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AlzFormer: Multi-modal framework for Alzheimer's classification using MRI and graph-embedded demographics guided by adaptive attention gating.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 20, 2025
Alzheimer's disease (AD) is the most common neurodegenerative progressive disorder and the fifth-leading cause of death in older people. The detection of AD is a very challenging task for clinicians and radiologists due to the complex nature of this ...
AI-assisted 3D versus conventional 2D preoperative planning in total hip arthroplasty for Crowe type II-IV high hip dislocation: a two-year retrospective study.
Journal of orthopaedic surgery and research
Aug 20, 2025
BACKGROUND: With the growing complexity of total hip arthroplasty (THA) for high hip dislocation (HHD), artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning has emerged as a promising tool to enhance surgical accuracy. T...
Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.
BMC cancer
Aug 20, 2025
BACKGROUND: Renal cell carcinoma (RCC) is a prevalent malignancy with highly variable outcomes. MicroRNA-15a (miR-15a) has emerged as a promising prognostic biomarker in RCC, linked to angiogenesis, apoptosis, and proliferation. Radiogenomics integra...
Automatic detection of cognitive events using machine learning and understanding models' interpretations of human cognition.
Scientific reports
Aug 20, 2025
The pupillary response is a valuable indicator of cognitive workload, capturing fluctuations in attention and arousal governed by the autonomic nervous system. Cognitive events, defined as the initiation of mental processes, are closely linked to cog...
A smart secure virtual reality immersive application for alzheimer's and dementia patients.
Scientific reports
Aug 20, 2025
Alzheimer's disease (AD) poses significant challenges for the elderly, leading to cognitive decline, social isolation, and lower quality of life. Current interventions often require cumbersome wearable devices e.g. the camera-based monitoring that ma...
A development of machine learning models to preoperatively predict insufficient clinical improvement after total knee arthroplasty.
Journal of orthopaedic surgery and research
Aug 20, 2025
BACKGROUND: Identifying patients unlikely to achieve meaningful improvement following total knee arthroplasty (TKA) supports more effective shared decision-making (SDM). This study aimed to develop and validate machine learning (ML) models that preop...
Stacking ensemble learning models diagnose pulmonary infections using host transcriptome data from metatranscriptomics.
Scientific reports
Aug 20, 2025
The prompt diagnosis of pulmonary infections with unknown etiology in patients in severe condition remains a challenge due to the lack of rapid and effective diagnostic methods. While metatranscriptomic sequencing offers a powerful approach, its clin...
Determination of miRNA in tear extracellular vesicles significantly associated with treatment-requiring retinopathy of prematurity: a pilot study.
Scientific reports
Aug 20, 2025
Retinopathy of prematurity (ROP) develops in some premature infants and may be characterized by permanent severe retinal damage necessitating early detection and prompt treatment. The purpose of this study was to investigate whether specific miRNAs i...
Unsupervised clustering of biochemical markers reveals health profiles associated with function and survival in active aging.
Scientific reports
Aug 20, 2025
This study explores the relationships between biochemical phenotypes identified using machine learning, and key health outcomes, including body composition, physical function, and mortality risk. Data were collected from 536 physically active Spanish...
A study on the effectiveness of machine learning models for hepatitis prediction.
Scientific reports
Aug 20, 2025
Hepatitis continues to be a major global health challenge, leading to high morbidity and mortality rates. Despite advances in diagnosis and treatment, early prediction of hepatitis outcomes remains an essential area for improvement. This study seeks ...
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