Primary Care

Screening and Diagnosis of Chronic Pharyngitis Based on Deep Learning.

Chronic pharyngitis is a common disease, which has a long duration and a wide range of onset. It is ...

Effects of obesity on breast size, thoracic spine structure and function, upper torso musculoskeletal pain and physical activity in women.

PURPOSE: This study investigated the effects of obesity on breast size, thoracic spine structure and...

Detection of smoking status from retinal images; a Convolutional Neural Network study.

Cardiovascular diseases are directly linked to smoking habits, which has both physiological and anat...

Development and Prospective Validation of a Machine Learning-Based Risk of Readmission Model in a Large Military Hospital.

BACKGROUND: Thirty-day hospital readmissions are a quality metric for health care systems. Predictiv...

A pilot study of autonomous artificial intelligence-based diabetic retinopathy screening in Poland.

Artificial Intelligence (AI) for the early detection of breast cancer: a scoping review to assess AI's potential in breast screening practice.

INTRODUCTION: Various factors are driving interest in the application of artificial intelligence (AI...

Artificial intelligence for diabetic retinopathy screening in Africa.

Deep learning in ophthalmology: The technical and clinical considerations.

The advent of computer graphic processing units, improvement in mathematical models and availability...

An ensemble learning method for asthma control level detection with leveraging medical knowledge-based classifier and supervised learning.

Approximately 300 million people are afflicted with asthma around the world, with the estimated deat...

Directional Relationship Between Vitamin D Status and Prediabetes: A New Approach from Artificial Neural Network in a Cohort of Workers with Overweight-Obesity.

Despite the increasing literature on the association of diabetes with inflammation, cardiovascular ...

Matched Learning for Optimizing Individualized Treatment Strategies Using Electronic Health Records.

Current guidelines for treatment decision making largely rely on data from randomized controlled tri...

Regional level influenza study based on Twitter and machine learning method.

The significance of flu prediction is that the appropriate preventive and control measures can be ta...

Accuracy of American College of Surgeons National Surgical Quality Improvement Program Universal Surgical Risk Calculator in Predicting Complications Following Robot-Assisted Radical Cystectomy at a National Comprehensive Cancer Center.

There is paucity of literature about the validation of the American College of Surgeons National Su...

Predicting childhood obesity using electronic health records and publicly available data.

BACKGROUND: Because of the strong link between childhood obesity and adulthood obesity comorbidities...

Efficient Deep Network Architectures for Fast Chest X-Ray Tuberculosis Screening and Visualization.

Automated diagnosis of tuberculosis (TB) from chest X-Rays (CXR) has been tackled with either hand-c...

Applications of machine learning in GPCR bioactive ligand discovery.

GPCRs constitute the largest druggable family having targets for 475 Food and Drug Administration (F...

Predictive Estimates of Risks Associated with Type 2 Diabetes Mellitus on the Basis of Biochemical Biomarkers and Derived Time-Dependent Parameters.

Systems Pharmacological Approach to Investigate the Mechanism of for Application to Alzheimer's Disease.

(OC)-a traditional Chinese medicine (TCM)-has been reported to have large numbers of flavonoids, al...

Specific impact of past and new major cardiovascular events on acute kidney injury and end-stage renal disease risks in diabetes: a dynamic view.

BACKGROUND: Interconnections between major cardiovascular events (MCVEs) and renal events are recogn...

Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study.

PURPOSE: To study the feasibility of automatically identifying normal digital mammography (DM) exams...

Application of Machine Learning to Identify Clustering of Cardiometabolic Risk Factors in U.S. Adults.

The aim of this study is to compare some machine learning methods with traditional statistical para...