AIMC Topic: Machine Learning
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MAMSI: Integration of Multiassay Liquid Chromatography-Mass Spectrometry Metabolomics Data Using Multiview Machine Learning.
Analytical chemistry
Jul 10, 2025
Liquid chromatography-mass spectrometry (LC-MS) is a commonly used analytical technique in untargeted metabolomics. However, the diverse chemical and physical properties of metabolites often require the use of several different analytical assays for ...
Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis.
Orphanet journal of rare diseases
Jul 10, 2025
OBJECTIVE: Emerging evidence suggests a potential relationship between lipid metabolism and idiopathic pulmonary fibrosis (IPF). This study aimed to identify lipid-related genes implicated in IPF pathogenesis.
Application progress of machine learning in patient-ventilator asynchrony during mechanical ventilation: a systematic review.
Critical care (London, England)
Jul 10, 2025
INTRODUCTION: Patient-ventilator asynchrony (PVA) is a common and harmful complication during mechanical ventilation, often requiring labor-intensive manual assessment. Machine learning (ML) offers a promising approach for automated and accurate PVA ...
Predicting antiretroviral therapy adherence status of adult HIV-positive patients using machine-learning Northwest, Ethiopia, 2025.
BMC medical informatics and decision making
Jul 10, 2025
BACKGROUND: Adherence with Anti-Retroviral Therapy (ART) reduces viral load, as well as HIV-related morbidity and mortality. Despite the expanded availability of ART, non-adherence remains a series problem, leads increased viral load, a decline CD4 c...
Interpretive prediction of hyperuricemia and gout patients via machine learning analysis of human gut microbiome.
BMC microbiology
Jul 10, 2025
Hyperuricemia (HUA) and gout result from imbalances in uric acid metabolism and are closely associated with the gut microbiota. Advanced analytical methods facilitate the exploration of microbiota complexity. In this study, 16S rRNA sequencing data f...
GeoAI-based soil erosion risk assessment in the Brahmaputra River Basin: a synergistic approach using RUSLE and advanced machine learning.
Environmental monitoring and assessment
Jul 10, 2025
Soil erosion is a critical environmental issue in the Brahmaputra River Basin, threatening agricultural productivity, water resources, and ecological balance. This study employs the revised universal soil loss equation (RUSLE) alongside remote sensin...
Machine learning analysis of survival outcomes in breast cancer patients treated with chemotherapy, hormone therapy, surgery, and radiotherapy.
Scientific reports
Jul 10, 2025
Breast cancer continues to be a leading cause of death among women in the world. The prediction of survival outcomes based on treatment modalities, i.e., chemotherapy, hormone therapy, surgery, and radiation therapy is an essential step towards perso...
Machine learning models predict risk of lower extremity deep vein thrombosis in hospitalized patients with spontaneous intracerebral hemorrhage.
Scientific reports
Jul 10, 2025
Lower extremity deep vein thrombosis is one of the important complications of spontaneous intracerebral hemorrhage. We aimed to develop a risk assessment model to predict the risk of lower extremity DVT during hospitalization in patients with spontan...
Comprehensive multi-omics and machine learning framework for glioma subtyping and precision therapeutics.
Scientific reports
Jul 10, 2025
Glioma is a highly heterogeneous and aggressive brain tumour that demands an integrated understanding of its molecular and immunological landscape. We collected multi-omics data from 575 TCGA diffuse-glioma patients (156 IDH-wild-type WHO-grade 4 gli...
Exploiting heart rate variability for driver drowsiness detection using wearable sensors and machine learning.
Scientific reports
Jul 10, 2025
Driver drowsiness is a critical issue in transportation systems and a leading cause of traffic accidents. Common factors contributing to accidents include intoxicated driving, fatigue, and sleep deprivation. Drowsiness significantly impairs a driver'...
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