Predicting unrecognized enhancer-mediated genome topology by an ensemble machine learning model [METHOD]
Transcriptional enhancers commonly work over long genomic distances to precisely regulate spatiotemporal gene expression patterns. Dissecting the promoters physically contacted by these distal regulatory elements is essential for understanding developmental processes as well as the role of disease-associated risk variants. Modern proximity-ligation assays, like HiChIP and ChIA-PET, facilitate the accurate identification of long-range contacts between enhancers and promoters. However, these assays are technically challenging, expensive, and time-consuming, making it difficult to investigate enhancer topologies, especially i...
Source: Genome Research - November 12, 2020 Category: Genetics & Stem Cells Authors: Tang, L., Hill, M. C., Wang, J., Wang, J., Martin, J. F., Li, M. Tags: METHOD Source Type: research

ASPEN President's Address: "The 2020 Overture: A New Tune For the Future".
This article is protected by copyright. All rights reserved. PMID: 33180961 [PubMed - as supplied by publisher] (Source: JPEN Journal Of Parenteral And Enteral Nutrition)
Source: JPEN Journal Of Parenteral And Enteral Nutrition - November 12, 2020 Category: Nutrition Authors: Chan LN Tags: JPEN J Parenter Enteral Nutr Source Type: research

Setting up a successful nurse-led intravitreal injections service: pearls from Swindon.
Abstract The demand for performing intravitreal injections has increased in recent years, prompting the need for more nurse training in their administration. The Great Western Hospitals NHS Trust in Swindon has developed a structured nurse training programme and now has 8 independent nurse injectors trained to undertake injections independently; nurse practitioners now contribute upwards of 85% of the total number of injections. The authors have also demonstrated the financial benefits of using injection assistant devices and shown the positive impact such devices have on training. In September 2019, the authors o...
Source: British Journal of Nursing - November 12, 2020 Category: Nursing Authors: Hasan H, Mamtora S, Shah N Tags: Br J Nurs Source Type: research

Comparison between osteosynthesis with interlocking nail and minimally invasive plating for proximal- and middle-thirds of humeral shaft fractures
ConclusionIntramedullary interlocking nail seemed to be superior to minimally invasive plate osteosynthesis in the treatment of proximal- and middle-thirds of humeral shaft fractures due to shorter operative time and union time, less early post-operative pain, and fewer complications. The intramedullary interlocking nail could be considered a better surgical option for the management of proximal middle humeral fractures, though it may also depend on the surgeons ’ skills and learning curve. Further in-depth prospective studies are in great need to verify our conclusion. (Source: International Orthopaedics)
Source: International Orthopaedics - November 12, 2020 Category: Orthopaedics Source Type: research

Pathways and Barriers to Careers in Academic Clinical Cancer Prevention: a Qualitative Study
AbstractNational surveys document steady declines over time in interest in academic medicine and cancer prevention careers (Am J Prev Med 54(3):444 –8,2018). Through interviews with 16 academic cancer prevention physicians at one comprehensive cancer center, this study identifies motivations and barriers to physician careers in academic cancer prevention and proposes recommendations to increase recruitment. Participants reported that cancer prevention was vague to them early in training, impairing career exploration. Further, without role models and opportunities to learn about cancer prevention, many were ignorant o...
Source: Journal of Cancer Education - November 12, 2020 Category: Cancer & Oncology Source Type: research

A Breath of Knowledge: Overview of Current Adolescent E-cigarette Prevention and Cessation Programs
ConclusionsAlthough the programs reviewed largely incorporated theory and included key components known to be effective, there are some gaps in the programs ’ overall ability to prevent and stop adolescents from using e-cigarettes, such as lack of dedicated e-cigarette materials. More evidence-based tools, resources, and evaluations are needed to best inform adolescent e-cigarette cessation. Addressing the gaps that existing prevention and cessation p rograms present requires intervening at multiple systematic levels, conducting more rigorous program evaluations, and bolstering the availability of cessation programs....
Source: Current Addiction Reports - November 12, 2020 Category: Addiction Source Type: research

