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The ENDORSE Feasibility Study: Exploring the Use of M-Health, Artificial Intelligence and Serious Games for the Management of Childhood Obesity.
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Application of artificial intelligence in diagnosis and treatment of colorectal cancer: A novel Prospect.
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Future of Artificial Intelligence Applications in Cancer Care: A Global Cross-Sectional Survey of Researchers.
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Artificial Intelligence for the Prediction and Early Diagnosis of Pancreatic Cancer: Scoping Review.
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Machine learning-based radiomics model to predict benign and malignant PI-RADS v2.1 category 3 lesions: a retrospective multi-center study.
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Artificial intelligence-aided lytic spinal bone metastasis classification on CT scans.
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Fully-Automated detection of small bowel carcinoid tumors in CT scans using deep learning.
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Artificial Intelligence-Aided Endoscopy and Colorectal Cancer Screening.
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A Deep Learning Radiomics Nomogram to Predict Response to Neoadjuvant Chemotherapy for Locally Advanced Cervical Cancer: A Two-Center Study.
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Acute on chronic liver failure: prognostic models and artificial intelligence applications.
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Classification of lapses in smokers attempting to stop: A supervised machine learning approach using data from a popular smoking cessation smartphone app.
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A risk prediction model based on machine learning for early cognitive impairment in hypertension: Development and validation study.
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Screening for Osteoporosis from Blood Test Data in Elderly Women Using a Machine Learning Approach.
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Development and validation of machine learning models for nonalcoholic fatty liver disease.
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Functional activity level reported by an informant is an early predictor of Alzheimer's disease.
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Deep learning-based EEG analysis to classify normal, mild cognitive impairment, and dementia: algorithms and dataset.
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Detecting individuals with severe mental illness using artificial intelligence applied to magnetic resonance imaging.
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An Intelligent Diabetic Patient Tracking System Based on Machine Learning for E-Health Applications.
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Application of Artificial Intelligence in Assessing the Self-Management Practices of Patients with Type 2 Diabetes.
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Developing Automated Computer Algorithms to Track Periodontal Disease Change from Longitudinal Electronic Dental Records.
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Predicting Social Determinants of Health in Patient Navigation: Case Study.
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Artificial Intelligence in Emergency Medicine: a Viewpoint of Current Applications, Foreseeable Opportunities and Challenges.
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Capturing children food exposure using wearable cameras and deep learning.
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Quantitative Evaluation of Spatial Accessibility of Various Urban Medical Services Based on Big Data of Outpatient Appointments.
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Harnessing Machine Learning in Tackling Domestic Violence-An Integrative Review.
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Disaggregating Latino nativity in equity research using electronic health records.
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Towards a deeper understanding of pain: How machine learning and deep learning algorithms are needed to provide the next generation of pain medicine for use in the clinic.
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An efficient landmark model for prediction of suicide attempts in multiple clinical settings.
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Evaluating the Performance of Machine Learning Methods for Risk Estimation of Delirium in Patients Hospitalized from the Emergency Department.
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Biocompatible and Long-Term Monitoring Strategies of Wearable, Ingestible and Implantable Biosensors: Reform the Next Generation Healthcare.
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Big Data Analytics to Reduce Preventable Hospitalizations-Using Real-World Data to Predict Ambulatory Care-Sensitive Conditions.
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Machine learning prognosis model based on patient-reported outcomes for chronic heart failure patients after discharge.
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A machine-learning based bio-psycho-social model for the prediction of non-obstructive and obstructive coronary artery disease.
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Artificial intelligence-based diagnosis of acute pulmonary embolism: Development of a machine learning model using 12-lead electrocardiogram.
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The Use of Artificial Intelligence to Predict the Development of Atrial Fibrillation.
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Identification of Recurrent Atrial Fibrillation using Natural Language Processing Applied to Electronic Health Records.
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Performance Evaluation of Quantum-Based Machine Learning Algorithms for Cardiac Arrhythmia Classification.
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Applications of Artificial Intelligence in Thrombocytopenia.
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Explainable Machine Learning Model to Predict COVID-19 Severity Among Older Adults in the Province of Quebec.
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Machine Learning Prediction of Urine Cultures in Primary Care.
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Artificial Intelligence for Antimicrobial Resistance Prediction: Challenges and Opportunities towards Practical Implementation.
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Using Machine Learning to Predict Antimicrobial Resistance-A Literature Review.
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Artificial intelligence in public health: the potential of epidemic early warning systems.
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Leveraging deep learning to improve vaccine design.
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Real-Time Prediction of Sepsis in Critical Trauma Patients: Machine Learning-Based Modeling Study.
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Detecting dengue fever in children using online Rasch analysis to develop algorithms for parents: An APP development and usability study.
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Machine learning algorithm to predict mortality in critically ill patients with sepsis-associated acute kidney injury.
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Computer-Aided Diagnosis of COVID-19 from Chest X-ray Images Using Hybrid-Features and Random Forest Classifier.
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DDPM: A Dengue Disease Prediction and Diagnosis Model Using Sentiment Analysis and Machine Learning Algorithms.
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Comparative Analysis of Clinical and CT Findings in Patients with SARS-CoV-2 Original Strain, Delta and Omicron Variants.
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Automated Quantification of Pneumonia Infected Volume in Lung CT Images: A Comparison with Subjective Assessment of Radiologists.
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Prediction model for gestational diabetes mellitus using the XG Boost machine learning algorithm.
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