RSC - Chem. Commun. latest articles)
Source: RSC - Chem. Commun. latest articles - January 6, 2020 Category: Chemistry Authors: Masaru Kondo Source Type: research

Competency on Call: Resident Driven Learning Objectives for Competency-Based Medical Education.
Authors: Fage B, Alldred T, Levitt S, Abate A, Fefergrad M PMID: 31900877 [PubMed - as supplied by publisher] (Source: The Journal of American Association of Directors of Psychiatric Residency Training)
Source: The Journal of American Association of Directors of Psychiatric Residency Training - January 6, 2020 Category: Psychiatry Tags: Acad Psychiatry Source Type: research

Medical Students' Experience in a Trauma Chaplain Shadowing Program: A Mixed Method Analysis.
This study therefore analyzed an elective, first-year medical student, eight-hour, trauma chaplain shadowing experience, the objectives of which are to increase students' knowledge and understanding of (i) the role of chaplains/pastoral care in patient care; (ii) strategies for engaging patients and/or families in difficult situations; and (iii) approaches for discussing issues of spirituality with patients and families. Aquestionnaire was sent to participants after the experience assessing the value of the experience. Two focus groups provided additional qualitative data. Of the 148 participants over 6 years, 100 complete...
Source: Medical Education Online - January 6, 2020 Category: Universities & Medical Training Tags: Med Educ Online Source Type: research

New Evidence Supporting a Role of Hippocampus in the Development of Psychosis
The nature of cognitive dysfunction in schizophrenia and related disorders renders the hippocampus a particularly appealing research target in studies that attempt to uncover the mechanisms underlying conversion to psychosis. While comprising only approximately 1% of total gray matter volume in the adult brain (1), this small structure plays an indispensable role in a variety of cognitive functions known to be affected in schizophrenia, including declarative memory, learning, executive functioning, and emotional processing (2). (Source: Biological Psychiatry)
Source: Biological Psychiatry - January 6, 2020 Category: Psychiatry Authors: Hengyi Cao, Tyrone D. Cannon Tags: Commentary Source Type: research

[ASAP] Connecting Current Literature, Cartoons, and Creativity: Incorporating Student-Created Cartoons in a Biochemistry Course to Enhance Learning
Journal of Chemical EducationDOI: 10.1021/acs.jchemed.9b00876 (Source: Journal of Chemical Education)
Source: Journal of Chemical Education - January 6, 2020 Category: Chemistry Authors: Roger W. Giese* Source Type: research

[ASAP] Deep Learning to Generate < italic toggle="yes" > in Silico < /italic > Chemical Property Libraries and Candidate Molecules for Small Molecule Identification in Complex Samples
Analytical ChemistryDOI: 10.1021/acs.analchem.9b02348 (Source: Analytical Chemistry)
Source: Analytical Chemistry - January 6, 2020 Category: Chemistry Authors: Sean M. Colby, Jamie R. Nun~ez, Nathan O. Hodas, Courtney D. Corley, and Ryan R. Renslow* Source Type: research

A new concordant partial AUC and partial c statistic for imbalanced data in the evaluation of machine learning algorithms
In classification and diagnostic testing, the receiver-operator characteristic (ROC) plot and the area under the ROC curve (AUC) describe how an adjustable threshold causes changes in two types of error: false... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - January 6, 2020 Category: Information Technology Authors: Andr é M. Carrington, Paul W. Fieguth, Hammad Qazi, Andreas Holzinger, Helen H. Chen, Franz Mayr and Douglas G. Manuel Tags: Research article Source Type: research

Reproducibility of Machine Learning Models in Health Care
This Viewpoint reviews how machine learning models are developed and trained, discusses the challenges of reproducing medical machine learning model accuracy, and proposes practices and standards to improve the models ’ reproducibility and replicability. (Source: JAMA - Journal of the American Medical Association)
Source: JAMA - Journal of the American Medical Association - January 6, 2020 Category: General Medicine Source Type: research

