AIMC Topic: Machine Learning

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Machine learning algorithms integrate bulk and single-cell RNA data to reveal the crosstalk and heterogeneity of NOTCH and autophagy activity following idiopathic pulmonary fibrosis.

International immunopharmacology Jun 9, 2025
BACKGROUND: NOTCH and autophagy significantly impact the pathogenesis of idiopathic pulmonary fibrosis (IPF); however, studies exploring their heterogeneity and potential correlation at the single-cell level are still lacking. Identifying the feature...
Machine Learning Algorithms Single-Cell Analysis Humans Fibroblasts Autophagy Receptors, Notch Sequence Analysis, RNA Signal Transduction Idiopathic Pulmonary Fibrosis
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Explainable machine learning model for predicting internal mammary node metastasis in breast cancer: Multi-method development and cross-cohort validation.

Breast (Edinburgh, Scotland) Jun 9, 2025
BACKGROUND: This study developed an explainable machine learning model for baseline internal mammary lymph node metastasis (IMNM) in breast cancer patients.
Breast Neoplasms Middle Aged Risk Assessment Female Aged Adult Support Vector Machine Lymphatic Metastasis Neoplasm Staging Cohort Studies Logistic Models Lymph Nodes Humans Machine Learning SEER Program
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Predicting reticuloruminal pH and subacute ruminal acidosis of individual cows using machine learning and Fourier-transform infrared spectroscopy milk analysis.

Journal of dairy science Jun 9, 2025
Low reticuloruminal pH (rpH) for a prolonged period could lead to SARA. This disease negatively affects cow health and is associated with monetary losses for the dairy industry. The aim of this study was to predict rpH and SARA separately using diffe...
Spectroscopy, Fourier Transform Infrared Hydrogen-Ion Concentration Milk Acidosis Rumen Machine Learning Animals Female Cattle Cattle Diseases
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Few-shot learning and deep predictive models for cost optimization and carbon emission reduction in energy-water management.

Journal of environmental management Jun 9, 2025
Effective management of energy and water resources is essential for mitigating environmental impacts and enhancing sustainability. This paper proposes a multiple-objective linear program tailored to accommodate energy-water applications in diverse cl...
Carbon Netherlands Machine Learning
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Screening of Biomaterials for Stem Cell Culture Applications.

ACS biomaterials science & engineering Jun 9, 2025
Stem cells have a considerable role to play in future biomedical breakthroughs due to their therapeutic potential. As stem cells may be studied in a variety of different applications, a "one size fits all" approach to the stem cell culture substrate ...
Animals Stem Cells Biocompatible Materials Cell Culture Techniques Humans Machine Learning
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Interpretable web-based machine learning model for predicting intravenous immunoglobulin resistance in Kawasaki disease.

Italian journal of pediatrics Jun 9, 2025
BACKGROUND: Kawasaki disease (KD) is a leading cause of acquired heart disease in children that is treated with intravenous immunoglobulin (IVIG). However, 10-20% of cases exhibit IVIG resistance, which increases the risk of coronary complications. E...
Male Risk Assessment Infant Child, Preschool Child Mucocutaneous Lymph Node Syndrome Machine Learning Retrospective Studies Female Humans Drug Resistance Predictive Value of Tests Internet Immunoglobulins, Intravenous
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Integrated muti-omics data and machine learning reveal CD151 as a key biomarker inducing chemoresistance in metabolic syndrome-related early-onset left-sided colorectal cancer.

Functional & integrative genomics Jun 9, 2025
Emerging evidence has suggested a potential pathological association between early-onset left-sided colorectal cancer (EOLCC) and metabolic syndrome (MetS). However, the underlying genetic and molecular mechanisms remain insufficiently elucidated. Th...
Tetraspanin 24 Gene Expression Regulation, Neoplastic Metabolic Syndrome Drug Resistance, Neoplasm Humans Female Male Machine Learning Colorectal Neoplasms Middle Aged Biomarkers, Tumor Gene Regulatory Networks
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Investigating methods to enhance interpretability and performance in cardiac MRI for myocardial scarring diagnosis using convolutional neural network classification and One Match.

PloS one Jun 9, 2025
Machine learning (ML) classification of myocardial scarring in cardiac MRI is often hindered by limited explainability, particularly with convolutional neural networks (CNNs). To address this, we developed One Match (OM), an algorithm that builds on ...
Male Heart Humans Algorithms Magnetic Resonance Imaging Middle Aged Image Interpretation, Computer-Assisted Female Neural Networks, Computer Convolutional Neural Networks Cicatrix Aged Machine Learning Myocardium
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BanglaNewsClassifier: A machine learning approach for news classification in Bangla Newspapers using hybrid stacking classifiers.

PloS one Jun 9, 2025
Bangla news floods the web, and the need for smarter and more efficient classification techniques is greater than ever. Previous studies mostly focused on traditional models, overlooking the potential of hybrid techniques to handle the ever-growing c...
Machine Learning Algorithms Language Humans Deep Learning Support Vector Machine Newspapers as Topic
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Aggregating soft labels from crowd annotations improves uncertainty estimation under distribution shift.

PloS one Jun 9, 2025
Selecting an effective training signal for machine learning tasks is difficult: expert annotations are expensive, and crowd-sourced annotations may not be reliable. Recent work has demonstrated that learning from a distribution over labels acquired f...
Crowdsourcing Uncertainty Humans Machine Learning Algorithms
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