Graph Convolutional Neural Networks with Global Attention for Improved Materials Property Prediction
Phys. Chem. Chem. Phys., 2020, Accepted Manuscript DOI: 10.1039/D0CP01474E, PaperSteph-Yves M Louis, Yong Zhao, Alirezaq Nasiri, Xiran Wang, Yuqi Song, Fei Liu, Jianjun Hu One of the major design issues in machine learning (ML) models for materials property prediction(MPP) is how to enable the models to learn property related physicochemical features. While many composition... The content of this RSS Feed (c) The Royal Society of Chemistry (Source: RSC - Phys. Chem. Chem. Phys. latest articles)
Source: RSC - Phys. Chem. Chem. Phys. latest articles - August 3, 2020 Category: Chemistry Authors: Steph-Yves M Louis Source Type: research

Category similarity affects study choices in self-regulated learning.
Authors: Lu X, Penney TB, Kang SHK Abstract During learning, interleaving exemplars from different categories (e.g., ABCBCACAB) rather than blocking by category (e.g., AAABBBCCC) often enhances inductive learning, especially when the categories are highly similar. However, when allowed to select their own study schedules, learners overwhelmingly tend to block rather than interleave. Category similarity has been shown to moderate the relative benefit of interleaved versus blocked study. We investigated whether learners were sensitive to category similarity when choosing exemplars for study, and whether these choices...
Source: Memory and Cognition - August 3, 2020 Category: Neuroscience Tags: Mem Cognit Source Type: research

CTumorGAN: a unified framework for automatic computed tomography tumor segmentation
ConclusionIn order to overcome those key challenges arising from CT datasets and solve some of the main problems existing in the current deep learning-based methods, we propose a novel unified CTumorGAN framework, which can be effectively generalized to address any kinds of tumor datasets with superior performance. (Source: European Journal of Nuclear Medicine and Molecular Imaging)
Source: European Journal of Nuclear Medicine and Molecular Imaging - August 3, 2020 Category: Nuclear Medicine Source Type: research

A metastatic tumor is no different to a viral pandemic: lessons learnt from COVID-19 may teach us to change the PRRT paradigm
(Source: European Journal of Nuclear Medicine and Molecular Imaging)
Source: European Journal of Nuclear Medicine and Molecular Imaging - August 3, 2020 Category: Nuclear Medicine Source Type: research

Correction to: Staging and quantification of florbetaben PET images using machine learning: impact of predicted regional cortical tracer uptake and amyloid stage on clinical outcomes
Incorrect acknowledgments. (Source: European Journal of Nuclear Medicine and Molecular Imaging)
Source: European Journal of Nuclear Medicine and Molecular Imaging - August 3, 2020 Category: Nuclear Medicine Source Type: research

Weakly Supervised Vessel Segmentation in X-ray Angiograms by Self-Paced Learning from Noisy Labels with Suggestive Annotation
Publication date: Available online 1 August 2020Source: NeurocomputingAuthor(s): Jingyang Zhang, Guotai Wang, Hongzhi Xie, Shuyang Zhang, Ning Huang, Shaoting Zhang, Lixu Gu (Source: Neurocomputing)
Source: Neurocomputing - August 3, 2020 Category: Neuroscience Source Type: research

A novel approach for classification of mental tasks using multiview ensemble learning (MEL)
Publication date: Available online 1 August 2020Source: NeurocomputingAuthor(s): A. Gupta, R.U. Khan, V.K. Singh, M. Tanveer, D. Kumar, A. Chakraborti, R.B. Pachori (Source: Neurocomputing)
Source: Neurocomputing - August 3, 2020 Category: Neuroscience Source Type: research

Deep learning to find colorectal polyps in colonoscopy: a systematic literature review
Publication date: Available online 1 August 2020Source: Artificial Intelligence in MedicineAuthor(s): Luisa F. Sánchez-Peralta, Luis Bote-Curiel, Artzai Picón, Francisco M. Sánchez-Margallo, J. Blas Pagador (Source: Artificial Intelligence in Medicine)
Source: Artificial Intelligence in Medicine - August 3, 2020 Category: Bioinformatics Source Type: research

