AIMC Topic:
Supervised Machine Learning

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ProteinMAE: masked autoencoder for protein surface self-supervised learning.

Bioinformatics (Oxford, England) Dec 1, 2023
SUMMARY: The biological functions of proteins are determined by the chemical and geometric properties of their surfaces. Recently, with the booming progress of deep learning, a series of learning-based surface descriptors have been proposed and achie...
Membrane Proteins Natural Language Processing Protein Domains Supervised Machine Learning Binding Sites
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Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

Journal of the American Medical Informatics Association : JAMIA Nov 17, 2023
OBJECTIVE: Development of electronic health records (EHR)-based machine learning models for pediatric inpatients is challenged by limited training data. Self-supervised learning using adult data may be a promising approach to creating robust pediatri...
Humans Machine Learning Retrospective Studies Electronic Health Records Adult Child Inpatients Supervised Machine Learning
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SSLpheno: a self-supervised learning approach for gene-phenotype association prediction using protein-protein interactions and gene ontology data.

Bioinformatics (Oxford, England) Nov 1, 2023
MOTIVATION: Medical genomics faces significant challenges in interpreting disease phenotype and genetic heterogeneity. Despite the establishment of standardized disease phenotype databases, computational methods for predicting gene-phenotype associat...
Neural Networks, Computer Phenotype Genomics Supervised Machine Learning Gene Ontology
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Evidential meta-model for molecular property prediction.

Bioinformatics (Oxford, England) Oct 3, 2023
MOTIVATION: The usefulness of supervised molecular property prediction (MPP) is well-recognized in many applications. However, the insufficiency and the imbalance of labeled data make the learning problem difficult. Moreover, the reliability of the p...
Computational Biology Supervised Machine Learning
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Uncertainty Estimation with Data Augmentation for Active Learning Tasks on Health Data.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Supervised machine learning (ML) is revolutionising healthcare, but the acquisition of reliable labels for signals harvested from medical sensors is usually challenging, manual, and costly. Active learning can assist in establishing labels on-the-fly...
Algorithms Supervised Machine Learning Problem-Based Learning Uncertainty
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Predicting Dementia Risk for Elderly Community Dwellers in Primary Care Services Using Subgroup-specific Prediction Models.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2023
Early detection of individuals with a high risk of dementia is crucial for prompt intervention and clinical care. This study aims to identify high-risk groups for developing dementia by predicting the outcome of the Mini-Mental State Examination (MMS...
Humans Algorithms Aged Dementia Primary Health Care Supervised Machine Learning
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Supervised learning.

American journal of orthodontics and dentofacial orthopedics : official publication of the American Association of Orthodontists, its constituent societies, and the American Board of Orthodontics Jul 1, 2023
Humans Algorithms Supervised Machine Learning
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Deep Learning-Enabled Detection of Pneumoperitoneum in Supine and Erect Abdominal Radiography: Modeling Using Transfer Learning and Semi-Supervised Learning.

Korean journal of radiology Jun 1, 2023
OBJECTIVE: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using sup...
Humans Retrospective Studies Deep Learning Radiography Supervised Machine Learning Radiography, Thoracic Radiography, Abdominal
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COVID-19 disease identification network based on weakly supervised feature selection.

Mathematical biosciences and engineering : MBE Mar 16, 2023
The coronavirus disease 2019 (COVID-19) outbreak has resulted in countless infections and deaths worldwide, posing increasing challenges for the health care system. The use of artificial intelligence to assist in diagnosis not only had a high accurac...
Humans Neural Networks, Computer COVID-19 Supervised Machine Learning Datasets as Topic
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A Transferable Machine Learning Framework for Predicting Transcriptional Responses of Genes Across Species.

Methods in molecular biology (Clifton, N.J.) Jan 1, 2023
Leveraging existing resources in studied species to predict gene functions has the potential to rapidly expand understanding of annotated genes in other, less well-studied, species with assembled genomes. However, orthology is not a reliable predicto...
Machine Learning Supervised Machine Learning Poaceae Cold-Shock Response
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