AIMC Topic: Machine Learning

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Integration of machine learning in biomarker discovery for esophageal squamous cell carcinoma: Applications and future directions.

Pathology, research and practice
PURPOSE: Recent advancements in sequencing technologies and bioinformatics algorithms have facilitated significant breakthroughs in both fundamental and clinical tumor research. Nevertheless, the processing and utilization of large-scale data continu...

Integrative exome sequencing and machine learning identify MICB and interferon pathway genes as contributors to SSc risk.

Annals of the rheumatic diseases
OBJECTIVES: Systemic sclerosis (SSc) is a complex autoimmune disease with both known and unidentified genetic contributors. While genome-wide association studies (GWAS) have implicated multiple loci, many reside in noncoding regions. We aimed to iden...

Association between metal mixture in urine and abnormal blood pressure and mediated effect of oxidative stress based on BKMR and Machine learning method.

Ecotoxicology and environmental safety
BACKGROUND: Exposure to heavy metals represents a significant risk factor for hypertension and blood pressure disorders. Notably, current evidence indicates that the key biological processes of oxidative stress, inflammation, and endothelial dysfunct...

Spatiotemporal variations and driving mechanisms of carbon storage in Central Asia: Insights from the PLUS-InVEST models and machine learning.

Journal of environmental management
Against the backdrop of global climate change and rapid socioeconomic advancement, significant land use/cover changes(LUCC) in Central Asia have profoundly impacted terrestrial ecosystem carbon storage(CS). However, the assessment and spatiotemporal ...

Interpretable Machine Learning Prediction Model for Predicting Mortality Risk of ICU Patients With Pressure Ulcers Based on the Braden Scale: A Clinical Study Based on MIMIC-IV.

Journal of clinical nursing
AIMS: This study was to create an interpretable machine learning model to predict the risk of mortality within 90 days for ICU patients suffering from pressure ulcers.

A hybrid approach for machine learning based beat classification of ECG using different digital differentiators and DTCWT.

Computers in biology and medicine
This research paper presents a systematic approach to ECG beat classification using advanced machine learning techniques. The study classifies ECG beats into six distinct classes based on annotations from the MIT-BIH Arrhythmia Database. The methodol...

DNA-based prediction of eye color in Latin American population applying Machine Learning models.

Computers in biology and medicine
Reduction in the costs of DNA sequencing and genotyping allows for the increased availability of databases which can be useful for analyzing the relationship between the human genetic code and visible characteristics, diseases, and behaviors, among o...

Comprehensive duck DNA fingerprinting based on machine learning for breed identification.

Poultry science
Duck is one of the most widely distributed waterfowl in the world, with more than 6 billion of them farmed annually in the world, and has great economic and ecological value. Amidst mounting global prioritization of duck genetic resource exploration ...

Prediction of treatment efficacy in the suanzaoren decoction and estazolam for chronic insomnia disorder, along with brain function and cognitive changes before and after treatment, and potential gene expression profiles.

Asian journal of psychiatry
OBJECTIVE: This study compared the brain function changes in chronic insomnia disorder (CID) before and after treatment by suanzaoren decoction (SZRD) and estazolam, to reveal their effects in cognition improvement, and to explore the potential genet...

The Construction of a New Prognostic Model of Breast Cancer and the Exploration of Drug Sensitivity Based on Machine Learning for Glycosylation-Related Genes.

Clinical breast cancer
AIMS: Breast cancer has become the number 1 killer threatening women's health. In recent years, glycosylation modification has played an increasingly important role in tumor progression. The aim of this study was to explore the key genes that may be ...