Novel prognostication of patients with spinal and pelvic chondrosarcoma using deep survival neural networks
We used the Surveillance, Epidemiology, and End Results (SEER) database to develop and validate deep survival neural network machine learning (ML) algorithms to predict survival following a spino-pelvic chondr... (Source: BMC Medical Informatics and Decision Making)
Source: BMC Medical Informatics and Decision Making - January 6, 2020 Category: Information Technology Authors: Sung Mo Ryu, Sung Wook Seo and Sun-Ho Lee Tags: Research article Source Type: research

Comparing perineuronal nets and parvalbumin development between blackbird species with differences in early developmental song exposure [RESEARCH ARTICLE]
Gilles Cornez, Justin Langro, Charlotte A. Cornil, Jacques Balthazart, and Kathleen S. Lynch Brood parasitic songbirds are a natural system in which developing birds are isolated from species-typical song and therefore present a unique opportunity to compare neural plasticity in song learners raised with and without conspecific tutors. We compared perineuronal nets (PNN) and parvalbumin (PV) in song control nuclei in juveniles and adults of two closely related icterid species (i.e. blackbirds): brown-headed cowbirds (Molothrus ater; brood parasite) and red-winged blackbirds (Agelaius phoeniceus; non-parasite). The number ...
Source: Journal of Experimental Biology - January 6, 2020 Category: Biology Authors: Cornez, G., Langro, J., Cornil, C. A., Balthazart, J., Lynch, K. S. Tags: RESEARCH ARTICLE Source Type: research

Threat-induced modulation of hippocampal and striatal memory systems during navigation of a virtual environment.
Abstract The brain is composed of multiple memory systems that mediate distinct types of navigation. The hippocampus is important for encoding and retrieving allocentric spatial cognitive maps, while the dorsal striatum mediates procedural memories based on stimulus-response (S-R) associations. These memory systems are differentially affected by emotional arousal. In particular, rodent studies show that stress typically impairs hippocampal spatial memory while it spares or sometimes enhances striatal S-R memory. The influence of emotional arousal on these separate navigational memory systems has received less atte...
Source: Neurobiology of Learning and Memory - January 6, 2020 Category: Neurology Authors: Goodman J, McClay M, Dunsmoor JE Tags: Neurobiol Learn Mem Source Type: research

Machine learning in drug discovery and development part 1 – a primer
AbstractArtificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion paper will summarize applications of ML in drug discovery, drug development, and post ‐approval phase. (Source: CPT: Pharmacometrics and Systems Pharmacology)
Source: CPT: Pharmacometrics and Systems Pharmacology - January 6, 2020 Category: Drugs & Pharmacology Authors: Alan Talevi, Juan Francisco Morales, Gregory Hather, Jagdeep Podichetty, Sarah Kim, Peter C Bloomingdale, Samuel Kim, Jackson Burton, Joshua D Brown, Almut G Winterstein, Stephan Schmidt, J Kael White, Daniela J Conrado Tags: TUTORIAL Source Type: research

A Three ‐Dimensional Print Model of the Pterygopalatine Fossa Significantly Enhances the Learning Experience
AbstractThe pterygopalatine fossa (PPF) is a bilateral space deep within the skull that serves as a major neurovascular junction. However, its small volume and poor accessibility make it a difficult space to comprehend using two ‐dimensional illustrations and cadaveric dissections. A three‐dimensional (3D) printed model of the PPF was developed as a visual and kinesthetic learning tool for completely visualizing the fossa, its boundaries, its communicating channels, and its neurovascular structures. The model was evalua ted by analyzing student performance on pre‐ and post‐quizzes and a student satisfaction survey ...
Source: Anatomical Sciences Education - January 6, 2020 Category: Anatomy Authors: Jordan A. Tanner, Beeran Jethwa, Jeff Jackson, Maria Bartanuszova, Thomas S. King, Arunabh Bhattacharya, Ramaswamy Sharma Tags: RESEARCH REPORT Source Type: research

