AIMC Topic: Middle Aged

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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...

Calcium ion dynamic trajectory is associated with prognosis in patients with sepsis: A potential class mixture modeling study.

International immunopharmacology
Disturbed calcium homeostasis in patients with sepsis is associated with poor prognosis; however, its dynamic pattern and clinical significance remain unclear. This study aimed to establish an early warning system for calcium homeostasis in sepsis by...

Integrating machine learning and metabolomics to uncover new biomarkers for predicting pesticide exposure among patients with kidney function decline.

The Science of the total environment
Although pesticide application is indispensable for agricultural productivity, improper use can pose significant health risks, particularly for vulnerable populations. This study investigated the effects of pesticide exposure on metabolic pathways an...

A practical approach to predicting long-term outcomes in traumatic brain injury: Enhancing clinical decision-making with machine learning.

Computers in biology and medicine
BACKGROUND: Traumatic brain injury (TBI) is among the most prevalent causes of emergency department visits globally. TBI leads to high morbidity and mortality rates, which poses a noteworthy burden on the medical system regarding both patients and ec...

Clinical diagnostic and prognostic value of homocysteine combined with hemoglobin [f (Hcy-Hb)] in cardio-renal syndrome caused by primary acute myocardial infarction.

Journal of translational medicine
BACKGROUND: Cardio-renal syndrome (CRS), characterized by multi-organ interaction, is frequently overlooked in clinical practice. It poses significant challenges in treatment, leading to poor long-term prognosis and substantial economic burden on pat...

Development and validation of risk prediction models for acute kidney disease in gout patients: a retrospective study using machine learning.

European journal of medical research
BACKGROUND: Limited research has been conducted on the prevalence of acute kidney injury (AKI) and acute kidney disease (AKD) in gout patients, as well as the impact of these renal complications on patient outcomes. This study aims to develop machine...

Preoperative MRI-based radiomics analysis of intra- and peritumoral regions for predicting CD3 expression in early cervical cancer.

Scientific reports
The study investigates the correlation between CD3 T-cell expression levels and cervical cancer (CC) while developing a magnetic resonance (MR) imaging-based radiomics model for preoperative prediction of CD3 T-cell expression levels. Prognostic corr...

Public hesitancy for AI-based detection of neurodegenerative diseases in France.

Scientific reports
Recent advances in artificial intelligence (AI) have made it possible to detect neurodegenerative diseases (NDDs) earlier, potentially improving patient outcomes. However, AI-based detection tools remain underutilized. We studied individual valuation...

Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription.

Scientific reports
The increasing prevalence of type 2 diabetes (T2D) is a significant health concern worldwide. Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. Machine learning (ML) has the po...