Public Health & Policy

Shaping the future of postoperative recurrence in Crohn's disease: personalised approaches with AI-enabled imaging and multi-omics.

Postoperative recurrence (POR) is a major challenge in the long-term management of Crohn's disease (CD), affecting up to 70% of patients within the first year after surgical resection. The multifactorial pathogenesis of POR complicates prevention, while evolving surgical techniques and different anastomotic configurations further hinder accurate prediction and monitoring.Current surveillance strat...

Diagnostic stewardship monitoring systems: institutional and system-level approaches.

Diagnostic stewardship-performing the right test for the right patient at the right time-improves diagnostic accuracy and reduces healthcare resource waste. Various stewardship interventions have been introduced, yet their effects dissipate without systematic, sustained monitoring. One-time education and isolated system controls consistently show effect attenuation over time, and inappropriate ord...

Who Is Getting the Help They Need? An AI-Driven Study of Intersectional Disparities in Mental Health Service Utilization Among Young Adults with Suicidal Ideation.

Despite the critical role of mental health services in suicide prevention, disparities in service utilization persist across various individual and so...

Artificial Intelligence in Physical, Occupational and Neuro-Rehabilitation: Clinical Effectiveness, Prognostic Performance, and Pre-Implementation Feasibility - A Systematic Review.

BACKGROUND: Global rehabilitation needs far exceed capacity, and artificial intelligence (AI) is proposed to extend access, personalise therapy, and s...

An intelligent context-aware facial emotion recognition system for hearing-impaired individuals using large language models and neural network-based feature fusion.

Facial emotion recognition (FER) plays a vital role in understanding human behavior and communications, with applications in human-computer interactio...

Using natural language processing to assess proxy measures of therapeutic alliance across suicide risk tiers.

Therapeutic alliance is a core predictor of psychotherapeutic outcome, in general, and suicide prevention, specifically. Although clinical literature ...

Proceedings from the 2025 Midwest Pediatric Device Consortium showcase featuring software as a medical device.

On July 9, 2025, the Midwest Pediatric Device Consortium hosted its second showcase at the MidTown Collaboration Center in Cleveland, OH. This meeting...

Understanding antimicrobial resistance dynamics of non-typhoidal Salmonella in chickens and ducks - a prospective study from West Bengal, India.

This study investigated the antimicrobial resistance (AMR) profile of Salmonella enterica (n = 446) of poultry origin (n = 1020) collected from West B...

An exploratory study of multi-channel CNN for early detection of lung cancer from longitudinal healthcare records.

Lung cancer remains the leading cause of cancer-related mortality worldwide, with poor survival rates due to late-stage detection. Current low-dose co...

Artificial intelligence model predicts malignant transformation of oral leukoplakia and optimizes interventions.

PURPOSE: Oral leukoplakia (OL), the most common oral potentially malignant disorder (OPMD), poses a significant risk for transformation to oral squamo...

Development of a machine learning-based prognostic prediction model and a web-based tool for pediatric hepatoblastoma: a Surveillance, Epidemiology, and End Results (SEER) database study.

BACKGROUND: Prognostic evaluation of pediatric hepatoblastoma (HB) remains challenging due to the low accuracy of traditional risk stratification mode...

Occupational and socioeconomic predictors of myocardial infarction and coronary heart disease: a machine learning analysis.

BACKGROUND: Cardiovascular disease (CVD) remains a leading cause of morbidity and mortality worldwide. Although traditional cardiovascular risk models...

Breaking the culture habit: Complementing culture-based veterinary diagnostics with metagenomic data -A case study of feline and canine skin infections.

BACKGROUND: Skin infections have been described as the primary cause for veterinary small animal practice visits, frequently requiring topical and sys...

Machine learning and multi-dimensional transcriptomics reveal the key molecular network of benzo(a)pyrene/NNK in promoting laryngeal cancer and develop prognostic models.

Benzo(a)pyrene (BaP) and 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK), as typical environmental carcinogens, are widely present in tobacco smo...

Establishing a Sustainable Artificial Intelligence Infrastructure for Health Care Systems Part II: Consideration of Key Regulatory and Bioethical Barriers to Implementation.

Establishing an artificial intelligence (AI) infrastructure is contingent upon processes being conducted within structured regulatory frameworks that ...

A Guide to Constructing Indigenous Statistical Spaces for Prevention Science Research.

Artificial intelligence (AI)-powered computational methods, such as machine learning and natural language processing, are increasingly applied in deat...

Deep learning models for acute kidney injury prediction: multi-center external validation and evaluation under simulated continuous monitoring conditions.

Acute kidney injury (AKI) is a common hospital complication with substantial morbidity and mortality. Deep learning models for AKI prediction show str...

Spatial concordance metrics and related risk factors of brain-peripheral barrier axes: unveiling distinct concordance patterns for mental and neurological axes.

Numerous studies have documented bidirectional interactions between the central nervous system and barrier organs (skin, gut, and lung). While genome-...

The detectability paradox: bilingual medical report generation with open-weight models and the limits of human oversight.

OBJECTIVES: The automation of medical report generation using large language models (LLMs) could significantly reduce physicians' documentation burden...

Research on interpretable machine learning modeling and spatial prediction of cross-landform landslide disaster mechanism: A case study of Shaanxi Province.

The differential understanding of the landslidetriggering mechanisms across various geomorphic units is vital for enhancing regional disaster preventi...