Mindfulness and Creativity: Implications for Thinking and Learning
Publication date: Available online 1 August 2020Source: Thinking Skills and CreativityAuthor(s): Danah Henriksen, Carmen Richardson, Kyle Shack (Source: Thinking Skills and Creativity)
Source: Thinking Skills and Creativity - August 3, 2020 Category: Science Source Type: research

Molecules, Vol. 25, Pages 3545: Streptomyces sp. Strain MUSC 125 from Mangrove Soil in Malaysia with Anti-MRSA, Anti-Biofilm and Antioxidant Activities
Bey-Hing Goh There is an urgent need to search for new antibiotics to counter the growing number of antibiotic-resistant bacterial strains, one of which is methicillin-resistant Staphylococcus aureus (MRSA). Herein, we report a Streptomyces sp. strain MUSC 125 from mangrove soil in Malaysia which was identified using 16S rRNA phylogenetic and phenotypic analysis. The methanolic extract of strain MUSC 125 showed anti-MRSA, anti-biofilm and antioxidant activities. Strain MUSC 125 was further screened for the presence of secondary metabolite biosynthetic genes. Our results indicated that both polyketide synthase (pks) ge...
Source: Molecules - August 3, 2020 Category: Chemistry Authors: Hefa Mangzira Kemung Loh Teng-Hern Tan Kok-Gan Chan Hooi-Leng Ser Jodi Woan-Fei Law Learn-Han Lee Bey-Hing Goh Tags: Article Source Type: research

IJERPH, Vol. 17, Pages 5593: Online Newspaper Framing of Non-Communicable Diseases: Comparison of Mainland China, Taiwan, Hong Kong and Macao
heong As non-communicable diseases (NCDs) are now well recognized as the leading cause of mortality among adult populations worldwide, they are also increasingly the focus of media coverage. As such, the objective of this study is to describe the framing of NCDs in the coverage of newspapers, with the understanding that it says something about the society producing it. Automatic content analysis was employed to examine disease topics, risks, and cost consequences, thus providing lay people with a chance of learning the etiology of NCDs and information available for fighting diseases. The result of the computational met...
Source: International Journal of Environmental Research and Public Health - August 3, 2020 Category: Environmental Health Authors: Angela Chang Peter J. Schulz Angus Wenheng Cheong Tags: Article Source Type: research

PSA-based machine learning model improves prostate cancer risk stratification in a screening population
ConclusionsDevelopment of a dense neural network model  improved the diagnostic accuracy in screening for prostate cancer. These results demonstrate an additional utility of machine learning methods in prostate cancer risk stratification when using biochemical parameters. (Source: World Journal of Urology)
Source: World Journal of Urology - August 3, 2020 Category: Urology & Nephrology Source Type: research

Improved metabolic function and cognitive performance in middle-aged adults following a single dose of wild blueberry
ConclusionsThis study indicated acute cognitive benefits of WBB intake in cognitively healthy middle-aged individuals, particularly in the context of demanding tasks and cognitive fatigue. WBB improved glucose and insulin responses to a meal. Further research is required to elucidate the underlying mechanism by which WBB improves cognitive function. (Source: European Journal of Nutrition)
Source: European Journal of Nutrition - August 3, 2020 Category: Nutrition Source Type: research

The Society for Prevention Research 20 Years Later: a Summary of Training Needs
AbstractThe Society for Prevention Research (SPR) aims to continually provide relevant professional development training opportunities to advance scientific investigation of ways to improve the health, well-being, and social and educational outcomes of individuals and communities. Our study, led by the Training Needs Assessment Task Force, designed a quantitative questionnaire informed by semistructured, qualitative interviews of 13 key prevention science informants. The questionnaire was deployed to all SPR members, of which 347 completed it. Questions about training topics were asked along 8 categories: (1) theory; (2) p...
Source: Prevention Science - August 3, 2020 Category: Psychiatry & Psychology Source Type: research

