AIMC Topic: ROC Curve

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Precision Radiology: Predicting longevity using feature engineering and deep learning methods in a radiomics framework.

Scientific reports May 10, 2017
Precision medicine approaches rely on obtaining precise knowledge of the true state of health of an individual patient, which results from a combination of their genetic risks and environmental exposures. This approach is currently limited by the lac...
Reproducibility of Results Risk Factors Deep Learning ROC Curve Humans Phenotype Precision Medicine Tomography, X-Ray Computed Task Performance and Analysis Kaplan-Meier Estimate Mortality Longevity Image Processing, Computer-Assisted Area Under Curve Diagnostic Imaging Radiology
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Dysphonic Voice Pattern Analysis of Patients in Parkinson's Disease Using Minimum Interclass Probability Risk Feature Selection and Bagging Ensemble Learning Methods.

Computational and mathematical methods in medicine May 3, 2017
Analysis of quantified voice patterns is useful in the detection and assessment of dysphonia and related phonation disorders. In this paper, we first study the linear correlations between 22 voice parameters of fundamental frequency variability, ampl...
Voice ROC Curve Humans Logistic Models Machine Learning Algorithms Support Vector Machine Parkinson Disease
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Differentiation of Enhancing Glioma and Primary Central Nervous System Lymphoma by Texture-Based Machine Learning.

AJNR. American journal of neuroradiology Apr 27, 2017
BACKGROUND AND PURPOSE: Accurate preoperative differentiation of primary central nervous system lymphoma and enhancing glioma is essential to avoid unnecessary neurosurgical resection in patients with primary central nervous system lymphoma. The purp...
Central Nervous System Neoplasms ROC Curve Glioma Support Vector Machine Lymphoma Magnetic Resonance Imaging Adult Humans Diagnosis, Differential Sensitivity and Specificity Algorithms Image Interpretation, Computer-Assisted Male Female Image Enhancement Middle Aged
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Deep Learning at Chest Radiography: Automated Classification of Pulmonary Tuberculosis by Using Convolutional Neural Networks.

Radiology Apr 24, 2017
Purpose To evaluate the efficacy of deep convolutional neural networks (DCNNs) for detecting tuberculosis (TB) on chest radiographs. Materials and Methods Four deidentified HIPAA-compliant datasets were used in this study that were exempted from revi...
Radiography, Thoracic Retrospective Studies Sensitivity and Specificity ROC Curve Tuberculosis, Pulmonary Humans Neural Networks, Computer Algorithms
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Metastasis detection from whole slide images using local features and random forests.

Cytometry. Part A : the journal of the International Society for Analytical Cytology Apr 20, 2017
Digital pathology has led to a demand for automated detection of regions of interest, such as cancerous tissue, from scanned whole slide images. With accurate methods using image analysis and machine learning, significant speed-up, and savings in cos...
Lymphocytes Image Interpretation, Computer-Assisted Cell Nucleus Histocytochemistry ROC Curve Lymph Nodes Lymphatic Metastasis Area Under Curve Eosine Yellowish-(YS) Hematoxylin Humans Machine Learning Software Female Adult Breast Neoplasms Middle Aged
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Two-phase deep convolutional neural network for reducing class skewness in histopathological images based breast cancer detection.

Computers in biology and medicine Apr 18, 2017
Different types of breast cancer are affecting lives of women across the world. Common types include Ductal carcinoma in situ (DCIS), Invasive ductal carcinoma (IDC), Tubular carcinoma, Medullary carcinoma, and Invasive lobular carcinoma (ILC). While...
Machine Learning Algorithms Female Breast Neoplasms ROC Curve Image Interpretation, Computer-Assisted Cell Nucleus Histocytochemistry Humans Mitosis Neural Networks, Computer
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Cascade convolutional neural networks for automatic detection of thyroid nodules in ultrasound images.

Medical physics Apr 17, 2017
PURPOSE: It is very important for calculation of clinical indices and diagnosis to detect thyroid nodules from ultrasound images. However, this task is a challenge mainly due to heterogeneous thyroid nodules with distinct components are similar to ba...
Humans Neural Networks, Computer Ultrasonography Thyroid Nodule ROC Curve Probability
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Driver behavior profiling: An investigation with different smartphone sensors and machine learning.

PloS one Apr 10, 2017
Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver behavior profiling tries to understand and positively impact driver behavior. Usually driver behavior profiling tasks involve automated collection of driving da...
Automobile Driving Accelerometry Behavior ROC Curve Humans Smartphone Neural Networks, Computer Area Under Curve Machine Learning Bayes Theorem
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Use of a machine learning framework to predict substance use disorder treatment success.

PloS one Apr 10, 2017
There are several methods for building prediction models. The wealth of currently available modeling techniques usually forces the researcher to judge, a priori, what will likely be the best method. Super learning (SL) is a methodology that facilitat...
Substance-Related Disorders Neural Networks, Computer Area Under Curve Machine Learning ROC Curve Middle Aged Databases, Factual Socioeconomic Factors Diagnosis, Computer-Assisted Female Prognosis Treatment Outcome Humans Length of Stay Young Adult Regression Analysis Adolescent Adult Male
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Comparison of Machine Learning Approaches for Prediction of Advanced Liver Fibrosis in Chronic Hepatitis C Patients.

IEEE/ACM transactions on computational biology and bioinformatics Apr 4, 2017
BACKGROUND/AIM: Using machine learning approaches as non-invasive methods have been used recently as an alternative method in staging chronic liver diseases for avoiding the drawbacks of biopsy. This study aims to evaluate different machine learning ...
Algorithms Biomarkers Female Young Adult Humans Machine Learning Diagnosis, Computer-Assisted Models, Statistical Adolescent Hepatitis C, Chronic ROC Curve Liver Cirrhosis Adult Male Middle Aged Disease Progression
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