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Automated dairy cattle body condition score using side-view images and deep learning.

Body condition score (BCS) is key to assessing the health, productivity, and energy balance of dairy cows. However, traditional manual methods are time-intensive, dependent on evaluator experience, and prone to subjective biases, limiting large-scale, frequent monitoring. In smallholder settings, where regular BCS monitoring and nutrition advisory support are unavailable, rationing often focuses o...

Clinical governance of artificial intelligence in internal medicine: a literature-informed five-pillar framework for complex care.

Most artificial intelligence (AI) governance frameworks in healthcare address model development, reporting standards, or regulation in broad terms, but do not adequately translate these principles into the operational realities of internal medicine. Although multimorbidity, frailty, polypharmacy, diagnostic uncertainty, incomplete data, and transitions of care are not exclusive to internal medicin...

Evaluating Equity in AI-Supported Functional Assessment: Agreement Between Clinician Judgment and Digital Metrics in Stroke Rehabilitation.

Evaluating agreement between AI-generated functional assessment metrics and clinician judgment in stroke rehabilitation is important for understanding...

Re to "Re: Artificial intelligence in the management of hospital malnutrition: A systematic review Clinical Nutrition ESPEN Volume 70, December 2025, Mancin et al [1].

Machine learning-based prognostic model integrating preoperative HALP score and lactate dehydrogenase for predicting postoperative recurrence of prostate cancer.

OBJECTIVE: Postoperative biochemical recurrence (BCR) of prostate cancer (PCa) remains a major clinical challenge, and traditional risk assessment sys...

Conceptualization, Contexts, and Measurement of Nursing Theoretical Literacy: Protocol for a Scoping Review.

BACKGROUND: Nursing theory and conceptual models are central to nursing as a knowledge discipline, yet theory is often perceived as abstract and diffi...

Data for famine and extreme emergencies: challenges and opportunities.

High-quality data are a pre-requisite for the development of models-whether of famine or food and nutrition-related emergencies. We highlighted challe...

Psychological distress in cancer survivors: a population-based analysis and machine learning-based risk stratification.

PURPOSE: As the number of cancer survivors increases, psychological distress has become an important issue. Using nationally representative data, we e...

Epigenetic-Metabolic interplay in chronic kidney disease mortality: insights from grimage acceleration and transcriptomic profiling.

BACKGROUND: Chronic kidney disease (CKD) is associated with a substantially elevated risk of mortality. Although GrimAge acceleration (GAA) and metabo...

Metabolic Health is Highly Predictive of Chronic Pain Among Non-Obese Adults: Evidence from the NHANES and CHARLS Studies.

OBJECTIVE: To investigate the predictive value of the estimated glucose disposal rate (eGDR) for chronic pain (CP) and to evaluate its consistency as ...

AI-driven personalization of food systems: From precision nutrition to climate-resilient supply chains.

Traditional large-scale production and standardized interventions cannot address the risks due to individual metabolic diversity, climate change, and ...

Machine learning-based preoperative classification of colorectal cancer stage using systemic inflammatory and nutritional biomarkers.

BACKGROUND: Accurate preoperative staging in colorectal cancer (CRC) is critical for determining the appropriate treatment strategy. This study evalua...

Mitigating Misinformation in Health and Nutrition: Assessing Risk, Harm, and Scalable Solutions.

AI and longevity medicine: unlocking predictive and preventive strategies for healthy aging.

Longevity medicine is transforming healthcare by shifting the focus from disease treatment toward the preservation of function, resilience, and health...

High-throughput design of defined microbial consortia for crop protection.

BACKGROUND: Synthetic microbial communities (SynComs) are changing the mechanism of crop protection that ensures global sustainability in agricultural...

Towards precision agriculture for assessing germination rates and density of rice seedling using hierarchical convolutional neural network on drone imagery.

Rice is a significant food that plays a vital part in delivering nutrition to the world's population. Hence, approaches for assessing rice yield have ...

Beyond the digital health tsunami: reaffirming biomedical and health informatics as the scientific foundation of digital healthcare transformation.

Digital health (DH) has emerged as the dominant terminology for technology-enabled healthcare, reshaping institutional discourse, educational programm...

Using Machine Learning Methodology to Identify Predictors of Non-Response to MTSS-B: a Focus on Discipline Problems and Juvenile Justice Involvement.

Multi-tiered systems of support for behavior (MTSS-B) is a widely-used tiered preventive intervention currently used in over 25,000 schools across the...

Targeting metabolic dysregulation in postmenopausal breast cancer: Synergistic effects of nutrition-based interventions and exercise on molecular and cellular pathways.

Postmenopausal females diagnosed with breast cancer who are undergoing aromatase inhibitor (AI) therapy often exhibit metabolic disturbances, which ma...

Can GPT-5 Support Licensing Examination Preparation? Analysis of Accuracy, Reasoning, and Semantic Similarity Across Rehabilitation Disciplines.

In this cross-sectional study of 300 board-style questions across physical therapy, occupational therapy, and speech-language pathology, we evaluated ...