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Visit Types in Primary Care With Telehealth Use During the COVID-19 Pandemic: Systematic Review
Visit Types in Primary Care With Telehealth Use During the COVID-19 Pandemic: Systematic Review
Background: Telehealth was rapidly incorporated into primary care during the COVID-19 pandemic. However, there is limited ...
Medical Text Simplification Using Reinforcement Learning (TESLEA): Deep Learning–Based Text Simplification Approach
Medical Text Simplification Using Reinforcement Learning (TESLEA): Deep Learning–Based Text Simplification Approach
Background: In most cases, the abstracts of articles in the medical domain are publicly available. Although these are acce...
Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study
Perspective Toward Machine Learning Implementation in Pediatric Medicine: Mixed Methods Study
Background: Given the costs of machine learning implementation, a systematic approach to prioritizing which models to impl...
The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing
The Real-World Experiences of Persons With Multiple Sclerosis During the First COVID-19 Lockdown: Application of Natural Language Processing
Background: The increasing availability of “real-world” data in the form of written text holds promise for deepening our u...
Shared Interoperable Clinical Decision Support Service for Drug-Allergy Interaction Checks: Implementation Study
Shared Interoperable Clinical Decision Support Service for Drug-Allergy Interaction Checks: Implementation Study
Background: Clinical decision support (CDS) can improve health care with respect to the quality of care, patient safety, e...
A Transfer Learning Approach to Correct the Temporal Performance Drift of Clinical Prediction Models: Retrospective Cohort Study
A Transfer Learning Approach to Correct the Temporal Performance Drift of Clinical Prediction Models: Retrospective Cohort Study
Background: Clinical prediction models suffer from performance drift as the patient population shifts over time. There is ...
Realizing the Potential of Computer-Assisted Surgery by Embedding Digital Twin Technology
Realizing the Potential of Computer-Assisted Surgery by Embedding Digital Twin Technology
The value of virtual world and digital phenotyping has been demonstrated in several fields, and their applications in the ...
Discovery and Analytical Validation of a Vocal Biomarker to Monitor Anosmia and Ageusia in Patients With COVID-19: Cross-sectional Study
Discovery and Analytical Validation of a Vocal Biomarker to Monitor Anosmia and Ageusia in Patients With COVID-19: Cross-sectional Study
Background: The COVID-19 disease has multiple symptoms, with anosmia and ageusia being the most prevalent, varying from 75...
Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study
Classifying Comments on Social Media Related to Living Kidney Donation: Machine Learning Training and Validation Study
Background: Living kidney donation currently constitutes approximately a quarter of all kidney donations. There exist barr...
Developing an Automated Assessment of In-session Patient Activation for Psychological Therapy: Codevelopment Approach
Developing an Automated Assessment of In-session Patient Activation for Psychological Therapy: Codevelopment Approach
Background: Patient activation is defined as a patient’s confidence and perceived ability to manage their own health. Pati...
The Application of Graph Theoretical Analysis to Complex Networks in Medical Malpractice in China: Qualitative Study
The Application of Graph Theoretical Analysis to Complex Networks in Medical Malpractice in China: Qualitative Study
Background: Studies have shown that hospitals or physicians with multiple malpractice claims are more likely to be involve...
Managing Critical Patient-Reported Outcome Measures in Oncology Settings: System Development and Retrospective Study
Managing Critical Patient-Reported Outcome Measures in Oncology Settings: System Development and Retrospective Study
Background: Remote monitoring programs based on the collection of patient-reported outcome (PRO) data are being increasing...
Automatic Screening of Pediatric Renal Ultrasound Abnormalities: Deep Learning and Transfer Learning Approach
Automatic Screening of Pediatric Renal Ultrasound Abnormalities: Deep Learning and Transfer Learning Approach
Background: In recent years, the progress and generalization surrounding portable ultrasonic probes has made ultrasound (U...
Linking Biomedical Data Warehouse Records With the National Mortality Database in France: Large-scale Matching Algorithm
Linking Biomedical Data Warehouse Records With the National Mortality Database in France: Large-scale Matching Algorithm
Background: Often missing from or uncertain in a biomedical data warehouse (BDW), vital status after discharge is central ...
Tooth-Related Disease Detection System Based on Panoramic Images and Optimization Through Automation: Development Study
Tooth-Related Disease Detection System Based on Panoramic Images and Optimization Through Automation: Development Study
Background: Early detection of tooth-related diseases in patients plays a key role in maintaining their dental health and ...
Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities
Lifting Hospital Electronic Health Record Data Treasures: Challenges and Opportunities
Electronic health records (EHRs) have been successfully used in data science and machine learning projects. However, most ...
Relation Extraction in Biomedical Texts Based on Multi-Head Attention Model With Syntactic Dependency Feature: Modeling Study
Relation Extraction in Biomedical Texts Based on Multi-Head Attention Model With Syntactic Dependency Feature: Modeling Study
Background: With the rapid expansion of biomedical literature, biomedical information extraction has attracted increasing ...
Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning Approach
Identifying Patients With Heart Failure Who Are Susceptible to De Novo Acute Kidney Injury: Machine Learning Approach
Background: Studies have shown that more than half of patients with heart failure (HF) with acute kidney injury (AKI) have...
A Recurrent Neural Network Model for Predicting Activated Partial Thromboplastin Time After Treatment With Heparin: Retrospective Study
A Recurrent Neural Network Model for Predicting Activated Partial Thromboplastin Time After Treatment With Heparin: Retrospective Study
Background: Anticoagulation therapy with heparin is a frequent treatment in intensive care units and is monitored by activ...