Editorial: Individualizing Interventions for Young Children With Autism: Embracing the Next Generation of Intervention Research
“If you have known one child with autism, you have known one child with autism.” Clinical heterogeneity is a defining feature of autism spectrum disorder (ASD). This includes heterogeneity of implicated genes, etiological pathways, neurocognitive mechanisms, behavioral characteristics, comorbid conditions, and developmental trajectories. It is not surprising that children with ASD also vary greatly in their response to interventions. A better understanding of “which children benefit from which intervention” is critical to ensure that each child has access to the most effective interven tion, deliver...
Source: Journal of the American Academy of Child and Adolescent Psychiatry - November 12, 2020 Category: Psychiatry Authors: Michael Siller Tags: Editorial Source Type: research

Deep learning based DNA:RNA triplex forming potential prediction
Long non-coding RNAs (lncRNAs) can exert functions via forming triplex with DNA. The current methods in predicting the triplex formation mainly rely on mathematic statistic according to the base paring rules. ... (Source: BMC Bioinformatics)
Source: BMC Bioinformatics - November 12, 2020 Category: Bioinformatics Authors: Yu Zhang, Yahui Long and Chee Keong Kwoh Tags: Software Source Type: research

Sensors, Vol. 20, Pages 6476: Real-Time Pattern-Recognition of GPR Images with YOLO v3 Implemented by Tensorflow
Zhi Qiu Artificial intelligence (AI) is widely used in pattern recognition and positioning. In most of the geological exploration applications, it needs to locate and identify underground objects according to electromagnetic wave characteristics from the ground-penetrating radar (GPR) images. Currently, a few robust AI approach can detect targets by real-time with high precision or automation for GPR images recognition. This paper proposes an approach that can be used to identify parabolic targets with different sizes and underground soil or concrete structure voids based on you only look once (YOLO) v3. With the Tenso...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Yuanhong Li Zuoxi Zhao Yangfan Luo Zhi Qiu Tags: Article Source Type: research

Sensors, Vol. 20, Pages 6475: Improving CSI Prediction Accuracy with Deep Echo State Networks in 5G Networks
icano The forthcoming fifth-generation networks require improvements in cognitive radio intelligence, going towards more smart and aware radio systems. In the emerging radio intelligence approach, the empowerment of cognitive capabilities is performed through the adoption of machine learning techniques. This paper investigates the combined application of the convolutional and recurrent neural networks for the channel state information forecasting, providing a multivariate scalar time series prediction by taking into account the multiple factors dependence of the channel state conditions. Finally, the system performance...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Tommaso Pecorella Romano Fantacci Benedetta Picano Tags: Article Source Type: research

Sensors, Vol. 20, Pages 6470: Demonstration of Three-Dimensional Indoor Visible Light Positioning with Multiple Photodiodes and Reinforcement Learning
Hong Chen To provide high-quality location-based services in the era of the Internet of Things, visible light positioning (VLP) is considered a promising technology for indoor positioning. In this paper, we study a multi-photodiodes (multi-PDs) three-dimensional (3D) indoor VLP system enhanced by reinforcement learning (RL), which can realize accurate positioning in the 3D space without any off-line training. The basic 3D positioning model is introduced, where without height information of the receiver, the initial height value is first estimated by exploring its relationship with the received signal strength (RSS),...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Zhang Chen Zeng Cao Hong Chen Tags: Article Source Type: research

A rat epigenetic clock recapitulates phenotypic aging and co-localizes with heterochromatin
This study aimed to generate a novel epigenetic clock in rats —a model with unique physical, physiological, and biochemical advantages—by incorporating behavioral data, unsupervised machine learning, and network analysis to identify epigenetic signals that not only track with age, but also relates to phenotypic aging. Reduced representation bisulfite seque ncing (RRBS) data was used to train an epigenetic age (DNAmAge) measure in Fischer 344 CDF (F344) rats. This measure correlated with age at (r = 0.93) in an independent sample, and related to physical functioning (p=5.9e-3), after adjusting for age and cell c...
Source: eLife - November 12, 2020 Category: Biomedical Science Tags: Computational and Systems Biology Genetics and Genomics Source Type: research