Machine learning in drug discovery and development part 1 – a primer
AbstractArtificial intelligence, in particular machine learning (ML), has emerged as a key promising pillar to overcome the high failure rate in drug development. Here, we present a primer on the ML algorithms most commonly used in drug discovery and development. We also list possible data sources, describe good practices for ML model development and validation, and share a reproducible example. A companion paper will summarize applications of ML in drug discovery, drug development, and post ‐approval phase. (Source: CPT: Pharmacometrics and Systems Pharmacology)
Source: CPT: Pharmacometrics and Systems Pharmacology - January 6, 2020 Category: Drugs & Pharmacology Authors: Alan Talevi, Juan Francisco Morales, Gregory Hather, Jagdeep Podichetty, Sarah Kim, Peter C Bloomingdale, Samuel Kim, Jackson Burton, Joshua D Brown, Almut G Winterstein, Stephan Schmidt, J Kael White, Daniela J Conrado Tags: TUTORIAL Source Type: research

An inverse optimization approach to understand human acquisition of kinematic coordination in bimanual fine manipulation tasks.
Abstract Tasks that require the cooperation of both hands and arms are common in human everyday life. Coordination helps to synchronize in space and temporally motion of the upper limbs. In fine bimanual tasks, coordination enables also to achieve higher degrees of precision that could be obtained from a single hand. We studied the acquisition of bimanual fine manipulation skills in watchmaking tasks, which require assembly of pieces at millimeter scale. It demands years of training. We contrasted motion kinematics performed by novice apprentices to those of professionals. Fifteen subjects, ten novices and five ex...
Source: Biological Cybernetics - January 6, 2020 Category: Science Authors: Yao K, Billard A Tags: Biol Cybern Source Type: research

A Patient-Oriented, General Practitioner-Level, Deep Learning-based Cutaneous Pigmented Lesion Risk Classifier on Smartphone.
Abstract Given that advanced melanoma has a poor prognosis, earlier detection is essential.1 Recently, deep learning (DL) models have shown promise in aiding diagnosis of melanoma.2,3 However, these models only consider images but not complementary clinical information; and are mainly for diagnostic purpose, rather than screening. PMID: 31907926 [PubMed - as supplied by publisher] (Source: The British Journal of Dermatology)
Source: The British Journal of Dermatology - January 6, 2020 Category: Dermatology Authors: Chin YPH, Hou ZY, Lee MY, Chu HM, Wang HH, Lin YT, Gittin A, Chien SC, Nguyen PA, Li LC, Chang TH, Li YCJ Tags: Br J Dermatol Source Type: research

The Lecture Note-Taking Skills of Adolescents With and Without Learning Disabilities.
This study attempted to replicate these findings with two groups of high school students-those with and without the diagnosis of a learning disability (LD). Students without LD scored significantly higher than those with LD on handwriting speed, listening comprehension, background knowledge, sustained attention, quality of notes, and test performance. Results of regression analyses indicated that note-taking (f2 = 1.94) and test-taking (f2 = 2.69) were associated with listening comprehension and background knowledge predominately. If these results are replicated, they suggest that the variables related to note-taking in ty...
Source: Journal of Learning Disabilities - January 6, 2020 Category: Disability Authors: Oefinger LM, Peverly ST Tags: J Learn Disabil Source Type: research

