AIMC Topic: Area Under Curve

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Overlooked pitfalls in multi-class machine learning classification in radiation oncology and how to avoid them.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Jan 25, 2020
In radiation oncology, Machine Learning classification publications are typically related to two outcome classes, e.g. the presence or absence of distant metastasis. However, multi-class classification problems also have great clinical relevance, e.g...
Monte Carlo Method Radiation Injuries Radiation Exposure Models, Theoretical Area Under Curve Radiation Oncology Technology Assessment, Biomedical Humans Machine Learning Biomarkers Risk Factors
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Application of artificial intelligence using convolutional neural networks in determining the invasion depth of esophageal squamous cell carcinoma.

Esophagus : official journal of the Japan Esophageal Society Jan 24, 2020
OBJECTIVES: In Japan, endoscopic resection (ER) is often used to treat esophageal squamous cell carcinoma (ESCC) when invasion depths are diagnosed as EP-SM1, whereas ESCC cases deeper than SM2 are treated by surgical operation or chemoradiotherapy. ...
Male Middle Aged Deep Learning Neoplasm Invasiveness Reproducibility of Results Aged Aged, 80 and over Humans Sensitivity and Specificity Esophageal Squamous Cell Carcinoma Neural Networks, Computer Preoperative Care Artificial Intelligence Endoscopic Mucosal Resection Retrospective Studies Area Under Curve Female Esophageal Neoplasms Japan Outcome Assessment, Health Care
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Improvement of classification performance of Parkinson's disease using shape features for machine learning on dopamine transporter single photon emission computed tomography.

PloS one Jan 24, 2020
OBJECTIVE: To assess the classification performance between Parkinson's disease (PD) and normal control (NC) when semi-quantitative indicators and shape features obtained on dopamine transporter (DAT) single photon emission computed tomography (SPECT...
Parkinson Disease Area Under Curve Corpus Striatum Tomography, Emission-Computed, Single-Photon Machine Learning Databases, Factual Case-Control Studies ROC Curve Humans
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Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

European radiology Jan 21, 2020
OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading.
Humans Neural Networks, Computer Machine Learning Algorithms Biomarkers Retrospective Studies Female Aged Data Accuracy Liver Cirrhosis Elasticity Imaging Techniques Adult Liver Male Area Under Curve Middle Aged Hepatitis B, Chronic ROC Curve
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Validating the validation: reanalyzing a large-scale comparison of deep learning and machine learning models for bioactivity prediction.

Journal of computer-aided molecular design Jan 20, 2020
Machine learning methods may have the potential to significantly accelerate drug discovery. However, the increasing rate of new methodological approaches being published in the literature raises the fundamental question of how models should be benchm...
Benchmarking Drug Evaluation, Preclinical User-Computer Interface ROC Curve Support Vector Machine Area Under Curve Humans Machine Learning Algorithms Computer Simulation Drug Discovery Deep Learning
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DC-AL GAN: Pseudoprogression and true tumor progression of glioblastoma multiform image classification based on DCGAN and AlexNet.

Medical physics Jan 20, 2020
PURPOSE: Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. PsP exhibits similarities in shape and intensity to the true tumor progression (TTP) of GBM on the follow-up magn...
Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Glioblastoma Area Under Curve Humans Disease Progression
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Classification of Interstitial Lung Abnormality Patterns with an Ensemble of Deep Convolutional Neural Networks.

Scientific reports Jan 15, 2020
Subtle interstitial changes in the lung parenchyma of smokers, known as Interstitial Lung Abnormalities (ILA), have been associated with clinical outcomes, including mortality, even in the absence of Interstitial Lung Disease (ILD). Although several ...
Tomography, X-Ray Computed Humans Lung Neural Networks, Computer ROC Curve Databases, Factual Area Under Curve Radiographic Image Interpretation, Computer-Assisted Prognosis Lung Diseases, Interstitial
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Convolutional neural network-automated hepatobiliary phase adequacy evaluation may optimize examination time.

European journal of radiology Jan 14, 2020
PURPOSE: To develop and evaluate the performance of a fully-automated convolutional neural network (CNN)-based algorithm to evaluate hepatobiliary phase (HBP) adequacy of gadoxetate disodium (EOB)-enhanced MRI. Secondarily, we explored the potential ...
Liver Area Under Curve Workflow Image Interpretation, Computer-Assisted ROC Curve Liver Neoplasms Contrast Media Magnetic Resonance Imaging Time Gadolinium DTPA Algorithms Retrospective Studies Female Aged Adult Male Middle Aged Efficiency Humans Neural Networks, Computer
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Evaluation of the predictive ability of ultrasound-based assessment of breast cancer using BI-RADS natural language reporting against commercial transcriptome-based tests.

PloS one Jan 10, 2020
PURPOSE: The objective of this study was to assess the classification capability of Breast Imaging Reporting and Data System (BI-RADS) ultrasound feature descriptors targeting established commercial transcriptomic gene signatures that guide managemen...
Gene Expression Profiling Humans Area Under Curve Research Design Retrospective Studies Ultrasonography, Mammary Female Breast Neoplasms Middle Aged Cohort Studies ROC Curve Natural Language Processing
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Retraining an open-source pneumothorax detecting machine learning algorithm for improved performance to medical images.

Clinical imaging Jan 8, 2020
PURPOSE: To validate a machine learning model trained on an open source dataset and subsequently optimize it to chest X-rays with large pneumothoraces from our institution.
Algorithms Retrospective Studies Sensitivity and Specificity Male Humans Machine Learning Deep Learning Area Under Curve Radiography Pneumothorax
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