Exploring why we learn from productive failure: insights from the cognitive and learning sciences
This study compared the effectiveness of productive failure with indirect failure to further characterize the underpinni ng cognitive mechanisms of productive failure. Year one pharmacy students (N = 42) were randomly assigned to a productive failure or an indirect failure learning condition. The problem of estimating renal function based on serum creatinine was described to participants in the productive failure learning condition, who were then asked to generate a solution. Participants in the indirect failure condition learned about the same problem and were given incorrect solutions that other students ha...
Source: Advances in Health Sciences Education - November 12, 2020 Category: Universities & Medical Training Source Type: research

Peritoneal dialysis (PD) technique training: what features influence learning time?
ConclusionNumber of PD training sessions depends on the patient ’s age and comorbidities, but is not related to social, educational or employment status. Prolonged training duration was a statistically significant predictor of higher peritonitis risk, but it was not related to shorter permanence in PD in our series. Identifying these patients since the trainin g period would be useful to adapt training schedule as an early prevention strategy to minimize the risk of peritonitis and plan a preemptive retraining. (Source: Clinical and Experimental Nephrology)
Source: Clinical and Experimental Nephrology - November 12, 2020 Category: Urology & Nephrology Source Type: research

IJERPH, Vol. 17, Pages 8386: Machine Learning for Mortality Analysis in Patients with COVID-19
ria-Olivas Yasser Alakhdar-Mohmara This paper analyzes a sample of patients hospitalized with COVID-19 in the region of Madrid (Spain). Survival analysis, logistic regression, and machine learning techniques (both supervised and unsupervised) are applied to carry out the analysis where the endpoint variable is the reason for hospital discharge (home or deceased). The different methods applied show the importance of variables such as age, O2 saturation at Emergency Rooms (ER), and whether the patient comes from a nursing home. In addition, biclustering is used to globally analyze the patient-drug dataset, extracting s...
Source: International Journal of Environmental Research and Public Health - November 12, 2020 Category: Environmental Health Authors: Manuel S ánchez-Montañés Pablo Rodr íguez-Belenguer Antonio J. Serrano-L ópez Emilio Soria-Olivas Yasser Alakhdar-Mohmara Tags: Article Source Type: research

Using Machine Learning Analysis to Assist in Differentiating between Necrotizing Enterocolitis and Spontaneous Intestinal Perforation: A Novel Predictive Analytic Tool
Necrotizing enterocolitis (NEC) and spontaneous intestinal perforation (SIP) are devastating diseases in preterm neonates, often requiring surgical treatment. Previous studies evaluated outcomes in peritoneal drain placement versus laparotomy, but the accuracy of the presumptive diagnosis remains unknown without bowel visualization. Predictive analytics provide the opportunity to determine the etiology of perforation and guide surgical decision making. The purpose of this investigation was to build and evaluate machine learning models to differentiate NEC and SIP. (Source: Journal of Pediatric Surgery)
Source: Journal of Pediatric Surgery - November 12, 2020 Category: Surgery Authors: Allison C. Lure, Xinsong Du, Erik W. Black, Raechel Irons, Dominick J. Lemas, Janice A. Taylor, Orlyn Lavilla, Diomel de la Cruz, Josef Neu Source Type: research

Machine learning in precision medicine: lessons to learn
Nature Reviews Rheumatology, Published online: 12 November 2020; doi:10.1038/s41584-020-00538-2The ability to predict how a patient might respond to a medication would shift treatment decisions away from trial and error and reduce disease-associated health and financial burdens. Machine learning approaches applied to genomic datasets offer great promise to deliver personalized medicine but their application must first be optimized. (Source: Nature Reviews Rheumatology)
Source: Nature Reviews Rheumatology - November 12, 2020 Category: Rheumatology Authors: Darren Plant Anne Barton Source Type: research

Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study
AbstractMachine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the “multiclass machine learning (MCML)-based algorithms” (labelled as AtheroEdge 3.0ML) and assess whether considering carotid ultrasound imaging fused with conventional risk factors can provide better CVD/stroke risk prediction than conventional CVD risk calculators (CCVRC). Carotid ultrasound and coronary angiography were performed on 500 participants. Stenosis...
Source: The International Journal of Cardiovascular Imaging - November 12, 2020 Category: Radiology Source Type: research

Machine learning integration of circulating and imaging biomarkers for explainable patient-specific prediction of cardiac events: A prospective study
We sought to assess the performance of a comprehensive machine learning (ML) risk score integrating circulating biomarkers and computed tomography (CT) measures for the long-term prediction of hard cardiac events in asymptomatic subjects. (Source: Atherosclerosis)
Source: Atherosclerosis - November 12, 2020 Category: Cardiology Authors: Balaji K. Tamarappoo, Andrew Lin, Frederic Commandeur, Priscilla A. McElhinney, Sebastien Cadet, Markus Goeller, Aryabod Razipour, Xi Chen, Heidi Gransar, Stephanie Cantu, Robert JH. Miller, Stephan Achenbach, John Friedman, Sean Hayes, Louise Thomson, Na Source Type: research

Incorporation of a Machine Learning Algorithm With Object Detection Within the Thyroid Imaging Reporting and Data System Improves the Diagnosis of Genetic Risk
ConclusionsIncorporation of AI into TI-RADS improved radiologist performance and showed better malignancy risk prediction than AI alone when classifying thyroid nodules. Employing AI in existing thyroid nodule classification systems may help more accurately identifying high-risk nodules. (Source: Frontiers in Oncology)
Source: Frontiers in Oncology - November 12, 2020 Category: Cancer & Oncology Source Type: research

A Qualitative Study of Use of Mindfulness to Reduce Long-Term Use of Habit-Forming Prescription Drugs
Conclusions: Analyses suggested that mindfulness might increase individuals' control over medication intake by shifting individuals' attention toward present-moment sensory awareness of concrete stimuli, thereby facilitating other kinds of control, such as non-judgmental inner self-guidance and more adaptive ways of reducing distress. We suggest that it is the moment-to-moment sensory awareness and non-controlling observation of distress, together with inner self-guidance, that differentiates mindful control from dysfunctional attempts at direct, top down control of medication-use. (Source: Frontiers in Psychiatry)
Source: Frontiers in Psychiatry - November 12, 2020 Category: Psychiatry Source Type: research

Parents ’ Views on Young Children’s Distance Learning and Screen Time During COVID-19 Class Suspension in Hong Kong
. (Source: Early Education and Development)
Source: Early Education and Development - November 12, 2020 Category: Child Development Authors: Eva Yi Hung Lau Kerry Lee Source Type: research

Sensors, Vol. 20, Pages 6457: DLNR-SIQA: Deep Learning-Based No-Reference Stitched Image Quality Assessment
eon Lee Due to recent advancements in virtual reality (VR) and augmented reality (AR), the demand for high quality immersive contents is a primary concern for production companies and consumers. Similarly, the topical record-breaking performance of deep learning in various domains of artificial intelligence has extended the attention of researchers to contribute to different fields of computer vision. To ensure the quality of immersive media contents using these advanced deep learning technologies, several learning based Stitched Image Quality Assessment methods have been proposed with reasonable performances. However,...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Hayat Ullah Muhammad Irfan Kyungjin Han Jong Weon Lee Tags: Article Source Type: research

Sensors, Vol. 20, Pages 6460: Developing an Individual Glucose Prediction Model Using Recurrent Neural Network
In this study, we propose a personalized glucose prediction model using deep learning for hospitalized patients who experience Type-2 diabetes. We aim for our model to assist the medical personnel who check the blood glucose and control the amount of insulin doses. Herein, we employed a deep learning algorithm, especially a recurrent neural network (RNN), that consists of a sequence processing layer and a classification layer for the glucose prediction. We tested a simple RNN, gated recurrent unit (GRU), and long-short term memory (LSTM) and varied the architectures to determine the one with the best performance. For that,...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Dae-Yeon Kim Dong-Sik Choi Jaeyun Kim Sung Wan Chun Hyo-Wook Gil Nam-Jun Cho Ah Reum Kang Jiyoung Woo Tags: Article Source Type: research

