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Identification of novel vertebral development factors through UK Biobank candidate gene search and body imaging analysis.

Communications biology
Numerical variations and transitional anatomy in the human vertebral column represent a significant yet understudied aspect of skeletal development with potential effects on multiple physiological systems. Utilising UK Biobank data, we integrated gen...

Performance of Retrieval-Augmented Generation Large Language Models in Guideline-Concordant Prostate-Specific Antigen Testing: Comparative Study With Junior Clinicians.

Journal of medical Internet research
BACKGROUND: Prostate-specific antigen (PSA) testing remains the cornerstone of early prostate cancer detection. Society guidelines for prostate cancer screening via PSA testing serve to standardize patient care and are often used by trainees, junior ...

Using ChatGPT-4 for Lay Summarization in Prostate Cancer Research to Advance Patient-Centered Communication: Large-Scale Generative AI Performance Evaluation.

Journal of medical Internet research
BACKGROUND: The increasing volume and complexity of biomedical literature pose challenges for making scientific knowledge accessible to lay audiences. Lay summaries, now widely encouraged or required by journals, aim to bridge this gap by promoting h...

Biological Age Prediction of the Cerebellar Vermis in the Human Lifespan.

Cerebellum (London, England)
The cerebellar vermis undergoes diverse structural changes with aging, yet region-specific aging patterns remain underexplored. Using Brain Structure Age (BSA), a deep learning biomarker from structural magnetic resonance imaging (MRI), we aimed to: ...

Reconstructing impaired language using generative AI for people with aphasia.

Scientific reports
In an era of Generative Artificial Intelligence (AI), it may be possible to capitalise on AI's generative capabilities to assist people in compensating for their impaired language. Large Language Models (LLMs) have emerged as a recent breakthrough, r...

Construction and validation of a risk prediction model for complications in patients with acute leukemia based on machine learning.

Scientific reports
Early-phase severe complications remain a major cause of morbidity and mortality during induction chemotherapy for acute leukaemia. Existing risk scores capture only limited prognostic variance and are rarely well-calibrated for clinical decision sup...

A hybrid EMG-EEG interface for robust intention detection and fatigue-adaptive control of an elbow rehabilitation robot.

Scientific reports
Accurate detection of user intention is a critical requirement for intelligent control systems in upper-limb rehabilitation robots. However, electromyography (EMG)-based recognition can degrade significantly under muscle fatigue. To address this limi...

Compact machine learning model for perioperative stroke prediction prior to surgery: A retrospective cohort study.

Scientific reports
Perioperative stroke significantly impacts postoperative outcomes. Current risk stratification methods for perioperative stroke prediction lack accuracy and practicality. We aimed to develop a machine learning (ML) model that improves both accuracy a...

An intelligent taekwondo coaching system based on augmented reality technology with real-time feedback mechanisms.

Scientific reports
Traditional taekwondo training methods face limitations in providing objective, real-time feedback for technique improvement, relying primarily on subjective instructor observations that may lack precision and consistency. This research presents an i...

Robust missing data reconstruction in schizophrenia using tracking-removed autoencoder with fuzzy confidence integration.

Scientific reports
Neural network models for outcome prediction play a pivotal role in neurological disease research, particularly for baseline risk assessment. Schizophrenia, a complex and relatively rare neuropsychiatric disorder, presents significant diagnostic chal...