AIMC Topic: Machine Learning

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Psoas muscle CT radiomics-based machine learning models to predict response to infliximab in patients with Crohn's disease.

Annals of medicine
BACKGROUND: Crohn's disease (CD) is a chronic inflammatory bowel disease, with infliximab (IFX) commonly used for treatment. However, no clinically applicable model currently exists to predict the response of patients with CD to IFX therapy. Given th...

Assessing chronic obstructive pulmonary disease risk based on exhalation and cough sounds.

Biomedical engineering online
BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD), a progressively worsening respiratory condition, severely impacts patient quality of life. Early risk assessment can improve treatment outcomes and lessen healthcare burdens. How...

Employing machine learning for early detection of poly-victimization in rural children: a survey study in China's Chaoshan region.

BMC public health
BACKGROUND: Poly-victimization (PV), encompassing multiple forms of victimization including physical abuse, emotional maltreatment, neglect, and peer violence, poses a significant public health challenge among children, particularly in rural areas wi...

Assessing psychological resilience and its influencing factors in the MSM population by machine learning.

Scientific reports
This study assesses the influence of social support, self-esteem, depression, and education on psychological resilience among men who have sex with men (MSM) to inform policy-making. Data were collected from 1,070 MSM via an online survey in Zhejiang...

Predictive modeling and machine learning show poor performance of clinical, morphological, and hemodynamic parameters for small intracranial aneurysm rupture.

Scientific reports
Small intracranial aneurysms (SIAs) (< 5 mm) are increasingly detected due to advanced imaging, but predicting rupture risk remains challenging. Rupture, though rare, can cause devastating subarachnoid hemorrhage. This study analyzed 141 SIAs (101 un...

A modular fluorescent camera unit for wound imaging.

Communications biology
Advanced imaging tools are revolutionizing the diagnosis, treatment, and monitoring of medical conditions, offering unprecedented insights into live cell behavior and biophysical markers. We introduce a modular, hand-held fluorescent microscope featu...

Development of an interpretable machine learning model for frailty risk prediction in older adult care institutions: a mixed-methods, cross-sectional study in China.

BMJ open
OBJECTIVE: To develop and validate an interpretable machine learning (ML)-based frailty risk prediction model that combines real-time health data with validated scale assessments for enhanced decision-making and targeted health management in integrat...

Combination of machine learning and protein‑protein interaction network established one ATM‑DPP4‑TXN ferroptotic diagnostic model with experimental validation.

Molecular medicine reports
Ferroptosis and lethal sepsis are interlinked, although this association remains largely unknown to clinical panels. Sepsis is characterized by dysfunction of the inflammatory microenvironment. Most septic biomarkers lack independent validation, and ...

Machine-learning based strategy identifies a robust protein biomarker panel for Alzheimer's disease in cerebrospinal fluid.

Alzheimer's research & therapy
BACKGROUND: The complex pathogenesis of Alzheimer's disease (AD) has resulted in limited current biomarkers for its classification and diagnosis, necessitating further investigation into reliable universal biomarkers or combinations.

Machine learning-based predictive tools and nomogram for in-hospital mortality in critically ill cancer patients: development and external validation using retrospective cohorts.

BMC medical informatics and decision making
BACKGROUND: The incidence of intensive care unit (ICU) admissions and the corresponding mortality rates among cancer patients are both high. However, the existing scoring systems all lack specificity. This research seeks to establish and validate a p...