Activation of α7 nAChR by PNU-282987 improves synaptic and cognitive functions through restoring the expression of synaptic-associated proteins and the CaM-CaMKII-CREB signaling pathway.
Activation of α7 nAChR by PNU-282987 improves synaptic and cognitive functions through restoring the expression of synaptic-associated proteins and the CaM-CaMKII-CREB signaling pathway. Aging (Albany NY). 2020 Jan 06;12: Authors: Wang XL, Deng YX, Gao YM, Dong YT, Wang F, Guan ZZ, Hong W, Qi XL Abstract Ligands of nicotinic acetylcholine receptors (nAChRs) are widely considered as potential therapeutic agents. The present study used primary hippocampus cells and APPswe/PSEN1dE9 double-transgenic mice models to study the possible therapeutic effect and underlying mechanism of the specific activa...
Source: Aging - January 6, 2020 Category: Biomedical Science Authors: Wang XL, Deng YX, Gao YM, Dong YT, Wang F, Guan ZZ, Hong W, Qi XL Tags: Aging (Albany NY) Source Type: research

Exploration of flow reaction conditions using machine-learning for enantioselective organocatalyzed Rauhut-Currier and [3+2] annulation sequence.
Abstract A highly atom-economical enantioselective organocatalyzed Rauhut-Currier and [3+2] annulation sequence has been established by using a flow system. Suitable flow conditions were explored through reaction screening of multiple parameters using machine learning. Eventually, functionalized chiral spirooxindole analogues were obtained in high yield with good ee as a single diastereomer within one minute. PMID: 31903462 [PubMed - as supplied by publisher] (Source: Chemical Communications)
Source: Chemical Communications - January 6, 2020 Category: Chemistry Authors: Kondo M, Wathsala HDP, Sako M, Hanatani Y, Ishikawa K, Hara S, Takaai T, Washio T, Takizawa S, Sasai H Tags: Chem Commun (Camb) Source Type: research

The Psychotherapy Supervisor as an Agent of Transformation: To Anchor and Educate, Facilitate and Emancipate.
CONCLUSIONS: Psychotherapy supervisors serve foremost as agents of transformation, their chief objective being to actuate and actualize a transformative process of therapist development. The crucial processes by which supervisors achieve that transformative objective reside in the three streams of supervisory action. Accordingly, psychotherapy supervision is best conceptualized as a transformative learning pedagogy. PMID: 31902226 [PubMed - as supplied by publisher] (Source: American Journal of Psychotherapy)
Source: American Journal of Psychotherapy - January 6, 2020 Category: Psychiatry & Psychology Authors: Watkins CE Tags: Am J Psychother Source Type: research

Ex vivo fluorescence confocal microscopy: prostatic and periprostatic tissues atlas and evaluation of the learning curve
AbstractEx vivo fluorescence confocal microscopy (FCM) is an optical technology that provides fast H&E-like images of freshly excised tissues, and it has been mainly used for “real-time” pathological examination of dermatological malignancies. It has also shown to be a promising tool for fast pathological examination of prostatic tissues. We aim to create an atlas for FCM images of prostatic and periprostatic tissues to facilitate the interpretation of these images. Furthermore, we aimed to evaluate the learning curve of images interpretation of this new technology. Eighty fresh and unprepared biopsies obta...
Source: Virchows Archiv - January 6, 2020 Category: Pathology Source Type: research

Use of Individual Development Plans (IDPs) for Nurse Scientist Training
Individualized development plans (IDPs) are tools designed to support persons in identifying professional goals and strategies to achieve these goals. Currently, IDPs are used across all of the Ruth L. Kirschstein Institutional National Research Service Awards (T32) funded by the National Institute for Nursing Research (NINR). While several organizations, including the National Institutes of Health (NIH), have strongly encouraged the use of IDPs to support identification and achievement of learning and career development goals, limited information is available on how to best implement these tools in research training. (Sou...
Source: Nursing Outlook - January 6, 2020 Category: Nursing Authors: Hilaire J. Thompson, Sheila Judge Santacroce, Rita H. Pickler, Jerilyn K. Allen, Jane M. Armer, Suzanne Bakken, Kathryn H. Bowles, Yvette P. Conley, Sandra A. Dunbar, Lee Ellington, Margaret Grey, Margaret M. Heitkemper, Keela A. Herr, Eileen Lake, Ann Ma Source Type: research

