Primary Care

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

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Application of electronic trigger tools to identify targets for improving diagnostic safety.

Progress in reducing diagnostic errors remains slow partly due to poorly defined methods to identify...

Deep learning and virtual drug screening.

Current drug development is still costly and slow given tremendous technological advancements in dru...

Can nurses remain relevant in a technologically advanced future?

Technological breakthroughs occur at an ever-increasing rate thereby revolutionizing human health an...

Transforming Diabetes Care Through Artificial Intelligence: The Future Is Here.

An estimated 425 million people globally have diabetes, accounting for 12% of the world's health exp...

The basal to total insulin ratio in outpatients with diabetes on basal-bolus regimen.

OBJECTIVE: To evaluate the basal/total ratio of daily insulin dose (b/T) in outpatients with diabete...

Therapeutic Enoxaparin in the Morbidly Obese Patient: A Case Report and Review of the Literature.

Enoxaparin is a low molecular weight heparin commonly used in the treatment of venous thromboembolis...

Instance-Based Representation Using Multiple Kernel Learning for Predicting Conversion to Alzheimer Disease.

The early detection of Alzheimer's disease and quantification of its progression poses multiple diff...

Deep learning-based quantification of abdominal fat on magnetic resonance images.

Obesity is increasingly prevalent and associated with increased risk of developing type 2 diabetes, ...

An accessible and efficient autism screening method for behavioural data and predictive analyses.

Autism spectrum disorder is associated with significant healthcare costs, and early diagnosis can su...

Digital diabetes: Perspectives for diabetes prevention, management and research.

Digital medicine, digital research and artificial intelligence (AI) have the power to transform the ...

Discovering Highly Potent Molecules from an Initial Set of Inactives Using Iterative Screening.

The versatility of similarity searching and quantitative structure-activity relationships to model t...

Fibroblast growth factor23 is associated with axonal integrity and neural network architecture in the human frontal lobes.

Elevated levels of FGF23 in individuals with chronic kidney disease (CKD) are associated with advers...

Using predicate and provenance information from a knowledge graph for drug efficacy screening.

BACKGROUND: Biomedical knowledge graphs have become important tools to computationally analyse the c...

Digital Diabetes Data and Artificial Intelligence: A Time for Humility Not Hubris.

In the future artificial intelligence (AI) will have the potential to improve outcomes diabetes care...

Mixed effect machine learning: A framework for predicting longitudinal change in hemoglobin A1c.

Accurate and reliable prediction of clinical progression over time has the potential to improve the ...

Identifying people at risk of developing type 2 diabetes: A comparison of predictive analytics techniques and predictor variables.

BACKGROUND: The present study aims to identify the patients at risk of type 2 diabetes (T2D). There ...

Pivotal trial of an autonomous AI-based diagnostic system for detection of diabetic retinopathy in primary care offices.

Artificial Intelligence (AI) has long promised to increase healthcare affordability, quality and acc...

Automated retinopathy of prematurity screening using deep neural networks.

BACKGROUND: Retinopathy of prematurity (ROP) is the leading cause of childhood blindness worldwide. ...

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