Primary Care

Obesity

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

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Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure.

Hyperuricemia is a global health concern, with environmental chemicals as risk factors. This study u...

A lightweight graph neural network to predict long-term mortality in coronary artery disease patients: an interpretable causality-aware approach.

BACKGROUND: Coronary artery disease (CAD) causes substantial death toll in the United States and wor...

Radiation and contrast dose reduction in coronary CT angiography for slender patients with 70 kV tube voltage and deep learning image reconstruction.

OBJECTIVE: To evaluate the radiation and contrast dose reduction potential of combining 70 kV with d...

Comparing logistic regression and machine learning for obesity risk prediction: A systematic review and meta-analysis.

BACKGROUND: Logistic regression (LR) has traditionally been the standard method used for predicting ...

From classical approaches to artificial intelligence, old and new tools for PDAC risk stratification and prediction.

Pancreatic ductal adenocarcinoma (PDAC) is recognized as one of the most lethal malignancies, charac...

Hugan Tiaoshen Formula Improves the Comorbid Mechanism of Schizophrenia and Sleep Disorder via Multitarget Interaction Network.

This study aims to integrate cross-disease omics data and perform multidimensional analysis to uncov...

Use of machine learning techniques to predict poor survival after hematopoietic cell transplantation for myelofibrosis.

With the incorporation of effective therapies for myelofibrosis (MF), accurately predicting outcomes...

Enhancing osteoporosis risk prediction using machine learning: A holistic approach integrating biomarkers and clinical data.

Osteoporosis (OP) affects approximately 18 % of the global population, with osteoporosis-associated ...

NLP for computational insights into nutritional impacts on colorectal cancer care.

Colorectal cancer (CRC) is one of the most prominent cancers globally, with its incidence rising amo...

Identifying the key predictors of positive self-perceptions of aging using machine learning.

This study aimed to identify key predictors of self-perceptions of aging (SPA) among older adults by...

Machine learning-based prediction of hearing loss: Findings of the US NHANES from 2003 to 2018.

The prevalence of hearing loss (HL) has emerged as an escalating public health concern globally. The...

An Ultra-Low Power Wearable BMI System With Continual Learning Capabilities.

Driven by the progress in efficient embedded processing, there is an accelerating trend toward runni...

Research on multi-algorithm and explainable AI techniques for predictive modeling of acute spinal cord injury using multimodal data.

Machine learning technology has been extensively applied in the medical field, particularly in the c...

Predictive factors of hypoglycemia in type 2 diabetes: a prospective study using machine learning.

Hypoglycemia is a serious complication in individuals with type 2 diabetes mellitus. Identifying who...

Predicting cardiovascular risk with hybrid ensemble learning and explainable AI.

Cardiovascular diseases (CVDs) are still one of the leading causes of death globally, underscoring t...

[Expert consensus on systematic assessment and treatment of refractory wounds in the elderly (2025 edition)].

Early prevention and standardized management of refractory wounds in the elderly are very important ...

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