AIMC Topic: ROC Curve
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Evaluating machine learning methodologies for identification of cancer driver genes.
Scientific reports
Jun 10, 2021
Cancer is driven by distinctive sorts of changes and basic variations in genes. Recognizing cancer driver genes is basic for accurate oncological analysis. Numerous methodologies to distinguish and identify drivers presently exist, but efficient tool...
Weighing features of lung and heart regions for thoracic disease classification.
BMC medical imaging
Jun 10, 2021
BACKGROUND: Chest X-rays are the most commonly available and affordable radiological examination for screening thoracic diseases. According to the domain knowledge of screening chest X-rays, the pathological information usually lay on the lung and he...
A machine learning approach to predicting risk of myelodysplastic syndrome.
Leukemia research
Jun 8, 2021
BACKGROUND: Early myelodysplastic syndrome (MDS) diagnosis can allow physicians to provide early treatment, which may delay advancement of MDS and improve quality of life. However, MDS often goes unrecognized and is difficult to distinguish from othe...
The application of artificial intelligence methods to gene expression data for differentiation of uncomplicated and complicated appendicitis in children and adolescents - a proof of concept study.
BMC pediatrics
Jun 8, 2021
BACKGROUND: Genome wide gene expression analysis has revealed hints for independent immunological pathways underlying the pathophysiologies of phlegmonous (PA) and gangrenous appendicitis (GA). Methods of artificial intelligence (AI) have successfull...
Reliable Prediction Models Based on Enriched Data for Identifying the Mode of Childbirth by Using Machine Learning Methods: Development Study.
Journal of medical Internet research
Jun 4, 2021
BACKGROUND: The use of artificial intelligence has revolutionized every area of life such as business and trade, social and electronic media, education and learning, manufacturing industries, medicine and sciences, and every other sector. The new ref...
Natural language processing for the surveillance of postoperative venous thromboembolism.
Surgery
Jun 3, 2021
BACKGROUND: The objective of this study was to develop a portal natural language processing approach to aid in the identification of postoperative venous thromboembolism events from free-text clinical notes.
A deep transfer learning framework for the automated assessment of corneal inflammation on in vivo confocal microscopy images.
PloS one
Jun 3, 2021
PURPOSE: Infiltration of activated dendritic cells and inflammatory cells in cornea represents an important marker for defining corneal inflammation. Deep transfer learning has presented a promising potential and is gaining more importance in compute...
Application of machine learning approaches to administrative claims data to predict clinical outcomes in medical and surgical patient populations.
PloS one
Jun 3, 2021
OBJECTIVE: This study aimed to develop and validate a claims-based, machine learning algorithm to predict clinical outcomes across both medical and surgical patient populations.
An Effective Method for Detecting and Classifying Diabetic Retinopathy Lesions Based on Deep Learning.
Computational and mathematical methods in medicine
May 31, 2021
Diabetic retinopathy occurs as a result of the harmful effects of diabetes on the eyes. Diabetic retinopathy is also a disease that should be diagnosed early. If not treated early, vision loss may occur. It is estimated that one third of more than ha...
i4mC-EL: Identifying DNA N4-Methylcytosine Sites in the Mouse Genome Using Ensemble Learning.
BioMed research international
May 29, 2021
As one of important epigenetic modifications, DNA N4-methylcytosine (4mC) plays a crucial role in controlling gene replication, expression, cell cycle, DNA replication, and differentiation. The accurate identification of 4mC sites is necessary to und...
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