Knowledge Difference of Tumor Nutrition Risk Among Thoracic Cancer Patients, Their Family Members, Physicians, and Nurses
AbstractTo investigate the difference among patients, family members, physicians, and nurses in their ability to identify malnutrition risk in patients with thoracic cancer. The enrolled patients were evaluated by the NRS2002 nutritional risk scale. The patient-centered groups, including the patient, the primary caretaker, the physician, and the nurse, were given a questionnaire on their knowledge and understanding of nutrition therapy in cancer treatment. The incidence rate of nutritional risk in hospitalized patients with thoracic cancer was 13.8%. There were significant differences in the accuracy rate of nutritional ri...
Source: Journal of Cancer Education - August 3, 2020 Category: Cancer & Oncology Source Type: research

Effect of Missing Data Imputation on Deep Learning Prediction Performance for Vesicoureteral Reflux and Recurrent Urinary Tract Infection Clinical Study.
In this study, the effects of multiple imputation techniques MICE and FAMD on the performance of DL in the differential diagnosis were compared. The data of a retrospective cross-sectional study including 611 pediatric patients were evaluated (425 with VUR, 186 with rUTI, 26.65% missing ratio) in this research. CNTK and R 3.6.3 have been used for evaluating different models for 34 features (physical, laboratory, and imaging findings). In the differential diagnosis of VUR and rUTI, the best performance was obtained by deep learning with MICE algorithm with its values, respectively, 64.05% accuracy, 64.59% sensitivity, and 6...
Source: Biomed Res - August 2, 2020 Category: Research Authors: Köse T, Özgür S, Coşgun E, Keskinoğlu A, Keskinoğlu P Tags: Biomed Res Int Source Type: research

Multilanguage-handwriting self-powered recognition based on triboelectric nanogenerator enabled machine learning
Publication date: November 2020Source: Nano Energy, Volume 77Author(s): Weiqiang Zhang, Linfeng Deng, Lei Yang, Ping Yang, Dongfeng Diao, Pengfei Wang, Zhong Lin Wang (Source: Nano Energy)
Source: Nano Energy - August 2, 2020 Category: Nanotechnology Source Type: research

An Intelligent Diagnosis Method of Brain MRI Tumor Segmentation Using Deep Convolutional Neural Network and SVM Algorithm.
Authors: Wu W, Li D, Du J, Gao X, Gu W, Zhao F, Feng X, Yan H Abstract Among the currently proposed brain segmentation methods, brain tumor segmentation methods based on traditional image processing and machine learning are not ideal enough. Therefore, deep learning-based brain segmentation methods are widely used. In the brain tumor segmentation method based on deep learning, the convolutional network model has a good brain segmentation effect. The deep convolutional network model has the problems of a large number of parameters and large loss of information in the encoding and decoding process. This paper propose...
Source: Computational and Mathematical Methods in Medicine - August 2, 2020 Category: Statistics Tags: Comput Math Methods Med Source Type: research

Memory and metamemory for social interactions: Evidence for a metamemory expectancy illusion.
Authors: Mieth L, Schaper ML, Kuhlmann BG, Bell R Abstract People do not always have accurate metacognitive awareness of the conditions that lead to good source memory. In Experiment 1, participants studied words referring to bathroom and kitchen items that were either paired with an expected or unexpected room as the source. Participants provided judgments of item and source learning after each item-source pair. In line with previous studies, participants incorrectly predicted their memory to be better for expected than for unexpected sources. Here, we show that this metamemory expectancy illusion generalizes to s...
Source: Memory and Cognition - August 2, 2020 Category: Neuroscience Tags: Mem Cognit Source Type: research

Review on intrusion detection using feature selection with machine learning techniques
Publication date: Available online 31 July 2020Source: Materials Today: ProceedingsAuthor(s): C. Kalimuthan, J. Arokia Renjit (Source: Materials Today: Proceedings)
Source: Materials Today: Proceedings - August 2, 2020 Category: Materials Science Source Type: research