Sensors, Vol. 20, Pages 6461: A Computerized Bioinspired Methodology for Lightweight and Reliable Neural Telemetry
We present bioinspired electroceptive compressive sensing (BeCoS) as an approach for minimizing these penalties. It is a lightweight and reliable approach for the compression and transmission of neural signals inspired by active electroceptive sensing used by weakly electric fish. It uses a signature signal and a sensed pseudo-sparse differential signal to transmit and reconstruct the signals remotely. We have used EEG datasets to compare BeCoS with the block sparse Bayesian learning-bound optimization (BSBL-BO) technique—A popular compressive sensing technique used for low-energy wireless telemonitoring of E...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Olufemi Adeluyi Miguel A. Risco-Castillo Mar ía Liz Crespo Andres Cicuttin Jeong-A Lee Tags: Article Source Type: research

Sensors, Vol. 20, Pages 6450: Meta-Transfer Learning Driven Tensor-Shot Detector for the Autonomous Localization and Recognition of Concealed Baggage Threats
i Naoufel Werghi Screening baggage against potential threats has become one of the prime aviation security concerns all over the world, where manual detection of prohibited items is a time-consuming and hectic process. Many researchers have developed autonomous systems to recognize baggage threats using security X-ray scans. However, all of these frameworks are vulnerable against screening cluttered and concealed contraband items. Furthermore, to the best of our knowledge, no framework possesses the capacity to recognize baggage threats across multiple scanner specifications without an explicit retraining process. To...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Taimur Hassan Muhammad Shafay Samet Ak çay Salman Khan Mohammed Bennamoun Ernesto Damiani Naoufel Werghi Tags: Article Source Type: research

Sensors, Vol. 20, Pages 6451: An sEMG-Controlled 3D Game for Rehabilitation Therapies: Real-Time Time Hand Gesture Recognition Using Deep Learning Techniques
zorla In recent years the advances in Artificial Intelligence (AI) have been seen to play an important role in human well-being, in particular enabling novel forms of human-computer interaction for people with a disability. In this paper, we propose a sEMG-controlled 3D game that leverages a deep learning-based architecture for real-time gesture recognition. The 3D game experience developed in the study is focused on rehabilitation exercises, allowing individuals with certain disabilities to use low-cost sEMG sensors to control the game experience. For this purpose, we acquired a novel dataset of seven gestures using t...
Source: Sensors - November 12, 2020 Category: Biotechnology Authors: Nadia Nasri Sergio Orts-Escolano Miguel Cazorla Tags: Letter Source Type: research

Molecules, Vol. 25, Pages 5277: Machine Learning Methods in Drug Discovery
nzhi Wang The advancements of information technology and related processing techniques have created a fertile base for progress in many scientific fields and industries. In the fields of drug discovery and development, machine learning techniques have been used for the development of novel drug candidates. The methods for designing drug targets and novel drug discovery now routinely combine machine learning and deep learning algorithms to enhance the efficiency, efficacy, and quality of developed outputs. The generation and incorporation of big data, through technologies such as high-throughput screening and high throu...
Source: Molecules - November 12, 2020 Category: Chemistry Authors: Lauv Patel Tripti Shukla Xiuzhen Huang David W. Ussery Shanzhi Wang Tags: Review Source Type: research

Voice perturbations under the stress overload in young individuals: phenotyping and suboptimal health as predictors for cascading pathologies
AbstractVerbal communication is one of the most sophisticated human motor skills reflecting both —the mental and physical health of an individual. Voice parameters and quality changes are usually secondary towards functional and/or structural laryngological alterations under specific systemic processes, syndrome and pathologies. These include but are not restricted to dry mouth and Sicca synd romes, body dehydration, hormonal alterations linked to pubertal, menopausal, and andropausal status, respiratory disorders, gastrointestinal reflux, autoimmune diseases, endocrinologic disorders, underweight versus overweight a...
Source: EPMA Journal - November 12, 2020 Category: International Medicine & Public Health Source Type: research