Effect of 9  weeks continuous vs. interval aerobic training on plasma BDNF levels, aerobic fitness, cognitive capacity and quality of life among seniors with mild to moderate Alzheimer’s disease: a randomized controlled trial
ConclusionsNeither aerobic exercise modalities significantly modified plasma BDNF levels and cognitive performances. CAT and IAT enhanced aerobic fitness and functional capacities in AD patients and CAT their QoL.Trial registrationClinicalTrials.gov website (NCT02968875); registration date: 7 September 2016. “Retrospectively registered”. (Source: European Review of Aging and Physical Activity)
Source: European Review of Aging and Physical Activity - January 6, 2020 Category: Geriatrics Source Type: research

A Translational Approach to Cancer Research, Education and Training
In this study, we evaluate three new modules of the NSIP research, education, and clinical components that have been implemented in the first 2  years of National Cancer Institute Cancer Research Education Grants Program funding. The impact of these modules on intern satisfaction, learning, and near-term career trajectory is assessed to identify the most effective approaches and key measures of program outcomes. (Source: Journal of Cancer Education)
Source: Journal of Cancer Education - January 6, 2020 Category: Cancer & Oncology Source Type: research

A Three ‐Dimensional Print Model of the Pterygopalatine Fossa Significantly Enhances the Learning Experience
AbstractThe pterygopalatine fossa (PPF) is a bilateral space deep within the skull that serves as a major neurovascular junction. However, its small volume and poor accessibility make it a difficult space to comprehend using two ‐dimensional illustrations and cadaveric dissections. A three‐dimensional (3D) printed model of the PPF was developed as a visual and kinesthetic learning tool for completely visualizing the fossa, its boundaries, its communicating channels, and its neurovascular structures. The model was evalua ted by analyzing student performance on pre‐ and post‐quizzes and a student satisfaction survey ...
Source: Anatomical Sciences Education - January 6, 2020 Category: Anatomy Authors: Jordan A. Tanner, Beeran Jethwa, Jeff Jackson, Maria Bartanuszova, Thomas S. King, Arunabh Bhattacharya, Ramaswamy Sharma Tags: RESEARCH REPORT Source Type: research

Sensors, Vol. 20, Pages 322: A Comparative Analysis of Machine/Deep Learning Models for Parking Space Availability Prediction
Crespi Machine/Deep Learning (ML/DL) techniques have been applied to large data sets in order to extract relevant information and for making predictions. The performance and the outcomes of different ML/DL algorithms may vary depending upon the data sets being used, as well as on the suitability of algorithms to the data and the application domain under consideration. Hence, determining which ML/DL algorithm is most suitable for a specific application domain and its related data sets would be a key advantage. To respond to this need, a comparative analysis of well-known ML/DL techniques, including Multilayer Perceptro...
Source: Sensors - January 6, 2020 Category: Biotechnology Authors: Faraz Malik Awan Yasir Saleem Roberto Minerva Noel Crespi Tags: Article Source Type: research

Sensors, Vol. 20, Pages 320: Triplet Loss Guided Adversarial Domain Adaptation for Bearing Fault Diagnosis
Liu Recently, deep learning methods are becomingincreasingly popular in the field of fault diagnosis and achieve great success. However, since the rotation speeds and load conditions of rotating machines are subject to change during operations, the distribution of labeled training dataset for intelligent fault diagnosis model is different from the distribution of unlabeled testing dataset, where domain shift occurs. The performance of the fault diagnosis may significantly degrade due to this domain shift problem. Unsupervised domain adaptation has been proposed to alleviate this problem by aligning the distribution be...
Source: Sensors - January 6, 2020 Category: Biotechnology Authors: Wang Liu Tags: Article Source Type: research

