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Suicide risk prediction for Korean adolescents based on machine learning.

Scientific reports
Traditional clinical risk assessment tools proved inadequate for reliably identifying individuals at high risk for suicidal behavior. As a result, machine learning (ML) techniques have become progressively incorporated into psychiatric care. This stu...

AI in Home Care-Evaluation of Large Language Models for Future Training of Informal Caregivers: Observational Comparative Case Study.

Journal of medical Internet research
BACKGROUND: The aging population presents an accomplishment for society but also poses significant challenges for governments, health care systems, and caregivers. Elevated rates of functional limitations among older adults, primarily caused by chron...

Explainable Machine Learning Model for Predicting Persistent Sepsis-Associated Acute Kidney Injury: Development and Validation Study.

Journal of medical Internet research
BACKGROUND: Persistent sepsis-associated acute kidney injury (SA-AKI) shows poor clinical outcomes and remains a therapeutic challenge for clinicians. Early identification and prediction of persistent SA-AKI are crucial.

Intraocular lens calculation formula developed using artificial intelligence for ultrasonic biometry.

Arquivos brasileiros de oftalmologia
PURPOSE: We developed an artificial intelligence program for calculating intraocular lenses and analyzed its accuracy rate via ultrasonic biometry. This endeavor is aimed at enhancing precision and efficacy in the selection of intraocular lenses, par...

Artificial intelligence-based assessment of imaging biomarkers in epiretinal membrane surgery.

European journal of ophthalmology
PurposeThis study investigated the applicability of a validated AI-algorithm for analyzing different retinal biomarkers in eyes affected by epiretinal membranes (ERMs) before and after surgery.MethodsA retrospective study included 40 patients surgica...

A novel diagnosis method utilizing MDBO-SVM and imaging genetics for Alzheimer's disease.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Alzheimer's disease (AD) is the most common neurodegenerative disorder, yet its underlying mechanisms remain elusive. Early and accurate diagnosis is crucial for timely intervention and disease management. In this paper, a multi-strategy improved dun...

Biological age prediction in schizophrenia using brain MRI, gut microbiome and blood data.

Brain research bulletin
The study of biological age prediction using various biological data has been widely explored. However, single biological data may offer limited insights into the pathological process of aging and diseases. Here we evaluated the performance of machin...

Predictive modeling of response to repetitive transcranial magnetic stimulation in treatment-resistant depression.

Translational psychiatry
Identifying predictors of treatment response to repetitive transcranial magnetic stimulation (rTMS) remain elusive in treatment-resistant depression (TRD). Leveraging electronic medical records (EMR), this retrospective cohort study applied supervise...

The use of a convolutional neural network to automate radiologic scoring of computed tomography of paranasal sinuses.

Biomedical engineering online
BACKGROUND: Chronic rhinosinusitis (CRS) is diagnosed with symptoms and objective endoscopy or computed tomography (CT). The Lund-Mackay score (LMS) is often used to determine the radiologic severity of CRS and make clinical decisions. This proof-of-...

Predicting 30-day survival after in-hospital cardiac arrest: a nationwide cohort study using machine learning and SHAP analysis.

BMJ open
OBJECTIVE: In-hospital cardiac arrest (IHCA) presents a critical challenge with low survival rates and limited prediction tools. Despite advances in resuscitation, predicting 30-day survival remains difficult, and current methods lack interpretabilit...