AIMC Topic: Machine Learning

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Identification of key genes as diagnostic biomarkers for IBD using bioinformatics and machine learning.

Journal of translational medicine
BACKGROUND: The pathogenesis of inflammatory bowel disease (IBD) involves complex molecular mechanisms, and achieving clinical remission remains challenging. This study aims to identify IBD-potential biomarkers, analyze their correlation with immune ...

The value of triglyceride-glucose index-related indices in evaluating migraine: perspectives from multi-centre cross-sectional studies and machine learning models.

Lipids in health and disease
BACKGROUND: This study employed representative data from the U.S. and China to delve into the correlation among migraine prevalence, the triglyceride‒glucose index, a marker of insulin resistance, and the composite indicator of obesity.

Keyword-optimized template insertion for clinical note classification via prompt-based learning.

BMC medical informatics and decision making
BACKGROUND: Prompt-based learning involves the additions of prompts (i.e., templates) to the input of pre-trained large language models (PLMs) to adapt them to specific tasks with minimal training. This technique is particularly advantageous in clini...

Development and external validation of machine learning models for the early prediction of malnutrition in critically ill patients: a prospective observational study.

BMC medical informatics and decision making
BACKGROUND: Early detection of malnutrition in critically ill patients is crucial for timely intervention and improved clinical outcomes. However, identifying individuals at risk remains challenging due to the complexity and variability of patient co...

Interpretable machine learning analysis of immunoinflammatory biomarkers for predicting CHD among NAFLD patients.

Cardiovascular diabetology
BACKGROUND: Coronary Heart Disease (CHD) and Non-Alcoholic Fatty Liver Disease (NAFLD) share overlapping pathogenic mechanisms including adipose tissue dysfunction, insulin resistance, and systemic inflammation mediated by adipokines. However, the sp...

Construction and validation of a risk prediction model for chronic obstructive pulmonary disease (COPD): a cross-sectional study based on the NHANES database from 2009 to 2018.

BMC pulmonary medicine
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a major global public health concern, and early screening and identification of high-risk populations are critical for reducing the disease burden. Although several studies have explored the...

Network-based machine learning reveals cardiometabolic multimorbidity patterns and modifiable lifestyle factors: a community-focused analysis of NHANES 2015-2018.

BMC public health
Cardiometabolic Multimorbidity (CMM) has emerged as one of the primary threats to human health globally due to its high incidence, disability, and mortality rates. Accurate identification of CMM patterns is crucial for CMM classification and health m...

Predicting carotid atherosclerosis in latent autoimmune diabetes in adult patients using machine learning models: a retrospective study.

BMC cardiovascular disorders
BACKGROUND: Latent autoimmune diabetes in adults (LADA) is a slowly progressing form of diabetes with autoimmune origins. Patients with LADA are at an elevated risk of developing cardiovascular diseases, including carotid atherosclerosis. While machi...

A novel hybrid vision UNet architecture for brain tumor segmentation and classification.

Scientific reports
This paper focuses on designing and developing novel architectures termed Hybrid Vision UNet-Encoder Decoder (HVU-ED) segmenter and Hybrid Vision UNet-Encoder (HVU-E) classifier for brain tumor segmentation and classification, respectively. The propo...

Enhancing game outcome prediction in the Chinese basketball league through a machine learning framework based on performance data.

Scientific reports
Basketball remains among the most globally popular sports, with its various competitions drawing substantial attention. The analysis and modeling of basketball game data have long been central topics in sports analytics. In recent years, integrating ...