Sensors, Vol. 20, Pages 314: Machine Learning Methodology in a System Applying the Adaptive Strategy for Teaching Human Motions
ekarczyk The teaching of motion activities in rehabilitation, sports, and professional work has great social significance. However, the automatic teaching of these activities, particularly those involving fast motions, requires the use of an adaptive system that can adequately react to the changing stages and conditions of the teaching process. This paper describes a prototype of an automatic system that utilizes the online classification of motion signals to select the proper teaching algorithm. The knowledge necessary to perform the classification process is acquired from experts by the use of the machine learning me...
Source: Sensors - January 6, 2020 Category: Biotechnology Authors: Krzysztof W ójcik Marcin Piekarczyk Tags: Article Source Type: research

Sensors, Vol. 20, Pages 311: A Power Spectrum Maps Estimation Algorithm Based on Generative Adversarial Networks for Underlay Cognitive Radio Networks
Ying Xu In the underlay cognitive radio networks, the main challenge in detecting the idle radio resources is to estimate the power spectrum maps (PSMs), where the radio propagation characteristics are hard to obtain. For this reason, we propose a novel PSMs estimation algorithm based on the generative adversarial networks (GANs). First, we constructed the PSMs estimation model as a regression model in deep learning. Then, we converted the estimation task into an image reconstruction task by image color mapping. We fulfilled the above task by designing an image generator and an image discriminator in the proposed maps&...
Source: Sensors - January 6, 2020 Category: Biotechnology Authors: Xu Han Lei Xue Fucai Shao Ying Xu Tags: Article Source Type: research

Sensors, Vol. 20, Pages 308: Reference-Driven Compressed Sensing MR Image Reconstruction Using Deep Convolutional Neural Networks without Pre-Training
n Gan Deep learning has proven itself to be able to reduce the scanning time of Magnetic Resonance Imaging (MRI) and to improve the image reconstruction quality since it was introduced into Compressed Sensing MRI (CS-MRI). However, the requirement of using large, high-quality, and patient-based datasets for network training procedures is always a challenge in clinical applications. In this paper, we propose a novel deep learning based compressed sensing MR image reconstruction method that does not require any pre-training procedure or training dataset, thereby largely reducing clinician dependence on patient-based data...
Source: Sensors - January 6, 2020 Category: Biotechnology Authors: Di Zhao Feng Zhao Yongjin Gan Tags: Article Source Type: research

SK2 channels in cerebellar Purkinje cells contribute to excitability modulation in motor-learning –specific memory traces
by Giorgio Grasselli, Henk-Jan Boele, Heather K. Titley, Nora Bradford, Lisa van Beers, Lindsey Jay, Gerco C. Beekhof, Silas E. Busch, Chris I. de Zeeuw, Martijn Schonewille, Christian Hansel Neurons store information by changing synaptic input weights. In addition, they can adjust their membrane excitability to alter spike output. Here, we demonstrate a role of such “intrinsic plasticity” in behavioral learning in a mouse model that allows us to detect specific consequences of abs ent excitability modulation. Mice with a Purkinje-cell–specific knockout (KO) of the calcium-activated K+ channel SK2 (L7-SK...
Source: PLoS Biology: Archived Table of Contents - January 6, 2020 Category: Biology Authors: Giorgio Grasselli Source Type: research

Interpreting neural decoding models using grouped model reliance
by Simon Valentin, Maximilian Harkotte, Tzvetan Popov Machine learning algorithms are becoming increasingly popular for decoding psychological constructs based on neural data. However, as a step towards bridging the gap between theory-driven cognitive neuroscience and data-driven decoding approaches, there is a need for methods that allow to interpre t trained decoding models. The present study demonstratesgrouped model reliance as a model-agnostic permutation-based approach to this problem. Grouped model reliance indicates the extent to which a trained model relies on conceptually related groups of variables, such as fre...
Source: PLoS Computational Biology - January 6, 2020 Category: Biology Authors: Simon Valentin Source Type: research

