Primary Care

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

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Machine Learning-Driven D-Glucose Prediction Using a Novel Biosensor for Non-Invasive Diabetes Management.

Developing reliable noninvasive diagnostic and monitoring systems for diabetes remains a significant...

Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning.

BACKGROUND: Metabolic diseases (MDs), exemplified by diabetes, hypertension, and dyslipidemia, have ...

A Scoping Review of Artificial Intelligence for Precision Nutrition.

With the role of artificial intelligence (AI) in precision nutrition rapidly expanding, a scoping re...

What Are Patients' Perceptions and Attitudes Regarding the Use of Artificial Intelligence in Skin Cancer Screening and Diagnosis? Narrative Review.

Artificial intelligence (AI) could enable early diagnosis of skin cancer; however, how AI should be ...

Artificial intelligence-enabled lipid droplets quantification: Comparative analysis of NIS-elements Segment.ai and ZeroCostDL4Mic StarDist networks.

Lipid droplets (LDs) are dynamic organelles that are present in almost all cell types, with a partic...

Machine learning approach on plasma proteomics identifies signatures associated with obesity in the KORA FF4 cohort.

AIMS: This study investigated the role of plasma proteins in obesity to identify predictive biomarke...

Development and validation of a machine learning approach for screening new leprosy cases based on the leprosy suspicion questionnaire.

Leprosy is a dermatoneurological disease and can cause irreversible nerve damage. In addition to bei...

Is personality associated with the lived experience of the NHS England low calorie diet programme: A pilot study.

This pilot study explored the use of a novel behavioural artificial intelligence (AI) tool to examin...

The Central Role of Learning in Preventing Foot Complications in Persons With Diabetes: A Scoping Review.

BACKGROUND: Despite a variety of literature reviews, there is limited understanding of the learning ...

Identification and taste presentation characteristics of umami peptides from soybean paste based on peptidomics and virtual screening.

This research concentrated on soybean paste fermented with Tetragenococcus halophilus, employing pep...

Fast screening of COVID-19 inpatient samples by integrating machine learning and label-free SERS methods.

BACKGROUND: Advances in bio-analyte detection demonstrate the need for innovation to overcome the li...

Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction.

PURPOSE: Artificial intelligence (AI) could reduce lung cancer screening computer tomography (CT)-re...

Intelligent larval zebrafish phenotype recognition via attention mechanism for high-throughput screening.

BACKGROUND: Larval zebrafish phenotypes serve as critical research indicators in fields such as ecot...

Quality assurance and validity of AI-generated single best answer questions.

BACKGROUND: Recent advancements in generative artificial intelligence (AI) have opened new avenues i...

Detecting severe coronary artery stenosis in T2DM patients with NAFLD using cardiac fat radiomics-based machine learning.

To analyze radiomics features of cardiac adipose tissue in individuals with type 2 diabetes (T2DM) a...

A feature explainability-based deep learning technique for diabetic foot ulcer identification.

Diabetic foot ulcers (DFUs) are a common and serious complication of diabetes, presenting as open so...

Early gestational diabetes mellitus risk predictor using neural network with NearMiss.

BACKGROUND: Gestational diabetes mellitus (GDM) is globally recognized as a significant pregnancy-re...

Recent topics in musculoskeletal imaging focused on clinical applications of AI: How should radiologists approach and use AI?

The advances in artificial intelligence (AI) technology in recent years have been remarkable, and th...

An efficient catalyst screening strategy combining machine learning and causal inference.

Due to the diversity of catalyst synthesis methods, the optimization of catalysts by traditional exp...

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