Primary Care

Machine learning-based online web calculator predicts the risk of sarcopenic obesity in older adults.

BACKGROUND: Sarcopenic obesity (SO) has a higher risk of adverse health events compared to having obesity or sarcopenia alone due to the dual burden of both muscle loss and fat gain. The prevalence of SO is progressively increasing as the population ages and the obesity epidemic progresses. Currently, there are no tools for predicting the risk of SO, and this study aimed to construct a well-perfor...

Multidomain Behavioral Change Digital Coaching for Chronic Disease Management in Patients With Type 2 Diabetes: Framework Development and Preliminary Evaluation.

BACKGROUND: Unhealthy lifestyle behaviors have been identified as a major cause of numerous health issues, with a steady global increase in their prevalence. Addressing this challenge requires comprehensive behavioral changes to promote the adoption of a sustainable healthier lifestyle. However, despite the prevalent need, cost-effective and successful digital coaching for health-related behavior ...

Feasibility study of "double-low" scanning protocol combined with artificial intelligence iterative reconstruction algorithm for abdominal computed tomography enhancement in patients with obesity.

OBJECTIVE: To evaluate the efficacy of the "double-low" scanning protocol combined with the artificial intelligence iterative reconstruction (AIIR) al...

Unsupervised learning using EHR and census data to identify distinct subphenotypes of newly diagnosed hypertension patients.

BACKGROUND: Hypertension (HTN) is a complex condition with significant heterogeneity in presentation and treatment response. Identifying distinct subp...

A Pilot Feasibility Study Exploring the Preliminary Effectiveness of an AI-Driven Virtual Human Intervention for General Practitioner Obesity Education and Communication-Skills Training.

BACKGROUND: Rising global obesity rates demand effective weight management strategies from general practitioners (GPs). However, time constraints, tra...

Event-Driven Taxonomy (EDT) Screening: Leveraging Effect-Based Spectral Libraries to Accelerate Semiquantitative Nontarget Analysis of AhR Agonists in Sediment in the Era of Big Data.

Sediments contain complex chemical mixtures. While effect-directed analysis (EDA) combined with nontarget screening (NTS) is promising, its large-scal...

Progress in the application research of cervical cancer screening developed by artificial intelligence in large populations.

Cervical cancer stands out among various cancers due to its potential for prevention and eradication, mainly through vaccination and proactive screeni...

The Impact of Genetic and Acquired Risk Factors on Thromboembolic Events: A Retrospective Study.

This study, involving a cohort of 980 patients with arterial and/or venous events, evaluated the relative importance of genetic and traditional risk f...

Data-driven nutritional assessment of urban food landscapes: insights from Boston, London, and Dubai.

Urban food landscapes significantly influence dietary habits and health outcomes, with disparities in food access contributing to obesity, particularl...

Machine learning models using non-invasive tests & B-mode ultrasound to predict liver-related outcomes in metabolic dysfunction-associated steatotic liver disease.

Advanced metabolic-dysfunction-associated steatotic liver disease (MASLD) fibrosis (F3-4) predicts liver-related outcomes. Serum and elastography-base...

Robust Bi-CBMSegNet framework for advancing breast mass segmentation in mammography with a dual module encoder-decoder approach.

Breast cancer is a prevalent disease affecting millions of women worldwide, and early screening can significantly reduce mortality rates. Mammograms a...

Structural health monitoring and evaluation method for an immersed tunnel based on deep learning.

The health monitoring of the subsea-immersed tunnels is essential for the early detection of anomalies and the assurance of their long-term operationa...

Enhancing diabetes risk prediction through focal active learning and machine learning models.

To improve the effectiveness of diabetes risk prediction, this study proposes a novel method based on focal active learning strategies combined with m...

Cellular senescence in renal ischemia-reperfusion injury.

Acute kidney injury (AKI) affects more than 20% of hospitalized patients and is a significant contributor to morbidity and mortality, primarily due to...

Artificial intelligence and digital twins for the personalised prediction of hypertension risk.

Hypertension is a significant global health challenge, contributing substantially to morbidity and mortality through its association with various card...

Virtual Hydrolysis-Based Screening of Wheat-Derived DPP-IV Inhibitory Peptides: A Mechanistic Analysis Integrating Cell Experiments and Molecular Dynamics Simulations.

Dipeptidyl peptidase-IV (DPP-IV) inhibitors play a critical role in the treatment of diabetes and metabolic diseases. This study combines computationa...

Autonomous screening of infants at high risk for neurodevelopmental impairments using a radar sensor and machine learning.

Neurodevelopmental impairments (NDIs) are significant long-term complications in preterm infants. While early recognition of infants at high risk for ...

A comparative approach of machine learning models to predict attrition in a diabetes management program.

Approximately 11.6% of Americans have diabetes and South Carolina has one of the highest rates of adults with diabetes. Diabetes self-management progr...

Unveiling Quality of Life Factors for the Elderly: A Public Health Nursing Approach Enhanced by Advanced ML and DL Techniques.

Community health nurses can enhance the elderly's quality of life (QoL) through personalized care, lifestyle counselling, and preventive measures. The...

Improving prediction of fragility fractures in postmenopausal women using random forest.

Osteoporosis is a chronic disease characterized by a progressive decline in bone density and quality, leading to increased bone fragility and a higher...