Data Augmentation for Deep-Learning-Based Electroencephalography
Publication date: Available online 31 July 2020Source: Journal of Neuroscience MethodsAuthor(s): Elnaz Lashgari, Dehua Liang, Uri Maoz (Source: Journal of Neuroscience Methods)
Source: Journal of Neuroscience Methods - August 2, 2020 Category: Neuroscience Source Type: research

Automated Classification of Postural Control for Individuals With Parkinson's Disease Using a Machine Learning Approach: A Preliminary Study.
In conclusion, participants with PD exhibited impaired postural stability and their postural sway features could be identified by machine learning algorithms. PMID: 32736341 [PubMed - as supplied by publisher] (Source: Journal of Applied Biomechanics)
Source: Journal of Applied Biomechanics - August 2, 2020 Category: Sports Medicine Tags: J Appl Biomech Source Type: research

Xanthone ‐enriched fraction of Garcinia mangostana and α‐mangostin improve the spatial learning and memory of chronic cerebral hypoperfusion rats
ConclusionsHowever, α‐MG (50 mg/kg) and XEFGM (100 mg/kg) reversed the cognitive impairment induced by CCH in MWM test. α‐MG (50 mg/kg) was further tested upon sub‐acute 14‐day treatment in CCH rats. Cognitive improvement was shown in MWM test but not in long‐term potentiation (LTP). BDNF but not CaMKII was found to be down‐regulated in CCH rats; however, both parameters were not affected by α‐MG. In conclusion, α‐MG ameliorated learning and memory deficits in both acute and sub‐acute treatments in CCH rats by improving the spatial learning but not hippocampal LTP. H...
Source: Journal of Pharmacy and Pharmacology - August 2, 2020 Category: Drugs & Pharmacology Authors: Ning Tiang, Mohamad Anuar Ahad, Vikneswaran Murugaiyah, Zurina Hassan Tags: Research Paper Source Type: research

Transforming sustainability science for practice: a social –ecological systems framework for training sustainability professionals
AbstractNew applied approaches are needed to address urgent, global environmental issues. Practitioners, scholars, and policy makers alike call for increased integration of natural and social sciences to develop new frameworks for better addressing the range of contemporary environmental issues. From a theoretical perspective, social –ecological systems (SES) offers a novel approach for enhancing sustainability science and for improving the practice of environmental management. To translate SES theory into action, education and training programs are needed that focus on the application of SES approaches across the ed...
Source: Sustainability Science - August 2, 2020 Category: Science Source Type: research

Acute cognitive deficits after traumatic brain injury predict Alzheimer ’s disease-like degradation of the human default mode network
AbstractTraumatic brain injury (TBI) and Alzheimer ’s disease (AD) are prominent neurological conditions whose neural and cognitive commonalities are poorly understood. The extent of TBI-related neurophysiological abnormalities has been hypothesized to reflect AD-like neurodegeneration because TBI can increase vulnerability to AD. However, it rema ins challenging to prognosticate AD risk partly because the functional relationship between acute posttraumatic sequelae and chronic AD-like degradation remains elusive. Here, functional magnetic resonance imaging (fMRI), network theory, and machine learning (ML) are levera...
Source: AGE - August 2, 2020 Category: Geriatrics Source Type: research

Sensors, Vol. 20, Pages 4308: Scalable Fleet Monitoring and Visualization for Smart Machine Maintenance and Industrial IoT Applications
Sofie Van Hoecke The wide adoption of smart machine maintenance in manufacturing is blocked by open challenges in the Industrial Internet of Things (IIoT) with regard to robustness, scalability and security. Solving these challenges is of uttermost importance to mission-critical industrial operations. Furthermore, effective application of predictive maintenance requires well-trained machine learning algorithms which on their turn require high volumes of reliable data. This paper addresses both challenges and presents the Smart Maintenance Living Lab, an open test and research platform that consists of a fleet of drive...
Source: Sensors - August 2, 2020 Category: Biotechnology Authors: Pieter Moens Vincent Bracke Colin Soete Sander Vanden Hautte Diego Nieves Avendano Ted Ooijevaar Steven Devos Bruno Volckaert Sofie Van Hoecke Tags: Article Source Type: research