DRIM: A Web-Based System for Investigating Drug Response at the Molecular Level by Condition-Specific Multi-Omics Data Integration
Pharmacogenomics is the study of how genes affect a person's response to drugs. Thus, understanding the effect of drug at the molecular level can be helpful in both drug discovery and personalized medicine. Over the years, transcriptome data upon drug treatment has been collected and several databases compiled before drug treatment cancer cell multi-omics data with drug sensitivity (IC50, AUC) or time-series transcriptomic data after drug treatment. However, analyzing transcriptome data upon drug treatment is challenging since more than 20,000 genes interact in complex ways. In addition, due to the difficulty of both time-...
Source: Frontiers in Genetics - November 12, 2020 Category: Genetics & Stem Cells Source Type: research

Machine Learning Based Network Analysis Determined Clinically Relevant miRNAs in Breast Cancer
ConclusionWe predicted 90 breast cancer risk miRNAs based on proposed DMTN by using SVM classifier. Predicted risk miRNAs are biologically and clinically relevant in breast cancer. Risk miRNAs and one-step neighbor genes could serve as biomarkers for immune cell infiltration and anti-cancer drug response, which sheds lights on immunotherapy or targeted therapy for patients with breast cancer. (Source: Frontiers in Genetics)
Source: Frontiers in Genetics - November 12, 2020 Category: Genetics & Stem Cells Source Type: research

PasoDoble, a Proposed Dance/Music for People With Parkinson's Disease and Their Caregivers
Managing the heterogeneity of Parkinson's disease symptoms and its progressive nature demands strategies targeting the hallmark disrupted neurotransmission but also the comorbid derangements and bolstering neuroprotection and regeneration. Strong efforts are done to find disease-modifying strategies, since slowing disease progression is not enough to hamper its burden and some motor symptoms are resistant to dopamine-replacement therapy. The inclusion of non-pharmacological strategies can provide such a multitarget umbrella approach. The silent long-term biological process that precedes the clinical onset of disease is a c...
Source: Frontiers in Neurology - November 12, 2020 Category: Neurology Source Type: research

Inherent fire safety engineering in complex road tunnels – Learning between industries in safety management
Publication date: February 2021Source: Safety Science, Volume 134Author(s): Lene Østrem, Morten Sommer (Source: Safety Science)
Source: Safety Science - November 11, 2020 Category: Occupational Health Source Type: research

Lessons learned in the implementation of supplementary immunization activity (SIA) field guidelines for injectable vaccines - Experiences from Tanzania.
CONCLUSION: The 2019 SIA achieved high administrative coverage as a result of effective coordination; adequate micro-planning; timely logistical preparations; and effective demand creation activities. Future campaigns need to give high priority to hard-to-reach and densely populated areas during planning and ensure timely disbursement of funds to the operational level during implementation. PMID: 33164797 [PubMed - in process] (Source: Vaccine)
Source: Vaccine - November 11, 2020 Category: Allergy & Immunology Authors: Mohamed N, Simba D, Mphuru A, Lyimo D, Kyesi F Tags: Vaccine Source Type: research

Investigating the learning approaches of students in nursing education
Publication date: Available online 10 November 2020Source: Journal of Taibah University Medical SciencesAuthor(s): Sharifah Alsayed, Farhan Alshammari, Eddieson Pasay-an, Wireen Leila Dator (Source: Journal of Taibah University Medical Sciences)
Source: Journal of Taibah University Medical Sciences - November 11, 2020 Category: Universities & Medical Training Source Type: research

Arteriovenous anastomosis learning curve using low cost simulator
Conclusions It was found that the training model used was effective for increasing learning of this technique. It is believed that future studies with larger samples or a higher number of phases could demonstrate both reduced time and improved quality of the anastomoses performed with statisti cal significance. (Source: Jornal Vascular Brasileiro)
Source: Jornal Vascular Brasileiro - November 11, 2020 Category: Surgery Source Type: research

