AIMC Topic: Supervised Machine Learning

Clear Filters Showing 1041 to 1050 of 1729 articles

Machine learning for syndromic surveillance using veterinary necropsy reports.

PloS one Feb 5, 2020
The use of natural language data for animal population surveillance represents a valuable opportunity to gather information about potential disease outbreaks, emerging zoonotic diseases, or bioterrorism threats. In this study, we evaluate machine lea...
Supervised Machine Learning ROC Curve Gastrointestinal Diseases Logistic Models Urologic Diseases Machine Learning Animals Deep Learning Area Under Curve Lung Diseases
View on PubMed DOI

Learning metal artifact reduction in cardiac CT images with moving pacemakers.

Medical image analysis Jan 30, 2020
Metal objects in the human heart such as implanted pacemakers frequently lead to heavy artifacts in reconstructed CT image volumes. Due to cardiac motion, common metal artifact reduction methods which assume a static object during CT acquisition are ...
Motion Artifacts Pacemaker, Artificial Metals Radiographic Image Interpretation, Computer-Assisted Supervised Machine Learning Humans Neural Networks, Computer Tomography, X-Ray Computed
View on PubMed DOI

Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

International journal of radiation oncology, biology, physics Jan 23, 2020
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...
Aged Aged, 80 and over Adult Breast Neoplasms Middle Aged Skin Humans Biomarkers Female Radiodermatitis Supervised Machine Learning Molecular Imaging Skin Temperature
View on PubMed DOI

Application of data mining in a cohort of Italian subjects undergoing myocardial perfusion imaging at an academic medical center.

Computer methods and programs in biomedicine Jan 16, 2020
INTRODUCTION: Coronary artery disease (CAD) is still one of the primary causes of death in the developed countries. Stress single-photon emission computed tomography is used to evaluate myocardial perfusion and ventricular function in patients with s...
Tomography, Emission-Computed, Single-Photon Myocardial Perfusion Imaging Supervised Machine Learning Data Mining Academic Medical Centers Aged Sensitivity and Specificity Male Italy Coronary Artery Disease Middle Aged Bayes Theorem Humans Female
View on PubMed DOI

Semi-supervised learning for automatic segmentation of the knee from MRI with convolutional neural networks.

Computer methods and programs in biomedicine Jan 11, 2020
BACKGROUND AND OBJECTIVE: Segmentation is a crucial step in multiple biomechanics and orthopedics applications. The time-intensiveness and expertise requirements of medical image segmentation present a significant bottleneck for corresponding workflo...
Knee Joint Supervised Machine Learning Monte Carlo Method Neural Networks, Computer Algorithms Deep Learning Imaging, Three-Dimensional Image Processing, Computer-Assisted Magnetic Resonance Imaging Humans
View on PubMed DOI

Single-modal and multi-modal false arrhythmia alarm reduction using attention-based convolutional and recurrent neural networks.

PloS one Jan 10, 2020
This study proposes a deep learning model that effectively suppresses the false alarms in the intensive care units (ICUs) without ignoring the true alarms using single- and multi- modal biosignals. Most of the current work in the literature are eithe...
Sensitivity and Specificity Monitoring, Physiologic Supervised Machine Learning Arrhythmias, Cardiac False Positive Reactions Neural Networks, Computer Humans Clinical Alarms Algorithms Intensive Care Units
View on PubMed DOI

Deep-Channel uses deep neural networks to detect single-molecule events from patch-clamp data.

Communications biology Jan 7, 2020
Single-molecule research techniques such as patch-clamp electrophysiology deliver unique biological insight by capturing the movement of individual proteins in real time, unobscured by whole-cell ensemble averaging. The critical first step in analysi...
Humans Neural Networks, Computer Artificial Intelligence Supervised Machine Learning Single Molecule Imaging Ion Channels Electrophysiological Phenomena ROC Curve Workflow Models, Biological Ion Channel Gating Patch-Clamp Techniques
View on PubMed DOI

Evolving knowledge graph similarity for supervised learning in complex biomedical domains.

BMC bioinformatics Jan 3, 2020
BACKGROUND: In recent years, biomedical ontologies have become important for describing existing biological knowledge in the form of knowledge graphs. Data mining approaches that work with knowledge graphs have been proposed, but they are based on ve...
Knowledge Bases Data Mining Semantics Humans Algorithms Supervised Machine Learning Biological Ontologies Gene Ontology
View on PubMed DOI

PGxCorpus, a manually annotated corpus for pharmacogenomics.

Scientific data Jan 2, 2020
Pharmacogenomics (PGx) studies how individual gene variations impact drug response phenotypes, which makes PGx-related knowledge a key component towards precision medicine. A significant part of the state-of-the-art knowledge in PGx is accumulated in...
Pharmacogenetics Supervised Machine Learning Humans PubMed Data Curation
View on PubMed DOI

Semi-Supervised Learning for Semantic Segmentation of Emphysema With Partial Annotations.

IEEE journal of biomedical and health informatics Dec 31, 2019
Segmentation and quantification of each subtype of emphysema is helpful to monitor chronic obstructive pulmonary disease. Due to the nature of emphysema (diffuse pulmonary disease), it is very difficult for experts to allocate semantic labels to ever...
Radiographic Image Interpretation, Computer-Assisted Supervised Machine Learning Male Emphysema Humans Lung Tomography, X-Ray Computed Deep Learning Female
View on PubMed DOI
Popular Topics
Recent Journals