IJERPH, Vol. 17, Pages 5574: Measurement Method for Evaluating the Lockdown Policies during the COVID-19 Pandemic
lnajjar Coronavirus Disease 2019 (COVID-19) has affected day to day life and slowed down the global economy. Most countries are enforcing strict quarantine to control the havoc of this highly contagious disease. Since the outbreak of COVID-19, many data analyses have been done to provide close support to decision-makers. We propose a method comprising data analytics and machine learning classification for evaluating the effectiveness of lockdown regulations. Lockdown regulations should be reviewed on a regular basis by governments, to enable reasonable control over the outbreak. The model aims to measure the efficiency...
Source: International Journal of Environmental Research and Public Health - August 2, 2020 Category: Environmental Health Authors: Mohammed Al Zobbi Belal Alsinglawi Omar Mubin Fady Alnajjar Tags: Article Source Type: research

Current Concepts in the Management of Trigger Finger in Adults.
Authors: Gil JA, Hresko AM, Weiss AC Abstract Trigger finger (TF) is one of the most common causes of hand disability. Immobilization of TF with a joint-blocking orthosis has been demonstrated to effectively relieve pain and improve function. The efficacy of steroid injections for TF varies based on the number of affected digits and the clinical severity of the condition. Up to three repeat steroid injections are effective in most patients. When conservative interventions are unsuccessful, open surgical release of the A1 pulley effectively alleviates the subjective and objective manifestations of TF and currently r...
Source: The Journal of the American Academy of Orthopaedic Surgeons - August 1, 2020 Category: Orthopaedics Tags: J Am Acad Orthop Surg Source Type: research

Resident, Fellow, and Attending Perception of E-Learning During the COVID-19 Pandemic and Implications on Future Orthopaedic Education.
CONCLUSION: E-learning has been an important modality to continue academic pursuits during the disruption in usual education and training schedules during the COVID-19 pandemic. Most trainees and attendings surveyed felt that e-learning should play a supplementary role in resident and fellow education moving forward. Although e-learning does provide an opportunity to hold multi-institutional conferences and makes participation in meetings logistically easier, it cannot fully replicate the dynamic interactions and benefits of in-person learning. PMID: 32732495 [PubMed - as supplied by publisher] (Source: The Journal of ...
Source: The Journal of the American Academy of Orthopaedic Surgeons - August 1, 2020 Category: Orthopaedics Tags: J Am Acad Orthop Surg Source Type: research

Decentralized Machine-Learning-Based Predictive Control of Nonlinear Processes
Publication date: Available online 31 July 2020Source: Chemical Engineering Research and DesignAuthor(s): Scarlett Chen, Zhe Wu, Panagiotis D. Christofides (Source: Chemical Engineering Research and Design)
Source: Chemical Engineering Research and Design - August 1, 2020 Category: Chemistry Source Type: research

AI learns to recognise individual birds from behind
Publication date: 1 August 2020Source: New Scientist, Volume 247, Issue 3293Author(s): Michael Le Page (Source: New Scientist)
Source: New Scientist - August 1, 2020 Category: Science Source Type: research

Deep learning for predicting the occurrence of cardiopulmonary diseases in Nanjing, China.
In this study, we established four different deep learning (DL) models to capture inherent long-term dependencies in sequences and potential complex relationships among constituents by initiating with the original input into a representation at a higher abstract level. We collected 504,555 and 786,324 hospital outpatient visits of grouped categories of respiratory (RESD) and circulatory system disease (CCD), respectively, in Nanjing from 2013 through 2018. The matched observations in time-series that might pose risk to cardiopulmonary health involved conventional air pollutants concentrations and metrological conditions. T...
Source: Chemosphere - August 1, 2020 Category: Chemistry Authors: Wang C, Qi Y, Zhu G Tags: Chemosphere Source Type: research

