AIMC Topic: Supervised Machine Learning

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Early detection of vascular catheter-associated infections employing supervised machine learning - a case study in Lleida region.

BMC medical informatics and decision making Aug 11, 2025
Healthcare-associated infections (HAIs), particularly Vascular Catheter-Associated Infections (VCAIs), are a significant concern, accounting for over 7% of all infections and are often linked to medical devices. Early detection of VCAIs before invasi...
Retrospective Studies Female Aged Humans Machine Learning Male Middle Aged Catheter-Related Infections Supervised Machine Learning Early Diagnosis Spain
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Prediction of human pathogenic start loss variants based on self-supervised contrastive learning.

BMC biology Aug 8, 2025
BACKGROUND: Start loss variants are a class of genetic variants that affect the bases of the start codon, disrupting the normal translation initiation process and leading to protein deletions or the production of different proteins. Accurate assessme...
Humans Codon, Initiator Computational Biology Supervised Machine Learning Genetic Variation
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Semi-supervised medical image segmentation based on multi-stage iterative training and high-confidence pseudo-labeling.

Biomedical physics & engineering express Aug 6, 2025
Due to the scarcity and high cost of pixel-level annotations for training data, semi-supervised learning has gradually become a key solution. Most existing methods rely on consistency regularization and pseudo-label generation, often adopting multi-b...
Heart Supervised Machine Learning Humans Reproducibility of Results Algorithms Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Semi-supervised contrastive learning variational autoencoder Integrating single-cell multimodal mosaic datasets.

BMC bioinformatics Aug 4, 2025
As single-cell sequencing technology became widely used, scientists found that single-modality data alone could not fully meet the research needs of complex biological systems. To address this issue, researchers began simultaneously collect multi-mod...
Humans Software Cluster Analysis Supervised Machine Learning Autoencoder Algorithms Single-Cell Analysis Computational Biology
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A hybrid supervised and unsupervised machine learning approach for identifying nucleoside drugs using nanopore readouts.

Nanoscale Jul 31, 2025
Nucleoside drugs, mimics of natural nucleosides, have become cornerstone treatments in clinical approaches to combat cancer and viral infections. The analysis of nucleoside drugs is commonly performed using liquid chromatography-tandem mass spectrome...
Tandem Mass Spectrometry Nanopores Supervised Machine Learning Humans Nucleosides Antiviral Agents Machine Learning Chromatography, Liquid Antineoplastic Agents Unsupervised Machine Learning
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Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning.

BMC medical informatics and decision making Jul 24, 2025
BACKGROUND: In the Intensive Care Unit (ICU), data stored in patient data management systems (PDMS) is commonly used in clinical practice and research. Parameters from point-of-care arterial blood gas (BG) analysis are used in the diagnosis and defin...
Blood Gas Analysis Middle Aged Supervised Machine Learning Retrospective Studies Intensive Care Units Female Aged Adult Male Humans
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Decoding basic emotional states through integration of an fNIRS-based brain-computer interface with supervised learning algorithms.

PloS one Jul 14, 2025
Automated detection of emotional states through brain-computer interfaces (BCIs) offers significant potential for enhancing user experiences and personalizing services across domains such as mental health, adaptive learning and interactive entertainm...
Algorithms Female Young Adult Adult Male Spectroscopy, Near-Infrared Humans Emotions Prefrontal Cortex Supervised Machine Learning Support Vector Machine Brain-Computer Interfaces
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Identification of right ventricular dysfunction with LogNNet based diagnostic model: A comparative study with supervised ML algorithms.

Scientific reports Jul 12, 2025
Right ventricular dysfunction (RVD) is strongly associated with increased mortality in patients with acute pulmonary embolism (PE), making its early detection crucial. Identifying RVD risk factors rapidly, accurately, and economically within the acut...
Humans Ventricular Dysfunction, Right Machine Learning Supervised Machine Learning Aged Middle Aged Algorithms Aged, 80 and over Pulmonary Embolism Female Male Risk Factors
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Ensemble methods and partially-supervised learning for accurate and robust automatic murine organ segmentation.

Scientific reports Jul 2, 2025
Delineation of multiple organs in murine µCT images is crucial for preclinical studies but requires manual volumetric segmentation, a tedious and time-consuming process prone to inter-observer variability. Automatic deep learning-based segmentation c...
X-Ray Microtomography Reproducibility of Results Animals Mice Deep Learning Supervised Machine Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted
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MS-EmoBoost: a novel strategy for enhancing self-supervised speech emotion representations.

Scientific reports Jul 1, 2025
Extracting richer emotional representations from raw speech is one of the key approaches to improving the accuracy of Speech Emotion Recognition (SER). In recent years, there has been a trend in utilizing self-supervised learning (SSL) for extracting...
Speech Humans Speech Recognition Software Emotions Algorithms Supervised Machine Learning
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