Outpatient Management of Sport-Related Concussion, Return to Learn, Return to Play
Outpatient sports-related concussion (SRC) management continues to evolve as evidence emerges supporting a multidisciplinary approach to the clinical assessment of SRC. Early active rehabilitation has replaced strict cognitive and physical rest. With this paradigm shift in management, pragmatic approaches are highly sought by busy clinicians that provide direction to individualized treatment, which can potentially expedite symptom resolution. Treatment strategies that address domain-based symptom constellations continue to be developed by clinician researchers. Although the optimal timing and dose of these domain-specific ...
Source: Clinics in Sports Medicine - November 11, 2020 Category: Sports Medicine Authors: Peter K. Kriz, James P. MacDonald Source Type: research

Shifts in intertrial interval duration in autoshaping with rats: Implications for path dependence
Publication date: November 2020Source: Learning and Motivation, Volume 72Author(s): Brian L. Thomas, Mauricio R. Papini (Source: Learning and Motivation)
Source: Learning and Motivation - November 11, 2020 Category: Psychiatry & Psychology Source Type: research

Noncontrast Computed Tomography-Based Radiomics Analysis in Discriminating Early Hematoma Expansion after Spontaneous Intracerebral Hemorrhage.
CONCLUSION: NCCT models based on multivariable, radiomics features and ML algorithm could improve the discrimination of early HE. The combined model was the best recommended model to identify sICH patients at risk of early HE. PMID: 33169546 [PubMed - as supplied by publisher] (Source: Korean Journal of Radiology)
Source: Korean Journal of Radiology - November 11, 2020 Category: Radiology Tags: Korean J Radiol Source Type: research

Development of a Malignancy Potential Binary Prediction Model Based on Deep Learning for the Mitotic Count of Local Primary Gastrointestinal Stromal Tumors.
CONCLUSION: We developed and preliminarily verified the GIST mitotic count binary prediction model, based on the VGG convolutional neural network. The model displayed a good predictive performance. PMID: 33169545 [PubMed - as supplied by publisher] (Source: Korean Journal of Radiology)
Source: Korean Journal of Radiology - November 11, 2020 Category: Radiology Tags: Korean J Radiol Source Type: research

Standardizing abortion education: what medical schools can learn from residency programs
Purpose of review With over 50 million abortions annually and 25% of pregnancies ending in abortion worldwide, abortion is one of the most common medical procedures. Yet abortion-related topics are glaringly absent from medical school curricula in the USA with half of medical schools including no formal training or only a single lecture. We explore abortion education in US medical schools and Obstetrics and Gynecology (Ob/Gyn) residency programs. Specifically, we review efforts to improve and standardize this training. Recent findings Despite documented interest in both learning and in the benefits of early expo...
Source: Current Opinion in Obstetrics and Gynecology - November 11, 2020 Category: OBGYN Tags: FAMILY PLANNING: Edited by Paul D. Blumenthal Source Type: research

Using artificial intelligence to assist radiologists in distinguishing COVID-19 from other pulmonary infections.
CONCLUSION: A deep learning algorithm-based AI model developed in this study successfully improved radiologists' performance in distinguishing COVID-19 from other pulmonary infections using chest CT images. PMID: 33164982 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - November 11, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

High-intensity interval training and active video gaming improve neurocognition in schizophrenia: a randomized controlled trial.
Authors: Bang-Kittilsen G, Egeland J, Holmen TL, Bigseth TT, Andersen E, Mordal J, Ulleberg P, Engh JA Abstract There is a need for treatments targeting neurocognitive dysfunctions in schizophrenia. The aim of this study was to investigate the neurocognitive effect of aerobic high-intensity interval training (HIIT). A comparison group performed sport simulating active video gaming (AVG). We anticipated that HIIT would improve neurocognition beyond any effect of AVG, due to engagement in higher intensity cardiorespiratory demands. Recent research on the beneficial neurocognitive effect of AVG challenges this expecta...
Source: European Archives of Psychiatry and Clinical Neuroscience - November 11, 2020 Category: Psychiatry Tags: Eur Arch Psychiatry Clin Neurosci Source Type: research

