Prevention

Truth, tone, and trust: integrating an AI exercise to foster responsible science communication in a graduate biomedical science course.

As generative AI becomes a standard fixture in graduate education, the pedagogical challenge has shifted from detection to integration. This article describes a curriculum intervention developed for Anatomy of Scientific Error, a graduate-level course on scientific error analysis in interdisciplinary research practice and communication at the Johns Hopkins Bloomberg School of Public Health. To inf...

Interpretable machine-learning survival prediction of breast cancer prognosis from lifestyle factors: evidence from UK biobank.

BACKGROUND: Understanding how lifestyle habits influence breast cancer survival is crucial for improving long-term outcomes and guiding individualized care. The purpose of this study is to comprehensively understand how dietary habits, exercise frequency, sleep quality and the frequency of tobacco and alcohol use affect the survival of breast cancer patients by analyzing the synergistic effects of...

Anticipating the Impact of AI on Diet and Exercise Apps: Foresight Study Applying the Futures Wheel.

AI has entered the wellness space through apps and wearables. These technologies can collect real-time data, infer lifestyle patterns, and dynamically...

Effectiveness of an AI-augmented teacher feedback model in improving medical students' clinical documentation skills: a retrospective cohort study.

BACKGROUND: Clinical documentation is central to evaluating medical students' clinical competence. However, traditional teacher feedback is often inef...

Multi-component exercise intervention methods for intelligent assisted diagnosis of sarcopenia in the elderly based on deep learning.

Population aging has made sarcopenia a major public health challenge in geriatric medicine. Current clinical diagnosis relies on large specialized equ...

Thinking about the Impact of Artificial Intelligence on U.S. Health Care Costs and Spending Growth.

This article critically examines the potential impacts of artificial intelligence (AI) on prices, total spending, and the rate of spending growth in t...

Serum 1H NMR-Based Untargeted Metabolomics for Noninvasive Early Detection of Breast Cancer.

Breast cancer (BC) is the most common malignancy among women, and late-stage presentation remains common in Asia, highlighting the need for affordable...

Integrating skeleton based representations for robust yoga pose classification using deep learning models.

Yoga is a popular form of exercise worldwide due to its spiritual and physical health benefits, but incorrect postures can lead to injuries. Automated...

Wearable fatigue detection system for wheelchair propulsion: Identifying key muscles via an attention-based LSTM Model.

Fatigue induces adverse short- and long-term health risks in wheelchair users. This study aimed to develop a machine learning approach to predict fati...

Prediction of Exercise Intolerance in the Recovery Period After Cardiovascular Surgery Using Perioperative Clinical Parameters.

OBJECTIVE: To develop and validate a machine learning model for predicting reduced exercise capacity at 3 months postoperatively using clinical parame...

Cartilage oligomeric matrix protein inhibits CKD-associated vascular calcification by suppressing PANoptosis in VSMCs via the AT1R/β-arrestin-2 axis.

Vascular calcification (VC), a common complication of chronic kidney disease (CKD), substantially contributes to cardiovascular morbidity. Although di...

Unsupervised machine learning derived bone phenotypes exhibit differential biomarker responses following acute ballistic loaded exercise.

Resistance exercise can stimulate new bone formation and result in changes to circulating markers of bone metabolism, but the relationship between the...

Technology-enabled telerehabilitation for Parkinson's disease: a scoping review of digital rehabilitation systems, delivery architectures, and implementation challenges.

INTRODUCTION: Digital technologies are increasingly integrated into neurorehabilitation programs for Parkinson's Disease (PD), enabling remote deliver...

Quality and nutritional accuracy of mHealth nutrition apps in Türkiye: A validation study using food records.

Background: Mobile health (mHealth) applications are increasingly used for dietary assessment and self-monitoring, yet their validity and comprehensiv...

Revolutionizing Nutrition: AI-Driven Health Solutions and Personalized Diets.

Artificial Intelligence (AI) is revolutionizing health and nutrition, significantly advancing personalized dietary management and health optimization....

Assessing the association of type 2 diabetes with skin health status: a study of the Northern Finland Birth Cohort 1966.

OBJECTIVES: There is evidence to suggest that alterations in skin health often co-occur with type 2 diabetes (T2D). However, the underlying mechanisms...

Evaluating AI in postoperative rehabilitation of axillary web syndrome after breast cancer surgery: ChatGPT vs DeepSeek.

OBJECTIVE: To systematically compare two generative artificial intelligence (AI) models, ChatGPT and DeepSeek in the rehabilitation management for axi...

Large language model-driven Socratic questioning for endodontic case analysis: A randomised controlled trial.

OBJECTIVE: Endodontic education requires structured clinical reasoning practise, but resource constraints often limit the delivery of case-based instr...

Personalized antiplatelet therapy: are we ready for a precision medicine approach.

Dual antiplatelet therapy (DAPT), combining aspirin with a P2Y12 inhibitor, remains central to secondary prevention after acute coronary syndrome and ...

Dietary patterns and Alzheimer's disease: East-west perspectives and future intervention strategies.

Among various modifiable risk factors, dietary patterns (DPs), as a holistic lifestyle intervention, have become a focus of current research due to th...