Primary Care

Obesity

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

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Advancing Cardiovascular, Kidney, and Metabolic Medicine: A Narrative Review of Insights and Innovations for the Future.

Cardiovascular, kidney and metabolic (CKM) conditions are interrelated, significantly contributing t...

Constructing machine learning-based risk prediction model for osteoarthritis in population aged 45 and above: NHANES 2011-2018.

Osteoarthritis is a widespread chronic joint disease, becoming increasingly prevalent, particularly ...

Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.

Primary care consultations provide an opportunity for patients and clinicians to assess asthma attac...

Intelligent Care: A Scientometric Analysis of Artificial Intelligence in Precision Medicine.

The integration of advanced computational methods into precision medicine represents a transformativ...

Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology.

BACKGROUND AND AIM: Colorectal cancer is among the most prevalent and deadliest cancers. Early predi...

Artificial intelligence models utilize lifestyle factors to predict dry eye related outcomes.

The purpose of this study is to examine and interpret machine learning models that predict dry eye (...

Assessing the association of multi-environmental chemical exposures on metabolic syndrome: A machine learning approach.

Metabolic syndrome (MetS) is a major global public health concern due to its rising prevalence and a...

Changes in recreational drug use, reasons for those changes and their consequence during and after the COVID-19 pandemic in the UK.

Changes in drug use in the general population during the COVID-19 pandemic and their long-term conse...

Dietary and lifestyle determinants of vitamin D status in the UK Biobank Cohort study for predictive modeling.

Vitamin D (VD) is involved in a wide variety of physiological processes. The high prevalence of VD d...

Machine learning integration of multimodal data identifies key features of circulating NT-proBNP in people without cardiovascular diseases.

N-Terminal Pro-Brain Natriuretic Peptide (NT-proBNP) is important for diagnosing and predicting hear...

Structural brain pattern abnormalities in tinnitus with and without hearing loss.

OBJECTIVE: Subjective tinnitus often coexists with hearing loss, and they share common pathophysiolo...

Early obesity risk prediction via non-dietary lifestyle factors using machine learning approaches.

Obesity poses a significant health threat, contributing to the development of noncommunicable diseas...

Comparing machine learning models for osteoporosis prediction in Tibetan middle aged and elderly women.

The aim of this study was to establish the optimal prediction model by comparing the prediction effe...

Fine-tuned deep learning models for early detection and classification of kidney conditions in CT imaging.

The kidney plays a vital role in maintaining homeostasis, but lifestyle factors and diseases can lea...

Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007-2018.

OBJECTIVES: This study aimed to compare the performance of five machine learning algorithms to predi...

Capsule DenseNet++: Enhanced autism detection framework with deep learning and reinforcement learning-based lifestyle recommendation.

Autism Spectrum Disorder (ASD) is a complex neurological condition that impairs the ability to inter...

A diagnostic model for polycystic ovary syndrome based on machine learning.

Diagnosis of polycystic ovary syndrome remains a challenge. In this study, we propose constructing a...

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