Computational optimization of associative learning experiments
by Filip Melinscak, Dominik R. Bach With computational biology striving to provide more accurate theoretical accounts of biological systems, use of increasingly complex computational models seems inevitable. However, this trend engenders a challenge of optimal experimental design: due to the flexibility of complex models, it is diff icult to intuitively design experiments that will efficiently expose differences between candidate models or allow accurate estimation of their parameters. This challenge is well exemplified in associative learning research. Associative learning theory has a rich tradition of computational mod...
Source: PLoS Computational Biology - January 6, 2020 Category: Biology Authors: Filip Melinscak Source Type: research

A multi-scanner study of MRI radiomics in uterine cervical cancer: prediction of in-field tumor control after definitive radiotherapy based on a machine learning method including peritumoral regions
ConclusionRecurrence could be predicted with high accuracy using expanded VOI for CC treated with definitive radiotherapy, suggesting that including the pathological characteristics of invasive margins in radiomics may improve predictive ability. (Source: Japanese Journal of Radiology)
Source: Japanese Journal of Radiology - January 6, 2020 Category: Radiology Source Type: research

Mixed Practice in Radiology Education —Has the Time Come?
Traditional medical education consists of required block rotations in the core specialties, which at 22% of medical schools includes radiology [1]. During that time, students typically dedicate 1 month to mastering essential radiological principles and basics of interpretation. Although students and many radiologists prefer this model, more recent educational research has shown that mixed practice, the process of interleaving problems and skills across disciplinary boundaries, results in better overall performance and longer-term learning as it provides opportunities for students to better assimilate knowledge and better p...
Source: Journal of the American College of Radiology : JACR - January 6, 2020 Category: Radiology Authors: Priscilla J. Slanetz, David M. Naeger, Laura L. Avery, Lori A. Deitte Tags: Civil discourse Source Type: research

Machine learning in rheumatology approaches the clinic
Nature Reviews Rheumatology, Published online: 06 January 2020; doi:10.1038/s41584-019-0361-0Machine learning and high-throughput technologies hold promise for the classification, diagnosis and treatment of patients with rheumatic diseases, with the ultimate goal of precision medicine. Several studies in 2019 highlight the feasibility and clinical utility of using machine learning in rheumatology to stratify patients and/or predict treatment responses. (Source: Nature Reviews Rheumatology)
Source: Nature Reviews Rheumatology - January 6, 2020 Category: Rheumatology Authors: Aridaman Pandit Timothy R. D. J. Radstake Source Type: research

Neuropsychiatric Symptoms and Risk Factors in Mild Cognitive Impairment: A Cohort Investigation of Elderly Patients
ConclusionsDepression may be an independent factor representing early neurodegeneration in elder patients with MCI. Further studies are warranted to assess whether effective management of NPS promotes the cognitive functions. (Source: The Journal of Nutrition, Health and Aging)
Source: The Journal of Nutrition, Health and Aging - January 6, 2020 Category: Nutrition Source Type: research

Machine learning applications in imaging analysis for patients with pituitary tumors: a review of the current literature and future directions
ConclusionThrough our concise evaluation and comparison of the studies using the concepts presented, we highlight future directions so that potential ML applications using different imaging modalities can be developed to benefit the clinical care of pituitary tumor patients. (Source: Pituitary)
Source: Pituitary - January 6, 2020 Category: Endocrinology Source Type: research

Sustainable interprofessional learning on clinical placements: the value of observing others at work.
Authors: Kent F, Glass S, Courtney J, Thorpe J, Nisbet G Abstract Clinical placements have the potential to offer meaningful interprofessional learning opportunities for pre-registration students. Informal, as opposed to structured interprofessional learning opportunities, may offer a sustainable solution to the challenges of scheduling formal interprofessional programs in the workplace. To investigate this concept, students on clinical placement from a range of professions were invited to observe another profession undertake a patient consultation, after which they completed a standardized reflective tool. A groun...
Source: Journal of Interprofessional Care - January 5, 2020 Category: Health Management Tags: J Interprof Care Source Type: research