Resident-Led Neighborhood Development to Support Health: Identifying Strategies Using CBPR.
This study extends this work by developing partnerships with community organizations and neighborhood residents to address health disparities. Community-based participatory research (CBPR) methods were utilized to engage partners in a 10-month research process to address community concerns that impact health. Seven community residents, neighborhood researchers, engaged in workshops to learn about the research process and used techniques to gather information to implement action strategies. Neighborhood researchers selected 14 vacant lots to implement their action plan, which included visions for repurposing the land into a...
Source: American Journal of Community Psychology - November 11, 2020 Category: Psychiatry Tags: Am J Community Psychol Source Type: research

Experiential Learning Cycles as an Effective Means for Teaching Psychiatric Clinical Skills via Repeated Simulation in the Psychiatry Clerkship.
Authors: Meyer EG, Battista A, Sommerfeldt JM, West JC, Hamaoka D, Cozza KL Abstract OBJECTIVE: This retrospective study compares differences in clinical performance on the psychiatry clerkship Objective Structured Clinical Examination (OSCE) between students receiving traditional repeated clinical simulation with those receiving repeated clinical simulation using the Kolb Cycle. METHODS: Psychiatry clerkship OSCE scores from 321 students who completed their psychiatry clerkship in 2016 and 2017 were compared. Specific performance measures included communication skills as determined by the Essential Elements of...
Source: The Journal of American Association of Directors of Psychiatric Residency Training - November 11, 2020 Category: Psychiatry Tags: Acad Psychiatry Source Type: research

Teaching psychomotor skills online: exploring the implications of novel coronavirus on health professions education.
This article considers how the problem of physical distance might be overcome, so that quality skill education might continue. ISSUES: Psychomotor skills are undeniably easier to teach and learn F2F, and training schedules in tertiary, in-service and accredited professional courses reflect this. This aspect of HPE is therefore at significant risk in the context of social distancing and physical isolation. Psychomotor skills are much more complex than the physical motor outputs alone might suggest, and an F2F skill session is only one way to build the complementary aspects of new skill performance. This article argues t...
Source: Rural and Remote Health - November 11, 2020 Category: Rural Health Tags: Rural Remote Health Source Type: research

Two factors, one direction towards social regulation policy convergence: Learning from policy experts in Norway and India
Publication date: Available online 10 November 2020Source: AlterAuthor(s): Gagan Chhabra (Source: ALTER - European Journal of Disability Research)
Source: ALTER - European Journal of Disability Research - November 11, 2020 Category: Disability Source Type: research

A technical survey on various machine learning approaches for Parkinson’s disease classification
Publication date: Available online 10 November 2020Source: Materials Today: ProceedingsAuthor(s): B. Sabeena, S. Sivakumari, P. Amudha (Source: Materials Today: Proceedings)
Source: Materials Today: Proceedings - November 11, 2020 Category: Materials Science Source Type: research

Demographically Corrected Normative < b > < i > Z < /i > < /b > Scores on the Neuropsychological Test Battery in Cognitively Normal Older Chinese Adults
Conclusions: We constructed a multivariable regression-based normativeZ score method for the measurement of cognition among older Chinese individuals in the community. The normative score will be useful for the accurate diagnosis of different subtypes of pre-MCI and MCI after preliminary rapid screening in the community.Dement Geriatr Cogn Disord (Source: Dementia and Geriatric Cognitive Disorders)
Source: Dementia and Geriatric Cognitive Disorders - November 11, 2020 Category: Geriatrics Source Type: research

Charcot and His Passion for Dogs: A Historical Note
Jean-Martin Charcot, one of the most brilliant neurologists in history, was a man of few words and few gestures. He had an impenetrable and unmovable face and was described as being austere, reserved, and shy. In contrast, in his personal life, he was a softhearted man who loved animals – especially dogs. In this historical note, we sought to look into the past and learn more about Dr. Charcot’s personal life – which was robustly impacted by his passion for dogs.Eur Neurol (Source: European Neurology)
Source: European Neurology - November 11, 2020 Category: Neurology Source Type: research