Primary Care

Latest AI and machine learning research in primary care for healthcare professionals.

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Natural language processing of electronic medical records identifies cardioprotective agents for anthracycline induced cardiotoxicity.

In this retrospective observational study, we aimed to investigate the potential of natural language...

Validation of a machine learning model for indirect screening of suicidal ideation in the general population.

Suicide is among the leading causes of death worldwide and a concerning public health problem, accou...

Food-derived DPP4 inhibitors: Drug discovery based on high-throughput virtual screening and deep learning.

Dipeptidyl peptidase-4 (DPP-4) is a critical target for the treatment of type 2 diabetes. This study...

Disease diagnostics using machine learning of B cell and T cell receptor sequences.

Clinical diagnosis typically incorporates physical examination, patient history, various laboratory ...

Enhanced in silico QSAR-based screening of butyrylcholinesterase inhibitors using multi-feature selection and machine learning.

Butyrylcholinesterase inhibition offers one of the formulated solutions to tackle the aggravating sy...

Intracranial stenosis prediction using a small set of risk factors in the Tromsø Study.

Intracranial atherosclerotic stenosis (ICAS) refers to a narrowing of intracranial arteries due to p...

Personalised screening tool for early detection of sarcopenia in stroke patients: a machine learning-based comparative study.

BACKGROUND: Sarcopenia is a common complication in patients with stroke, adversely affecting recover...

An extensive experimental analysis for heart disease prediction using artificial intelligence techniques.

The heart is an important organ that plays a crucial role in maintaining life. Unfortunately, heart ...

Building an intelligent diabetes Q&A system with knowledge graphs and large language models.

INTRODUCTION: This paper introduces an intelligent question-answering system designed to deliver per...

Machine learning or traditional statistical methods for predictive modelling in perioperative medicine: A narrative review.

Prediction of outcomes in perioperative medicine is key to decision-making and various prediction mo...

The Role of Artificial Intelligence in Obesity Risk Prediction and Management: Approaches, Insights, and Recommendations.

Greater than 650 million individuals worldwide are categorized as obese, which is associated with si...

Artificial Intelligence Methods for Diagnostic and Decision-Making Assistance in Chronic Wounds: A Systematic Review.

Chronic wounds, which take over four weeks to heal, are a major global health issue linked to condit...

Diabetic peripheral neuropathy detection of type 2 diabetes using machine learning from TCM features: a cross-sectional study.

AIMS: Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus. Ear...

Leveraging OGTT derived metabolic features to detect Binge-eating disorder in individuals with high weight: a "seek out" machine learning approach.

Binge eating disorder (BED) carries a 6 times higher risk for obesity and accounts for roughly 30% o...

Predicting diabetes self-management education engagement: machine learning algorithms and models.

INTRODUCTION: Diabetes self-management education (DSME) is endorsed by the American Diabetes Associa...

Impact of pectoral muscle removal on deep-learning-based breast cancer risk prediction.

State-of-the-art breast cancer risk (BCR) prediction models have been originally trained on mammogra...

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