AIMC Topic: Adult

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Development of a Machine Learning-Powered Optimized Lung Allocation System for Maximum Benefits in Lung Transplantation: A Korean National Data.

Journal of Korean medical science
BACKGROUND: An ideal lung allocation system should reduce waiting list deaths, improve transplant survival, and ensure equitable organ allocation. This study aimed to develop a novel lung allocation score (LAS) system, the MaxBenefit LAS, to maximize...

How adaptive social robots influence cognitive, emotional, and self-regulated learning.

Scientific reports
As educational environments become more diverse, adaptive technologies like social robots hold promise for providing individual support to learners. This study investigated the role of adaptive teaching of a robot on students' learning outcomes, emot...

Validation of a machine learning model for indirect screening of suicidal ideation in the general population.

Scientific reports
Suicide is among the leading causes of death worldwide and a concerning public health problem, accounting for over 700,000 registered deaths worldwide. However, suicide deaths are preventable with timely and evidence-based interventions, which are of...

An assessment of machine learning methods to quantify blood lactate from neutrophils phagocytic activity.

Scientific reports
Phagocytosis is a critical component of innate immunity that helps the body defend itself against infection, foreign particles, and cellular debris. Investigating and quantifying phagocytosis can help understand how the immune system identifies forei...

The Feasibility of Large Language Models in Verbal Comprehension Assessment: Mixed Methods Feasibility Study.

JMIR formative research
BACKGROUND: Cognitive assessment is an important component of applied psychology, but limited access and high costs make these evaluations challenging.

Identifying Patient-Reported Care Experiences in Free-Text Survey Comments: Topic Modeling Study.

JMIR medical informatics
BACKGROUND: Patient-reported experience surveys allow administrators, clinicians, and researchers to quantify and improve health care by receiving feedback directly from patients. Existing research has focused primarily on quantitative analysis of su...

Predictive modeling with linear machine learning can estimate glioblastoma survival in months based solely on MGMT-methylation status, age and sex.

Acta neurochirurgica
PURPOSE: Machine Learning (ML) has become an essential tool for analyzing biomedical data, facilitating the prediction of treatment outcomes and patient survival. However, the effectiveness of ML models heavily relies on both the choice of algorithms...

Development and validation of predictive models for diabetic retinopathy using machine learning.

PloS one
OBJECTIVE: This study aimed to develop and compare machine learning models for predicting diabetic retinopathy (DR) using clinical and biochemical data, specifically logistic regression, random forest, XGBoost, and neural networks.

Machine learning using random forest to differentiate between blow and fall situations of head trauma.

International journal of legal medicine
Blunt head trauma is a common occurrence in forensic practice. Interpreting the origin of craniocerebral injuries can be a challenging process, particularly when it comes to distinguishing between falls or inflicted blows. The objective of this study...