Learning sameness: object and relational similarity across species
Publication date: February 2021Source: Current Opinion in Behavioral Sciences, Volume 37Author(s): Stella Christie (Source: Current Opinion in Behavioral Sciences)
Source: Current Opinion in Behavioral Sciences - August 1, 2020 Category: Psychiatry & Psychology Source Type: research

Controlling Degrees of Freedom in Learning a Taekwondo Kick.
Authors: Guimarães AN, Ugrinowitsch H, Dascal JB, Okazaki VHA Abstract To test Bernstein's degrees of freedom (DF) hypothesis, the authors analyzed the effect of practice on the DF control and interjoint coordination of a Taekwondo kick. Thirteen inexperienced and 11 expert Taekwondo practitioners were evaluated. Contrary to Bernstein's hypothesis, the inexperienced group froze the DF at the end of learning, reducing the joint range of motion of the knee. Moderate and strong cross-correlations between joints did not change, demonstrating that the interjoint coordination was maintained. The inexperienced grou...
Source: Motor Control - August 1, 2020 Category: Neurology Tags: Motor Control Source Type: research

Do Illness Perception Predict Perceived Learning Needs Among Patients Treated With Percutaneous Coronary Intervention
Background The number of coronary heart disease (CHD) patients treated with percutaneous coronary intervention (PCI) has increased. The illness perception (IP) of PCI recipients needs to be evaluated. Yet, little is known whether patients' IP predicts perceived learning needs among patients treated with PCI. Objective The aim of this study was to assess patients' IP and to examine its influence on perceived learning needs post PCI. Methods A cross-sectional design was used. A convenience sample of 208 patients who had undergone first-time PCI participated in the study. Data were collected before patients were disch...
Source: Dimensions of Critical Care Nursing - August 1, 2020 Category: Nursing Tags: Educational DIMENSION Source Type: research

Genetic privacy: We must learn from the story of Henrietta Lacks
Henrietta Lacks's cells are used in experiments in laboratories around the world but were cultivated without her consent. The lessons from her story are more important than ever, says Maninder Ahluwalia (Source: New Scientist - Health)
Source: New Scientist - Health - August 1, 2020 Category: Consumer Health News Source Type: research

Understanding integrated care at the frontline using learning organisation theory: a participatory evaluation of locality level multi-professional teams in East London
Publication date: Available online 31 July 2020Source: Social Science & MedicineAuthor(s): Mirza Lalani, Sonia Bussu, Martin Marshall (Source: Social Science and Medicine)
Source: Social Science and Medicine - August 1, 2020 Category: Psychiatry & Psychology Source Type: research

Machine learning in oncology: a review.
Authors: Nardini C Abstract Machine learning is a set of techniques that promise to greatly enhance our data-processing capability. In the field of oncology, ML presents itself with a wealth of possible applications to the research and the clinical context, such as automated diagnosis and precise treatment modulation. In this paper, we will review the principal applications of ML techniques in oncology and explore in detail how they work. This will allow us to discuss the issues and challenges that ML faces in this field, and ultimately gain a greater understanding of ML techniques and how they can improve oncologi...
Source: Ecancermedicalscience - August 1, 2020 Category: Cancer & Oncology Tags: Ecancermedicalscience Source Type: research

Common cardiovascular risk factors and in-hospital mortality in 3,894 patients with COVID-19: survival analysis and machine learning-based findings from the multicentre Italian CORIST Study
Publication date: Available online 31 July 2020Source: Nutrition, Metabolism and Cardiovascular DiseasesAuthor(s): Augusto Di Castelnuovo, Marialaura Bonaccio, Simona Costanzo, Alessandro Gialluisi, Andrea Antinori, Nausicaa Berselli, Lorenzo Blandi, Raffaele Bruno, Roberto Cauda, Giovanni Guaraldi, Ilaria My, Lorenzo Menicanti, Agostino Parruti, Giuseppe Patti, Stefano Perlini, Francesca Santilli, Carlo Signorelli, Giulio G. Stefanini, Alessandra Vergori, Amina Abdeddaim (Source: Nutrition, Metabolism and Cardiovascular Diseases)
Source: Nutrition, Metabolism and Cardiovascular Diseases - August 1, 2020 Category: Nutrition Source Type: research

Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation
Convolutional neural networks (CNNs) have been extensively applied to two-dimensional (2D) medical image segmentation, yielding excellent performance. However, their application to three-dimensional (3D) nodul... (Source: Cancer Imaging)
Source: Cancer Imaging - August 1, 2020 Category: Radiology Authors: Xianling Dong, Shiqi Xu, Yanli Liu, Aihui Wang, M. Iqbal Saripan, Li Li, Xiaolei Zhang and Lijun Lu Tags: Research article Source Type: research

Individual Differences in Learning Abilities Impact Structure Addition: Better Learners Create More Structured Languages.
Abstract Over the last decade, iterated learning studies have provided compelling evidence for the claim that linguistic structure can emerge from non-structured input, through the process of transmission. However, it is unclear whether individuals differ in their tendency to add structure, an issue with implications for understanding who are the agents of change. Here, we identify and test two contrasting predictions: The first sees learning as a pre-requisite for structure addition, and predicts a positive correlation between learning accuracy and structure addition, whereas the second maintains that it is those...
Source: Cognitive Science - August 1, 2020 Category: Neuroscience Authors: Johnson T, Siegelman N, Arnon I Tags: Cogn Sci Source Type: research

Challenging infections in pregnancy
Maternal sepsis is “a life-threatening condition defined as organ dysfunction resulting from infection during pregnancy, childbirth, post-abortion, or postpartum period.” (World Health Organisation, 2017). Serious infection during, or immediately after, pregnancy may go initially unrecognized in an otherwise young and healthy group, who nevertheless do have a compromized immune system. Secondly, whilst malaise, flushes, nausea, vomiting and abdominal pain are common in pregnancy, each can herald sepsis with rapid demise for mother and baby. (Source: Obstetrics, Gynaecology and Reproductive Medicine)
Source: Obstetrics, Gynaecology and Reproductive Medicine - August 1, 2020 Category: OBGYN Authors: Marina Morgan Tags: Case-based learning Source Type: research

Utility of Artificial Intelligence Amidst the COVID 19 Pandemic: A Review
AbstractThe term machine learning refers to a collection of tools used for identifying patterns in data. As opposed to traditional methods of pattern identification, machine learning tools relies on artificial intelligence to map out patters from large amounts of data, can self-improve as and when new data becomes available and is quicker in accomplishing these tasks. This review describes various techniques of machine learning that have been used in the past in the prediction, detection and management of infectious diseases, and how these tools are being brought into the battle against COVID-19. In addition, we also discu...
Source: Journal of Medical Systems - August 1, 2020 Category: Information Technology Source Type: research

Does the availability of orthography support L2 word learning?
AbstractAvailability of orthography during word learning has been found to facilitate learning the word ’s spelling and pronunciation and has been proposed to facilitate learning its meaning. This has not been studied in second language (L2) learning yet, in which word learning often corresponds to translation learning. Therefore, an L2 word learning experiment was carried out. Grade 6 Dutch student s (n = 92) were taught English words, with orthography available or absent. Words were divided into those that are spelled entirely like they sound (consistent, e.g.,lilt) and those that are not (inconsisten...
Source: Reading and Writing - August 1, 2020 Category: Child Development Source Type: research

Sensors, Vol. 20, Pages 4300: A Deep Learning Model for Fault Diagnosis with a Deep Neural Network and Feature Fusion on Multi-Channel Sensory Signals
Liu Collecting multi-channel sensory signals is a feasible way to enhance performance in the diagnosis of mechanical equipment. In this article, a deep learning method combined with feature fusion on multi-channel sensory signals is proposed. First, a deep neural network (DNN) made up of auto-encoders is adopted to adaptively learn representative features from sensory signal and approximate non-linear relation between symptoms and fault modes. Then, Locality Preserving Projection (LPP) is utilized in the fusion of features extracted from multi-channel sensory signals. Finally, a novel diagnostic model based on multi...
Source: Sensors - August 1, 2020 Category: Biotechnology Authors: Ye Liu Liu Tags: Article Source Type: research

