AIMC Topic: ROC Curve

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Early Colorectal Cancer Detected by Machine Learning Model Using Gender, Age, and Complete Blood Count Data.

Digestive diseases and sciences Aug 23, 2017
BACKGROUND: Machine learning tools identify patients with blood counts indicating greater likelihood of colorectal cancer and warranting colonoscopy referral.
Algorithms Female Reproducibility of Results Risk Factors Adult Colorectal Neoplasms Male Aged Aged, 80 and over Registries Humans Data Mining Machine Learning Sex Factors Referral and Consultation Age Factors Blood Cell Count Early Detection of Cancer Odds Ratio Predictive Value of Tests Middle Aged Area Under Curve Colonoscopy Diagnosis, Computer-Assisted ROC Curve
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Bladder Cancer Treatment Response Assessment in CT using Radiomics with Deep-Learning.

Scientific reports Aug 18, 2017
Cross-sectional X-ray imaging has become the standard for staging most solid organ malignancies. However, for some malignancies such as urinary bladder cancer, the ability to accurately assess local extent of the disease and understand response to sy...
Treatment Outcome Urinary Bladder Neoplasms Medical Informatics Middle Aged Deep Learning ROC Curve Image Processing, Computer-Assisted Aged Aged, 80 and over Adult Male Humans Tomography, X-Ray Computed Female
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Prediction of Emergency Department Hospital Admission Based on Natural Language Processing and Neural Networks.

Methods of information in medicine Aug 16, 2017
OBJECTIVE: To describe and compare logistic regression and neural network modeling strategies to predict hospital admission or transfer following initial presentation to Emergency Department (ED) triage with and without the addition of natural langua...
ROC Curve Models, Theoretical Natural Language Processing Emergency Service, Hospital Adult Male Middle Aged Adolescent Vital Signs Humans Hospitalization Aged Young Adult Neural Networks, Computer Female
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Discrimination of plant root zone water status in greenhouse production based on phenotyping and machine learning techniques.

Scientific reports Aug 15, 2017
Plant-based sensing on water stress can provide sensitive and direct reference for precision irrigation system in greenhouse. However, plant information acquisition, interpretation, and systematical application remain insufficient. This study develop...
Reproducibility of Results Water ROC Curve Plant Roots Models, Biological Machine Learning Algorithms Phenotype Quantitative Trait, Heritable Plants Stress, Physiological Plant Physiological Phenomena Plant Development
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A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets.

Medical physics Aug 12, 2017
BACKGROUND: Deep learning methods for radiomics/computer-aided diagnosis (CADx) are often prohibited by small datasets, long computation time, and the need for extensive image preprocessing.
Retrospective Studies Breast Neoplasms Diagnosis, Computer-Assisted ROC Curve Image Processing, Computer-Assisted Humans Neural Networks, Computer
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A Method Based on Artificial Intelligence To Fully Automatize The Evaluation of Bovine Blastocyst Images.

Scientific reports Aug 9, 2017
Morphological analysis is the standard method of assessing embryo quality; however, its inherent subjectivity tends to generate discrepancies among evaluators. Using genetic algorithms and artificial neural networks (ANNs), we developed a new method ...
Automation, Laboratory Female Animals Cattle Embryo Transfer Neural Networks, Computer Blastocyst Artificial Intelligence Algorithms ROC Curve Image Processing, Computer-Assisted Microscopy
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Using Deep Learning for Classification of Lung Nodules on Computed Tomography Images.

Journal of healthcare engineering Aug 9, 2017
Lung cancer is the most common cancer that cannot be ignored and cause death with late health care. Currently, CT can be used to help doctors detect the lung cancer in the early stages. In many cases, the diagnosis of identifying the lung cancer depe...
Deep Learning ROC Curve Image Processing, Computer-Assisted Lung Neoplasms Humans Solitary Pulmonary Nodule Tomography, X-Ray Computed Neural Networks, Computer Radiography, Thoracic Reproducibility of Results Software Sensitivity and Specificity Algorithms Diagnosis, Computer-Assisted
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EMQIT: a machine learning approach for energy based PWM matrix quality improvement.

Biology direct Aug 1, 2017
BACKGROUND: Transcription factor binding affinities to DNA play a key role for the gene regulation. Learning the specificity of the mechanisms of binding TFs to DNA is important both to experimentalists and theoreticians. With the development of high...
Models, Genetic Transcription Factors Models, Molecular Datasets as Topic Gene Expression Regulation Machine Learning Software ROC Curve Computational Biology Binding Sites Position-Specific Scoring Matrices
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Coronary Computed Tomographic Angiography-Derived Fractional Flow Reserve Based on Machine Learning for Risk Stratification of Non-Culprit Coronary Narrowings in Patients with Acute Coronary Syndrome.

The American journal of cardiology Jul 25, 2017
This study investigated the prognostic value of coronary computed tomography angiography (cCTA)-derived fractional flow reserve (CT-FFR) in patients with acute coronary syndrome (ACS) and multivessel disease to gauge significance and guide management...
Humans Survival Rate Coronary Stenosis Male United States Fractional Flow Reserve, Myocardial Middle Aged Coronary Angiography Risk Assessment Machine Learning Acute Coronary Syndrome ROC Curve Prognosis Computed Tomography Angiography Retrospective Studies Female
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Protein asparagine deamidation prediction based on structures with machine learning methods.

PloS one Jul 21, 2017
Chemical stability is a major concern in the development of protein therapeutics due to its impact on both efficacy and safety. Protein "hotspots" are amino acid residues that are subject to various chemical modifications, including deamidation, isom...
Data Mining Solvents Asparagine Models, Statistical Amides Molecular Structure Supervised Machine Learning Software Computer Simulation ROC Curve
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