Primary Care

Obesity

Latest AI and machine learning research in obesity for healthcare professionals.

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Machine learning-based clustering identifies obesity subgroups with differential multi-omics profiles and metabolic patterns.

OBJECTIVE: Individuals living with obesity are differentially susceptible to cardiometabolic disease...

The uropathologist of the future: getting ready with intelligence for the prostate cancer tsunami.

According to the recently published paper by the Lancet Commission on prostate cancer (PCa) , the pr...

Study of obesity research using machine learning methods: A bibliometric and visualization analysis from 2004 to 2023.

BACKGROUND: Obesity, a multifactorial and complex health condition, has emerged as a significant glo...

Emergency Department Length of Stay Classification Based on Ensemble Methods and Rule Extraction.

This study employs machine learning techniques to identify factors that influence extended Emergency...

DeePhafier: a phage lifestyle classifier using a multilayer self-attention neural network combining protein information.

Bacteriophages are the viruses that infect bacterial cells. They are the most diverse biological ent...

Predicting Cardiovascular Disease Risk in Tobacco Users Using Machine Learning Algorithms.

Cardiovascular Diseases (CVDs) present a substantial global health burden, with tobacco use as a maj...

Dynamic Inverse Reinforcement Learning for Feedback-driven Reward Estimation in Brain Machine Interface Tasks.

Reinforcement learning (RL)-based brain machine interfaces (BMIs) provide a promising solution for p...

The Diagnosis of Cardiovascular Disease Using Simple Blood Biomarkers Through AI and Big Data.

Cardiovascular disease (CVD) is the leading cause of global mortality, diagnosed primarily through c...

Noninvasive detection of diabetes in obstructive sleep apnea based on overnight SpO signal and deep learning.

The prevalence of obstructive sleep apnea comorbid with diabetes is high while the awareness of diab...

Towards the development of a FAIR-compliant biomedical ontology for colorectal cancer.

Despite the widespread development of ontologies in many domains of healthcare, the field of colorec...

Novel Alzheimer's Disease Stating Based on Comorbidities-Informed Graph Neural Networks.

Alzheimer's Disease (AD), the most prevalent form of dementia, requires early prediction for timely ...

Strengths, weaknesses, opportunities, and threats of using AI-enabled technology in sleep medicine: a commentary.

UNLABELLED: Over the past few years, artificial intelligence (AI) has emerged as a powerful tool use...

Understanding and predicting pregnancy termination in Bangladesh: A comprehensive analysis using a hybrid machine learning approach.

Reproductive health issues, including unsafe pregnancy termination, remain a significant concern for...

Disease-driven domain generalization for neuroimaging-based assessment of Alzheimer's disease.

Development of deep learning models to evaluate structural brain changes caused by cognitive impairm...

Enhancing Thrombophilia Risk Prediction Through AI-Based Methodologies.

Thrombophilia, a predisposition to thrombosis, poses significant diagnostic challenges due to its mu...

Patient-Reported Outcomes for Robot-Assisted Laparoscopic Extravascular Renal Vein Stent Placements for Nutcracker Syndrome.

Nutcracker phenomenon is the compression of the left renal vein between the superior mesenteric art...

PCAO2: an ontology for integration of prostate cancer associated genotypic, phenotypic and lifestyle data.

Disease ontologies facilitate the semantic organization and representation of domain-specific knowle...

[Preliminary study on automatic quantification and grading of leopard spots fundus based on deep learning technology].

To achieve automatic segmentation, quantification, and grading of different regions of leopard spot...

Deep learning-based BMI inference from structural brain MRI reflects brain alterations following lifestyle intervention.

Obesity is associated with negative effects on the brain. We exploit Artificial Intelligence (AI) to...

Importance of Serum Albumin in Deep Learning-Based Prediction of Cognitive Function Data in the Aged Using a Basic Blood Test.

BACKGROUND: Recently, a method using deep learning has been developed to estimate the risk of develo...

Comparison of machine learning models to predict complications of bariatric surgery: A systematic review.

Due to changes in lifestyle, bariatric surgery is expanding worldwide. However, this surgery has nu...

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