Prevention

Deep Learning Segmentation of Pectoralis Muscle Volume at CT and Comparison with Pectoralis Muscle Area in COPD.

Purpose To develop a deep learning model for segmenting pectoralis muscle volume (PMV) at CT and evaluate the reproducibility, group differences, and associations of pectoralis muscle area (PMA) and PMV with chronic obstructive pulmonary disease (COPD)-related outcomes. Materials and Methods This study was a secondary analysis of the prospective Canadian Cohort Obstructive Lung Disease study (CanC...

Designing a Carbohydrate Counting App for Young Adults With Type 1 Diabetes: Usability Testing Interview Study.

BACKGROUND: Carbohydrate counting (CC) assists people with type 1 diabetes (T1D) adjust mealtime insulin doses; however, it is often burdensome. Mobile apps can simplify this process by automating carbohydrate estimation and insulin calculations, yet no comprehensive solution currently combines photo-based carbohydrate recognition with an integrated bolus calculator. OBJECTIVE: This study aimed to...

[A smart way back to work-The impact of digital rehabilitation on return-to-work outcomes after hand injuries].

BACKGROUND: Restoring the ability to work after hand injuries is a central goal of rehabilitation. Digital therapy applications are increasingly findi...

Machine Learning-driven Prioritisation of Lipoprotein(a) Testing: Model Development and Validation.

AIMS: Elevated lipoprotein(a) [Lp(a)] is a common risk factor for cardiovascular disease (CVD) affecting ∼1.4 billion people globally, with novel trea...

Cardioprotection in oncology: Mechanisms, risks and therapeutic strategies.

Objectives of this review is to conduct an analysis of current data of cardiotoxicity of anticancer drugs and radiation therapy, methods of cardiovasc...

Evaluating ChatGPT's advice and recommendations regarding exercise for people with inclusion body myositis.

The use of Large Language Models for exercise prescription in the general population has been shown to be safe and effective but not comprehensive com...

A Chat With Hippocrates: The Oath in the Age of AI.

In 2005, Weill Cornell Medicine revised the Hippocratic Oath. Since then, this revised oath has been administered to graduating medical students and b...

Deep learning-based infrared thermography reveals reproducible uniform and individual thermoregulatory responses during running.

Infrared thermography (IRT) has recently gained attention in the field of exercise physiology, due to its ability to monitor thermoregulatory and card...

Circulatory dietary and gut-derived metabolites predict early cognitive decline.

INTRODUCTION: A key component of disease prevention is the identification of at-risk individuals. Microbial dysbiosis in the early stages of cognitive...

DoTT-ML: Condition-aware detection of transcriptional readthrough from RNA-seq with optional ML-based prioritization.

Disruption of transcription termination (DoTT) occurs when RNA polymerase II reads past a gene's normal 3' end, generating downstream "readthrough" RN...

Maintenance factors for eating disorder symptoms based on ecological momentary assessment studies: A systematic review.

Several prominent theories of eating disorders maintenance exist, with most corresponding to evidence-based treatments. Ecological momentary assessmen...

The Evolving Role of the Qualified Person in an AI-Driven Pharma Compliance Landscape.

The role of the Qualified Person (QP) in pharmaceutical compliance is undergoing a fundamental transformation driven by the integration of artificial ...

Development and validation of a tool for detecting misinformation risk in diet, nutrition, and health content (Diet-MisRAT).

Diet-microbiota-kidney axis reprogramming: mechanistic insights into microbial metabolite-driven precision nutrition for chronic kidney disease.

Medical nutrition therapy serves as the cornerstone in the management of chronic kidney disease (CKD). While conventional approaches emphasize macronu...

Development and validation of a prediction model for long-term cognitive frailty risk in stroke patients based on CHARLS data.

BACKGROUND: This study aimed to develop and validate machine learning (ML) models for predicting the risk of cognitive frailty in community-dwelling e...

Priority questions for the next decade of blue carbon science.

Blue carbon ecosystems, classically defined as mangroves, tidal marshes and seagrasses, but increasingly expanded to include ecosystems such as tidal ...

Differential Factors Associated With the Presence of Persistent Symptoms in Individuals Diagnosed With Long COVID: Protocol for a Longitudinal Matched Case-Control Study.

BACKGROUND: Long COVID (postacute sequelae of SARS-CoV-2 infection) is a heterogeneous condition with persistent multisystem symptoms and substantial ...

Improving the composition of donor milk using machine learning and optimisation techniques.

BACKGROUND AND AIMS: The macronutrient composition of donor human milk (DHM) can vary substantially due to several factors such as maternal age, diet,...

Ameliorative effect of Rhus verniciflua Stokes on high-fat diet-induced obesity and advanced analysis with machine learning and deep learning-based network pharmacology.

AIMS: Obesity and metabolic dysfunction-associated steatotic liver disease (MASLD) arise from impaired redox and energy homeostasis, yet current thera...

Molecular mechanisms of exercise-induced improvements in Alzheimer's disease: a focus on lipid homeostasis.

Alzheimer's disease (AD) is the most prevalent type of dementia, and its pathophysiological mechanisms involve multiple factors, including genomic fac...