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Development of a Knowledge Map for Managing Symptoms of Graft-Versus-Host Disease in Patients Undergoing Hematopoietic Stem Cell Transplantation.

BACKGROUND: Graft-versus-host disease (GVHD) remains a critical complication affecting patients undergoing hematopoietic stem cell transplantation (HSCT), with multifaceted symptoms requiring systematic management. Current clinical practices lack structured tools to guide nurses in addressing GVHD-related symptoms across diverse organ systems. This review aims to synthesize evidence on GVHD sympto...

Predictive, Preventive and Personalized Medicine Approaches in Periodontitis: Emerging Technologies from Biomarkers to Artificial Intelligence-Driven Integrated Strategies.

RATIONALE AND PURPOSE: Periodontitis is a chronic multifactorial inflammatory disease linked to systemic conditions including cardiovascular disease and diabetes, underscoring the need for a holistic diagnostic approach. Current diagnostics rely on clinical probing and radiography, which detect accumulated damage rather than early biological activity or individual progression risk. This reactive p...

Comparative machine learning modeling of resting energy expenditure estimation in mechanically ventilated children after cardiac surgery.

OBJECTIVE: Nutrition status is vital for children's recovery following cardiac surgery, with substantial inter-individual variability in metabolic dem...

Membrane Protein Design: From Reprogramming Functions to AI-Guided De Novo Design Approaches.

Computational membrane protein design has rapidly evolved from early physics-based modeling into a mature discipline powered by high-throughput experi...

Evaluation of Large Language Models for Mapping Dietary Data to Food Databases.

BACKGROUND: New food databases increasingly provide biochemical information not yet captured in standard food composition databases (FCDs). To enable ...

Response to Letter to the Editor: Advancing Artificial Intelligence in Renal Nutrition: The Need for Culturally Adaptive, Equity-Focused Frameworks Beyond Retrieval-Augmented Generation.

Advancing Artificial Intelligence in Renal Nutrition: The Need for Culturally Adaptive, Equity-Focused Frameworks Beyond Retrieval-Augmented Generation.

Clinically actionable classification tool for childhood and adult atopic dermatitis via explainable AI: a retrospective cross-sectional study optimizing diagnostic accuracy.

BACKGROUND: Despite the critical role of early identification in managing atopic dermatitis (AD), current studies are limited by the absence of adult-...

A machine learning AI model for predicting condylar erosion in patients with temporomandibular joint disorders and analyzing factors contributing to prediction.

OBJECTIVES: In temporomandibular joint osteoarthritis, condylar erosion is considered a sign of disease progression. Few studies have clarified the ex...

Automated measurement of left ventricular ejection time via contactless suprasternal notch laser vibrometry.

Left Ventricular Ejection Time (LVET) is a sensitive indicator of early cardiac dysfunction, yet its routine use in first-line population screening is...

Mapping the digital determinants of health: a machine learning analysis of YouTube narratives on child undernutrition in Pakistan.

BACKGROUND: The role of social media in in shaping the public perception of health crises is growing, yet we know little about the contribution of pla...

Analytic Misjudgment of Drug Safety Evidence and Causality: From the Prosecutor's Fallacy and Simpson's Paradox to Artificial Intelligence.

Drug safety assessment, particularly in the post-marketing setting, is especially vulnerable to analytic misjudgment because it relies on heterogeneou...

Comparison of ChatGPT and dietitians in formulating diet plans and recommendations for patients with cardiometabolic diseases.

BACKGROUND: Artificial Intelligence (AI) is transforming personalized medicine, yet its efficacy constitutes a dynamic factor in the field of health a...

Retraction: Enhanced heart disease diagnosis and management: A multi-phase framework leveraging deep learning and personalized nutrition.

Modelling the impact of dietary diversity on child nutrition in Pakistan: a machine learning analysis with Shapley Additive exPlanations and Boruta interpretability.

BACKGROUND: Pakistan faces a serious challenge in malnutrition, as its core nutrition indicators and minimum dietary diversity remain below the recomm...

Smart feeding: the role of artificial intelligence and integrated nutrition platforms in the ICU.

PURPOSE OF REVIEW: Tremendous improvement in the use of artificial intelligence has opened new opportunities to analyze the data obtained from electro...

Lessons From Drug Discovery for Cryoprotective Agent Design: An AI-Oriented Perspective.

Cryopreservation is the storage of biological materials like cells, tissues, or even organs at cryogenic temperatures. This technology is a key enable...

Evaluating a Multitask AI Model versus Humans for Portion Size Estimation.

BACKGROUND: Accurate dietary assessment is essential for precision nutrition and nutrition surveillance. Portion size estimation remains challenging, ...

Reconfiguring biofortification strategies to transform food systems and address micronutrient deficiency of the 21st century.

Despite achieving substantial progress in caloric food security, micronutrient deficiencies remain a major global health challenge, highlighting a per...

Cross-population validation of the TyG-ABSI index as a novel predictor for chronic obstructive pulmonary disease: an integrated analysis using logistic regression and explainable machine learning.

BACKGROUND: Chronic Obstructive Pulmonary Disease (COPD) is increasingly recognized as a systemic inflammatory condition closely linked to metabolic d...