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Multiple polygenic score approach in colorectal cancer risk prediction.

Scientific reports
Recent studies have demonstrated that for various diseases, incorporating polygenic risk scores (PRSs) for other traits and diseases into the PRS-based risk prediction model may improve predictive performance - known as Multiple Polygenic Score (MPS)...

Diagnostic assistance method for RR-TB/MDR-TB patients under treatment based on CNN-LSTM.

Scientific reports
The rapid development of deep learning has promoted its application in disease diagnosis, treatment, and prognosis prediction. Medical imaging plays a crucial role in the management of rifampicin-resistant tuberculosis/multidrug-resistant tuberculosi...

Prompt-dependent performance of multimodal AI model in oral diagnosis: a comprehensive analysis of accuracy, narrative quality, calibration, and latency versus human experts.

Scientific reports
Prompt design is a critical yet underexplored factor influencing the diagnostic performance of large language models (LLMs). Gemini Pro 2.5 shows promise in multimodal reasoning, but no prior study has systematically compared prompt structures in ora...

Evaluation of normalized T1 signal intensity obtained using an automated segmentation model in lower leg MRI as a potential imaging biomarker in Charcot-Marie-Tooth disease type 1 A.

Scientific reports
We evaluated the potential utility of imaging parameters derived by normalizing muscle signal intensity on T1-weighted lower leg MRIs in Charcot-Marie-Tooth disease type 1 A (CMT1A) patients, using a deep learning-based automated muscle segmentation ...

A framework for AI ethics literacy: development, validation, and its role in fostering students' self-rated learning competence.

Scientific reports
This study investigates the relationship between AI ethics literacy and students' self-rated learning competence using AI by developing a comprehensive framework of AI ethics literacy comprising knowledge, attitude, and competence dimensions. Data we...

Dual-center study on AI-driven multi-label deep learning for X-ray screening of knee abnormalities.

Scientific reports
Knee abnormalities, such as meniscus tears and ligament injuries, are common in clinical practice and pose significant diagnostic challenges. While traditional imaging techniques-X-ray, Computed Tomography (CT) scan, and Magnetic Resonance Imaging (M...

Transparent AI-driven personalized risk prediction system for acute kidney injury after total hip arthroplasty.

Scientific reports
Acute kidney injury is a common and severe complication following total hip arthroplasty, particularly in elderly or high-risk patients with chronic conditions, significantly increasing morbidity and mortality rates. Traditional prediction methods of...

Research on the impact of explosive martial arts training on emotion regulation and attention based on questionnaire data.

Scientific reports
Understanding the psychological effects of martial arts training requires models that can bridge the gap between observable physical behavior and subjective cognitive states. This study proposes a deep learning framework that explicitly uses question...

Multimodal Multitask Learning for Predicting Depression Severity and Suicide Risk Using Pretrained Audio and Text Embeddings: Methodology Development and Application.

JMIR medical informatics
BACKGROUND: Depression is a critical psychological disorder necessitating urgent assessment and treatment, given its strong association with increased suicide risk (SR). Effective management hinges on promptly identifying individuals with high depres...

Machine learning-enhanced direct mass spectrometry analysis of non-volatile breath metabolites for rapid and accurate lung cancer screening.

Analytical methods : advancing methods and applications
Breath analysis by direct mass spectrometry faces significant challenges due to the inherent complexities in sample collection, low analyte concentrations, and accurate compound identification. While current breath analysis primarily focuses on volat...