Why do biomedical researchers learn to program? An exploratory investigation.
Conclusions: Librarians designing programming workshops should remember that most researchers are hoping to apply their new skills to a specific research task such as data cleaning, data analysis, and statistics and that language preferences can vary based on research community as well as personal preferences. Understanding the programming goals of researchers will make it easier for librarians to partner effectively and offer services that are critically needed in the biomedical community. PMID: 31897049 [PubMed - in process] (Source: Journal of the Medical Library Association : JMLA)
Source: Journal of the Medical Library Association : JMLA - January 5, 2020 Category: Databases & Libraries Tags: J Med Libr Assoc Source Type: research

The Effect of Combined Aerobic Exercise and Calorie Restriction on Mood, Cognition, and Motor Behavior in Overweight and Obese Women.
Authors: Žlibinaitė L, Solianik R, Vizbaraitė D, Mickevičienė D, Skurvydas A Abstract BACKGROUND: The benefits of weight loss programs on mood, cognitive, and motor behavior are largely limited to those of calorie restriction or exercise alone. Our aim was to investigate the effect of combined calorie restriction and aerobic exercise intervention on mood, brain activity, and cognitive and motor behavior in overweight and obese women. METHODS: Participants aged 36-56 years were randomized to either a control or an experimental group (aerobic exercise + 12.5% energy intake reduction) for a 6-month period. Ch...
Source: Journal of Physical Activity and Health - January 5, 2020 Category: Sports Medicine Tags: J Phys Act Health Source Type: research

Performance comparison of bubble point pressure from oil PVT data: Several neurocomputing techniques compared
AbstractPressure –Volume–Temperature (PVT) characterization of a crude oil involves establishing its bubble point pressure, which is the pressure at which the first gas bubble forms on a fluid sample while reducing pressure at a stabilized temperature. Although accurate measurement can be made experimentally, su ch experiments are expensive and time-consuming. Consequently, applying reliable artificial intelligence (AI)/machine learning methods to provide an accurate mathematical prediction of an oil’s bubble point pressure from more easily measured characteristics can provide valuable cost and time savin...
Source: European Journal of Applied Physiology - January 5, 2020 Category: Physiology Source Type: research

Precise cancer detection via the combination of functionalized SERS surfaces and convolutional neural network with independent inputs
Publication date: Available online 3 January 2020Source: Sensors and Actuators B: ChemicalAuthor(s): M. Erzina, A. Trelin, O. Guselnikova, B. Dvorankova, K. Strnadova, A. Perminova, P. Ulbrich, D. Mares, V. Jerabek, R. Elashnikov, V. Svorcik, O. LyutakovAbstractCombining the advanced approaches of surface functionalization and chemistry, plasmonics, surface enhanced Raman spectroscopy (SERS), and machine learning, we propose the advanced route for express and precise recognition of normal and cancer cells. Our interdisciplinary approach uses plasmonic coupling between the specific nanoparticles and underlying periodical pl...
Source: Sensors and Actuators B: Chemical - January 5, 2020 Category: Chemistry Source Type: research

Adult exposure to insecticides causes persistent behavioral and neurochemical alterations in zebrafish
Publication date: Available online 3 January 2020Source: Neurotoxicology and TeratologyAuthor(s): Andrew B. Hawkey, Lilah Glazer, Cassandra Dean, Corinne N. Wells, Kathryn-Ann Odamah, Theodore A. Slotkin, Frederic J. Seidler, Edward D. LevinAbstractFarmers are often chronically exposed to insecticides, which may present health risks including increased risk of neurobehavioral impairment during adulthood and across aging. Experimental animal studies complement epidemiological studies to help determine the cause-and-effect relationship between chronic adult insecticide exposure and behavioral dysfunction. With the zebrafish ...
Source: Neurotoxicology and Teratology - January 5, 2020 Category: Toxicology Source Type: research