AIMC Topic: Machine Learning

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Application of generalized linear mixed effects random forest for identifying risk factors of prediabetes in Tehran Lipid and Glucose Study.

Scientific reports
Prediabetes is a major risk factor for the development of diabetes, defined by blood glucose levels that are elevated but not yet high enough to meet the diagnostic criteria for Diabetes Mellitus. This condition is often clinically "silent" yet it ca...

Rapid screening for acute rheumatic fever using machine learning analysis of host tissue reactive antibodies.

Scientific reports
Acute Rheumatic Fever and Rheumatic Heart Disease (ARF/RHD) affect over 45 million people globally. ARF/RHD are autoimmune complications following group A streptococcal infections. Current diagnosis of ARF requires thorough medical examination, echoc...

Functional connectivity between non-motor and motor networks predicts motor recovery changes after stroke.

Scientific reports
Stroke impairs limb motor function, which affects patients' quality of life and imposes economic burdens. Early prediction of motor recovery is essential for guiding treatment and rehabilitation. While the corticospinal tract is a known biomarker, th...

MarkerPredict: predicting clinically relevant predictive biomarkers with machine learning.

NPJ systems biology and applications
Precision oncology relies on predictive biomarkers for selecting targeted cancer therapies. Network-based properties of proteins, together with structural features such as intrinsic disorder, are likely to shape their potential as biomarkers. We ther...

Aetiological clustering of newly diagnosed type 2 diabetes using machine learning: a retrospective cross-sectional study in Dubai, UAE.

BMJ open
OBJECTIVES: Type 2 diabetes (T2D) is a complex disease with a heterogeneous clinical presentation. Recently, five distinct clusters of T2D have been identified in the Emirati population of long-standing T2D with complications. This study aimed to val...

Machine learning-based fabrication of phytogenic NiO nanoparticles for anticancer activity in HepG2 Cell Culture.

Journal of materials science. Materials in medicine
Metal oxide nanomaterials play a central role in biomedical applications due to their unique physicochemical properties. In particular, various treatment methods such as drug delivery, hyperthermia therapy, radiation, and chemotherapy are used for th...

Development and validation of a machine learning-based prognostic model for gastric cancer: a multicenter retrospective study.

Langenbeck's archives of surgery
BACKGROUND: Machine learning has emerged as a promising tool for survival prediction in various diseases; however, its application and external validation in real-world gastric cancer populations remain limited.

[Suicide epidemiology in the province of Málaga (Spain) [2024]: a retrospective analysis using machine learning techniques].

Revista espanola de salud publica
OBJECTIVE: Suicide constitutes a Public Health challenge whose demographic and geographical heterogeneity demands targeted interventions. The paucity of subnational studies integrating advanced data analytics restricts the precise identification of r...

Evaluating community resilience through social media during China's first post-COVID-19 reopening: insights from machine learning.

Journal of global health
BACKGROUND: In the face of pandemics from infectious diseases, enhancing community resilience is increasingly important. It is, therefore, essential to evaluate community resilience and identify factors that can strengthen it. This study aimed to eva...

Utilising bioinformatics and molecular docking technology to explore the underlying mechanisms of intervertebral disc degeneration with potential therapeutic drugs and formulas.

Journal of global health
BACKGROUND: Intervertebral disc degeneration (IDD) is prevalent in orthopaedics, yet lacks effective treatments. This study seeks to discover potential therapeutic targets for IDD to inform clinical therapies and traditional medicine approaches.