Sensors, Vol. 20, Pages 4299: Evaluation of Salmon, Tuna, and Beef Freshness Using a Portable Spectrometer
In this study, we demonstrated a system to determine food freshness by analyzing the spectral response from a portable visible/near-infrared (VIS/NIR) spectrometer using the Convolutional Neural Network (CNN)-based machine learning algorithm. Spectral response data from salmon, tuna, and beef incubated at 25 °C were obtained every minute for 30 h and then categorized into three states of “fresh”, “likely spoiled”, and “spoiled” based on time and pH. Using the obtained spectral data, a CNN-based machine learning algorithm was bui...
Source: Sensors - August 1, 2020 Category: Biotechnology Authors: Eui Jung Moon Youngsik Kim Yu Xu Yeul Na Amato J. Giaccia Jae Hyung Lee Tags: Letter Source Type: research

Sensors, Vol. 20, Pages 4301: A Novel Pulmonary Nodule Detection Model Based on Multi-Step Cascaded Networks
ang Jiang Pulmonary nodule detection in chest computed tomography (CT) is of great significance for the early diagnosis of lung cancer. Therefore, it has attracted more and more researchers to propose various computer-assisted pulmonary nodule detection methods. However, these methods still could not provide convincing results because the nodules are easily confused with calcifications, vessels, or other benign lumps. In this paper, we propose a novel deep convolutional neural network (DCNN) framework for detecting pulmonary nodules in the chest CT image. The framework consists of three cascaded networks: First, a U-ne...
Source: Sensors - August 1, 2020 Category: Biotechnology Authors: Jianning Chi Shuang Zhang Xiaosheng Yu Chengdong Wu Yang Jiang Tags: Article Source Type: research

IJERPH, Vol. 17, Pages 5570: Management of Primary Dysmenorrhea among University Students in the South of Spain and Family Influence
This study identifies the need for education on self-care and management of menstrual pain. (Source: International Journal of Environmental Research and Public Health)
Source: International Journal of Environmental Research and Public Health - August 1, 2020 Category: Environmental Health Authors: Mar ía Laura Parra-Fernández Mar ía Dolores Onieva-Zafra Ana Abreu-S ánchez Juan Diego Ramos-Pichardo Mar ía Teresa Iglesias-López Elia Fern ández-Martínez Tags: Article Source Type: research

Personalized machine learning approach to predict candidemia in medical wards
AbstractPurposeCandidemia is a highly lethal infection; several scores have been developed to assist the diagnosis process and recently different models have been proposed. Aim of this work was to assess predictive performance of a Random Forest (RF) algorithm for early detection of candidemia in the internal medical wards (IMWs).MethodsA set of 42 potential predictors was acquired in a sample of 295 patients (male: 142, age: 72  ± 15 years; candidemia: 157/295; bacteremia: 138/295). Using tenfold cross-validation, a RF algorithm was compared with a classic stepwise multivariable logistic regressi...
Source: Infection - August 1, 2020 Category: Infectious Diseases Source Type: research

Middle-Level Features for the Explanation of Classification Systems by Sparse Dictionary Methods.
ini G Abstract Machine learning (ML) systems are affected by a pervasive lack of transparency. The eXplainable Artificial Intelligence (XAI) research area addresses this problem and the related issue of explaining the behavior of ML systems in terms that are understandable to human beings. In many explanation of XAI approaches, the output of ML systems are explained in terms of low-level features of their inputs. However, these approaches leave a substantive explanatory burden with human users, insofar as the latter are required to map low-level properties into more salient and readily understandable parts of the ...
Source: International Journal of Neural Systems - August 1, 2020 Category: Neurology Authors: Apicella A, Isgrò F, Prevete R, Tamburrini G Tags: Int J Neural Syst Source Type: research