Primary Care

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

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RASPELD to Perform High-End Screening in an Academic Environment toward the Development of Cancer Therapeutics.

The identification of compounds for dissecting biological functions and the development of novel dru...

Automatic polyp frame screening using patch based combined feature and dictionary learning.

Polyps in the colon can potentially become malignant cancer tissues where early detection and remova...

An Intelligent Model for Blood Vessel Segmentation in Diagnosing DR Using CNN.

Diabetic retinopathy (DR) is an eye disease, which affects the people who are all having the diabete...

Evaluation of antiproliferative and protective effects of Eupatorium cannabinum L. extracts.

Eupatorium cannabinum L. (Asteraceae) has been used for a long time for medicinal purposes due to it...

Multiscaled Fusion of Deep Convolutional Neural Networks for Screening Atrial Fibrillation From Single Lead Short ECG Recordings.

Atrial fibrillation (AF) is one of the most common sustained chronic cardiac arrhythmia in elderly p...

Improved perfusion pattern score association with type 2 diabetes severity using machine learning pipeline: Pilot study.

BACKGROUND: Type 2 diabetes mellitus (T2DM) is associated with alterations in the blood-brain barrie...

Use of Deep Learning to Examine the Association of the Built Environment With Prevalence of Neighborhood Adult Obesity.

IMPORTANCE: More than one-third of the adult population in the United States is obese. Obesity has b...

Artificial intelligence in retina.

Major advances in diagnostic technologies are offering unprecedented insight into the condition of t...

Prioritising references for systematic reviews with RobotAnalyst: A user study.

Screening references is a time-consuming step necessary for systematic reviews and guideline develop...

Current trends of digital solutions for diabetes management.

Industry 4.0 is an updated concept of smart production, which is identified with the fourth industri...

Identification of lead anti-human cytomegalovirus compounds targeting MAP4K4 via machine learning analysis of kinase inhibitor screening data.

Chemogenomic approaches involving highly annotated compound sets and cell based high throughput scre...

OC-2-KB: integrating crowdsourcing into an obesity and cancer knowledge base curation system.

BACKGROUND: There is strong scientific evidence linking obesity and overweight to the risk of variou...

Network-Based Drug Discovery: Coupling Network Pharmacology with Phenotypic Screening for Neuronal Excitability.

Diseases such as chronic pain with complex etiologies are unlikely to respond to single, target-spec...

Estimating individualized optimal combination therapies through outcome weighted deep learning algorithms.

With the advancement in drug development, multiple treatments are available for a single disease. Pa...

Machine learning algorithm-based risk prediction model of coronary artery disease.

In view of high mortality associated with coronary artery disease (CAD), development of an early pre...

Future Direction for Using Artificial Intelligence to Predict and Manage Hypertension.

PURPOSE OF REVIEW: Evidence that artificial intelligence (AI) is useful for predicting risk factors ...

A new computational intelligence approach to detect autistic features for autism screening.

Autism Spectrum Disorder (ASD) is one of the fastest growing developmental disability diagnosis. Gen...

Perturbation-Theory and Machine Learning (PTML) Model for High-Throughput Screening of Parham Reactions: Experimental and Theoretical Studies.

Machine learning (ML) algorithms are gaining importance in the processing of chemical information an...

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