AIMC Topic: Male

Clear Filters Showing 2071 to 2080 of 27433 articles

Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning.

BMC medical informatics and decision making
BACKGROUND: In the Intensive Care Unit (ICU), data stored in patient data management systems (PDMS) is commonly used in clinical practice and research. Parameters from point-of-care arterial blood gas (BG) analysis are used in the diagnosis and defin...

Precision nutrition in epigenetic aging: SHAP-optimized machine learning identifies omega-3 constituent-specific associations with aging biomarkers.

Biogerontology
This cross-sectional investigation seeks to examine the association between dietary omega-3 fatty acids (including α-linolenic acid [ALA], eicosapentaenoic acid [EPA], and docosahexaenoic acid [DHA]) and biomarkers of cellular aging, specifically DNA...

Perceived social support in the daily life of people with Parkinson's disease: a distinct role and potential classifier.

Scientific reports
Motor outcomes in Parkinson's disease (PD) have long been the primary diagnostic criteria and treatment targets. While non-motor outcomes of PD impact daily well-being, they are rarely targeted by interventions or utilized for classification. Despite...

A machine learning-based approach to predict depression in Chinese older adults with subjective cognitive decline: a longitudinal study.

Scientific reports
This study aims to identify depressive risks in elderly individuals with subjective cognitive decline (SCD) and develop a predictive model using machine learning algorithms to enable timely interventions.Data from the 2015 and 2018 waves of the China...

Predicting mortality risk in Alzheimer's disease using machine learning based on lifestyle and physical activity.

Scientific reports
Alzheimer's disease (AD), a progressive neurodegenerative disorder, significantly impacts patient survival, prompting the need for accurate prognostic tools. Lifestyle factors and physical activity levels have been identified as critical modifiable r...

Machine-learning driven strategies for adapting immunotherapy in metastatic NSCLC.

Nature communications
Immune checkpoint inhibitors (ICIs), either as monotherapy (ICI-Mono) or combined with chemotherapy (ICI-Chemo), improves survival in advanced non-small cell lung cancer (NSCLC). However, prospective guidance for choosing between these options remain...

Predicting In-Hospital Mortality in Intensive Care Unit Patients Using Causal SurvivalNet With Serum Chloride and Other Causal Factors: Cross-Country Study.

Journal of medical Internet research
BACKGROUND: Incorporating initial serum chloride levels as a prognostic indicator in the intensive care environment has the potential to refine risk stratification and tailor treatment strategies, leading to more efficient use of clinical resources a...

Decoding student cognitive abilities: a comparative study of explainable AI algorithms in educational data mining.

Scientific reports
Exploring students' cognitive abilities has long been an important topic in education. This study employs data-driven artificial intelligence (AI) models supported by explainability algorithms and PSM causal inference to investigate the factors influ...

Automated radiotherapy treatment planning guided by GPT-4Vision.

Physics in medicine and biology
. Radiotherapy treatment planning is a time-consuming and potentially subjective process that requires iterative adjustment of model parameters to balance multiple conflicting objectives. Recent advancements in frontier artificial intelligence (AI) m...

Post-stroke aphasia analysis using topological alterations in brain functional networks.

Journal of neural engineering
. Nearly one-third of stroke patients develop aphasia. Although the function of classical language areas (e.g. Broca's area, Wernicke's area) has been widely characterized, the network reorganization mechanisms behind specific language dysfunctions i...