AIMC Topic: Machine Learning
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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...
Software technical debt prediction based on complex software networks.
PloS one
Jun 9, 2025
Technical debt prediction (TDP) is crucial for the long-term maintainability of software. In the literature, many machine-learning based TDP models have been proposed; they used TD-related metrics as input features for machine-learning classifiers to...
Single-cell sequencing and machine learning reveal the role of dioxin-interacting genes in HCC prognosis and immune microenvironment.
Ecotoxicology and environmental safety
Jun 7, 2025
Dioxins are persistent environmental pollutants that bioaccumulate in the food chain, posing significant risks to human health. Despite their low environmental concentrations, dioxins accumulate in tissues, particularly in top predators and humans, r...
Machine learning classifiers to detect data pattern change of continuous emission monitoring system: A typical chemical industrial park as an example.
Environment international
Jun 7, 2025
Continuous Emission Monitoring Systems (CEMS) are critical for real-time pollutant measurement, widely deployed to supervise industrial emissions and ensure regulatory compliance. Despite their utility, CEMS data face challenges of data fabrications,...
Identification of macrophage-associated diagnostic biomarkers and molecular subtypes in gestational diabetes mellitus based on machine learning.
Artificial cells, nanomedicine, and biotechnology
Jun 6, 2025
Gestational diabetes mellitus (GDM) is a common metabolic disorder during pregnancy, involving multiple immune and inflammatory factors. Macrophages play a crucial role in its development. This study integrated scRNA-seq and RNA-seq data to explore m...
Evaluating the relationship between environmental chemicals and obesity: Evidence from a machine learning perspective.
Ecotoxicology and environmental safety
Jun 6, 2025
Environmental chemicals are increasingly recognized as important contributors to obesity, yet the number of studies evaluating this relationship remains insufficient. This study aimed to investigate these associations using interpretable machine lear...
Assessing simulation-based supervised machine learning for demographic parameter inference from genomic data.
Heredity
Jun 6, 2025
The ever-increasing availability of high-throughput DNA sequences and the development of numerous computational methods have led to considerable advances in our understanding of the evolutionary and demographic history of populations. Several demogra...
Multimodal Wearable Sensing for Biomechanics and Biomolecules Enabled by the M-MPM/VCFs@Ag Interface with Machine Learning Pipeline.
ACS sensors
Jun 6, 2025
The addition sensing device of sweat to wearable biostress sensors would eliminate the need for using multiple gadgets for healthcare analysis. Due to the distinct package fashion of sensor interface for biostress and biomolecule, achieving permeabil...
Quantum Machine Learning in Drug Discovery: Applications in Academia and Pharmaceutical Industries.
Chemical reviews
Jun 6, 2025
The nexus of quantum computing and machine learning─quantum machine learning─offers the potential for significant advancements in chemistry. This Review specifically explores the potential of quantum neural networks on gate-based quantum computers wi...
AVP-HNCL: Innovative Contrastive Learning with a Queue-Based Negative Sampling Strategy for Dual-Phase Antiviral Peptide Prediction.
Journal of chemical information and modeling
Jun 6, 2025
Viral infections have long been a core focus in the field of public health. Antiviral peptides (AVPs), due to their unique mechanisms of action and significant inhibitory effects against a wide range of viruses, exhibit tremendous potential in protec...
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