AIMC Topic: Humans

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Predicting risk of early-onset sepsis in low-resource neonatal units using routine healthcare data: development and evaluation of multivariable statistical and machine learning models.

BMJ paediatrics open
BACKGROUND: Neonatal sepsis is a major cause of morbidity and mortality in low-resource settings and accurate, context-appropriate diagnostic methods are urgently needed to improve clinical outcomes.

Transformer-based AI approach to unravel long-term, time-dependent prognostic complexity in patients with advanced NSCLC and PD-L1 ≥50%: insights from the pembrolizumab 5-year global registry.

Journal for immunotherapy of cancer
BACKGROUND: With nearly one-third of patients with advanced non-small cell lung cancer (NSCLC) and PD-L1 Tumor Proportion Score≥50% surviving beyond 5 years following first-line pembrolizumab, long-term outcomes challenge traditional paradigms of can...

Using Large Language Models for Chronic Disease Management Tasks: Scoping Review.

JMIR medical informatics
BACKGROUND: Chronic diseases present significant challenges in health care, requiring effective management to reduce morbidity and mortality. While digital technologies like wearable devices and mobile applications have been widely adopted, large lan...

Preferences, Perceptions, and Use of Online Nutrition Content Among Young Australian Adults: Qualitative Study.

Journal of medical Internet research
BACKGROUND: Nutrition misinformation is pervasive on frequently accessed online sources such as social media platforms and websites. Young adults are at a high risk of viewing or engaging with this content due to their high internet and social media ...

Synthetic Tabular Data Generation Under Horizontal Federated Learning Environments in Acute Myeloid Leukemia: Case-Based Simulation Study.

JMIR medical informatics
BACKGROUND: Data scarcity and dispersion pose significant obstacles in biomedical research, particularly when addressing rare diseases. In such scenarios, synthetic data generation (SDG) has emerged as a promising path to mitigate the first issue. Co...

Comparative study of technical and patient-related question answering quality of DeepSeek-R1 and ChatGPT-4o in the field of oral and maxillofacial surgery.

Oral and maxillofacial surgery
BACKGROUND: Artificial Intelligence (AI) technologies demonstrate potential as supplementary tools in healthcare, particularly in surgery, where they assist with preoperative planning, intraoperative decisions, and postoperative monitoring. In oral a...

Metaheuristic-optimized swin transformer with SHAP explainability for keratoconus classification from corneal topography maps.

International ophthalmology
Keratoconus (KCN) is an uncommon corneal disorder where the central cornea undergoes advanced thinning and causes non-uniform astigmatism. This results in metamorphopsia and potential vision loss if it is left untreated. Early detection of KCN is maj...

Machine learning for endoscopic third ventriculostomy success prediction-a systematic review and meta-analysis.

Child's nervous system : ChNS : official journal of the International Society for Pediatric Neurosurgery
BACKGROUND: Endoscopic third ventriculostomy (ETV) is a common treatment for pediatric obstructive hydrocephalus, but predicting its success remains challenging. Traditional predictive tools, such as the Endoscopic Third Ventriculostomy Success Score...

Unravelling mutation patterns in Extended-Spectrum β-Lactamases for precision drug design against AMR in Enterobacteriaceae.

Molecular genetics and genomics : MGG
Antimicrobial resistance (AMR) presents a critical global challenge, causing over 1.27 million deaths annually, with projections reaching 10 million by 2050. Among the most concerning contributors are Enterobacteriaceae, particularly Escherichia coli...

Alzheimer's disease classification using a hybrid deep learning approach with multi-layer U-net segmentation and XAI driven analysis.

PloS one
Alzheimer's disease (AD) is a neurodegenerative illness causing a significant decrease in cognitive function, and early, accurate diagnosis is of great therapeutic and diagnostic value. Currently, there is promising potential for applying various typ...