AIMC Topic: Machine Learning

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Amazon's climate crossroads: analyzing air pollution and health impacts under machine learning-based temperature increase scenarios in Northern Mato Grosso, Brazil.

Environmental geochemistry and health
Air pollution has long been a public health concern in South America, now increasingly linked to climate change. In Brazil, this issue is particularly acute in smaller cities with limited monitoring infrastructure. Sinop, located in the Amazon biome ...

Predictors and associations of complications in ureteroscopy for stone disease using AI: outcomes from the FLEXOR registry.

Urolithiasis
We aimed to develop machine learning(ML) algorithms to evaluate complications of flexible ureteroscopy and laser lithotripsy(fURSL), providing a valid predictive model. 15 ML algorithms were trained on a large number fURSL data from > 6500 patients f...

A customizable P hydrogel applicator for brachytherapy of skin hemangioma based on machine learning and 3D-printing.

Journal of materials chemistry. B
Skin hemangioma is a tumor originating from skin blood vessels, which often occurs in infants and children. Brachytherapy with the P-based radionuclide applicator is an effective non-invasive therapeutic method. However, the inordinance of lesions is...

Perceptual and technical barriers in sharing and formatting metadata accompanying omics studies.

Cell genomics
Metadata, or "data about data," is essential for organizing, understanding, and managing large-scale omics datasets. It enhances data discovery, integration, and interpretation, enabling reproducibility, reusability, and secondary analysis. However, ...

Analyzing Key Predictors of Postoperative Delirium Following Coronary Artery Bypass Grafting and Aortic Valve Replacement: A Machine Learning Perspective.

Medicina (Kaunas, Lithuania)
: Postoperative delirium (POD) is a frequent and severe complication following cardiac surgery, particularly in high-risk patients undergoing coronary artery bypass grafting (CABG) and aortic valve replacement (AVR). Despite extensive research, predi...

Past, Present and Future Perspectives of Forensic Genetics.

Biomolecules
Forensic genetics has experienced remarkable advancements over the past decades, evolving from the analysis of a limited number of DNA segments to comprehensive genome-wide investigations. This progression has significantly improved the ability to es...

Identifying Mild-to-Moderate Atopic Dermatitis Using a Generic Machine Learning Approach: A Danish National Health Register Study.

Acta dermato-venereologica
Atopic dermatitis is a chronic skin disease, causing itching and recurrent eczematous lesions. In Danish national register data, adults with atopic dermatitis can only be identified if they have a hospital-diagnosed atopic dermatitis. The purpose of ...

Identifying Lactylation-related biomarkers and therapeutic drugs in ulcerative colitis: insights from machine learning and molecular docking.

BMC pharmacology & toxicology
BACKGROUND: Ulcerative colitis (UC), a chronic relapsing-remitting inflammatory bowel disease. Recent studies have shown that lactylation modifications may be involved in metabolic-immune interactions in intestinal inflammation through epigenetic reg...

Development and validation of a novel predictive model for dementia risk in middle-aged and elderly depression individuals: a large and longitudinal machine learning cohort study.

Alzheimer's research & therapy
BACKGROUND: Depression serves as a prodromal symptom of dementia, and individuals with depression exhibit a significantly higher risk of developing dementia. The aim of this study is to develop and validate a novel dementia risk prediction tool among...