AIMC Topic: ROC Curve

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Deep learning model for diagnosing gastric mucosal lesions using endoscopic images: development, validation, and method comparison.

Gastrointestinal endoscopy Sep 4, 2021
BACKGROUND AND AIMS: Endoscopic differential diagnoses of gastric mucosal lesions (benign gastric ulcer, early gastric cancer [EGC], and advanced gastric cancer) remain challenging. We aimed to develop and validate convolutional neural network-based ...
Artificial Intelligence Deep Learning ROC Curve Area Under Curve Humans Neural Networks, Computer
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Ophthalmic Disease Detection via Deep Learning With a Novel Mixture Loss Function.

IEEE journal of biomedical and health informatics Sep 3, 2021
With the popularization of computer-aided diagnosis (CAD) technologies, more and more deep learning methods are developed to facilitate the detection of ophthalmic diseases. In this article, the deep learning-based detections for some common eye dise...
Humans Deep Learning ROC Curve Fundus Oculi Neural Networks, Computer Glaucoma Algorithms
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Accurate and Feasible Deep Learning Based Semi-Automatic Segmentation in CT for Radiomics Analysis in Pancreatic Neuroendocrine Neoplasms.

IEEE journal of biomedical and health informatics Sep 3, 2021
Current clinical practice or radiomics studies of pancreatic neuroendocrine neoplasms (pNENs) require manual delineation of the lesions in computed tomography (CT) images, which is time-consuming and subjective. We used a semi-automatic deep learning...
Humans Neoplasms ROC Curve Retrospective Studies Deep Learning Area Under Curve Tomography, X-Ray Computed
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Detecting hip osteoarthritis on clinical CT: a deep learning application based on 2-D summation images derived from CT.

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA Sep 2, 2021
UNLABELLED: We developed and compared deep learning models to detect hip osteoarthritis on clinical CT. The CT-based summation images, CT-AP, that resemble X-ray radiographs can detect radiographic hip osteoarthritis and in the absence of large train...
Radiography Osteoarthritis, Hip Tomography, X-Ray Computed Deep Learning ROC Curve Humans Retrospective Studies
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Revisiting performance metrics for prediction with rare outcomes.

Statistical methods in medical research Sep 1, 2021
Machine learning algorithms are increasingly used in the clinical literature, claiming advantages over logistic regression. However, they are generally designed to maximize the area under the receiver operating characteristic curve. While area under ...
Postoperative Complications ROC Curve Predictive Value of Tests Benchmarking False Positive Reactions Humans Machine Learning Algorithms
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AI outperformed every dermatologist in dermoscopic melanoma diagnosis, using an optimized deep-CNN architecture with custom mini-batch logic and loss function.

Scientific reports Sep 1, 2021
Melanoma, one of the most dangerous types of skin cancer, results in a very high mortality rate. Early detection and resection are two key points for a successful cure. Recent researches have used artificial intelligence to classify melanoma and nevu...
Humans Melanoma Skin Neoplasms Dermoscopy Neural Networks, Computer Artificial Intelligence Algorithms Deep Learning ROC Curve Dermatologists
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A Deep Learning Approach for Histopathological Diagnosis of Onychomycosis: Not Inferior to Analogue Diagnosis by Histopathologists.

Acta dermato-venereologica Aug 31, 2021
Onychomycosis is common. Diagnosis can be confirmed by various methods; a commonly used method is the histological examination of nail clippings. A deep learning system was developed and its diagnostic accuracy compared with that of human experts. A ...
Onychomycosis Artificial Intelligence Deep Learning ROC Curve Humans
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GenTB: A user-friendly genome-based predictor for tuberculosis resistance powered by machine learning.

Genome medicine Aug 30, 2021
BACKGROUND: Multidrug-resistant Mycobacterium tuberculosis (Mtb) is a significant global public health threat. Genotypic resistance prediction from Mtb DNA sequences offers an alternative to laboratory-based drug-susceptibility testing. User-friendly...
Tuberculosis, Multidrug-Resistant Software Workflow Web Browser Computational Biology Drug Resistance, Bacterial Humans Genome, Bacterial Microbial Sensitivity Tests Databases, Genetic Reproducibility of Results Machine Learning Antitubercular Agents ROC Curve Genomics
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Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

International journal of molecular sciences Aug 26, 2021
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for patients with non-small-cell lung cancer (NSCLC). We proposed a machin...
Mutation Lung Neoplasms Biomarkers Proto-Oncogene Proteins p21(ras) Supervised Machine Learning Carcinoma, Non-Small-Cell Lung Reproducibility of Results Male Tomography, X-Ray Computed Humans Neoplasm Staging Middle Aged Machine Learning Female ROC Curve Algorithms Aged Aged, 80 and over ErbB Receptors
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Explainable machine-learning predictions for complications after pediatric congenital heart surgery.

Scientific reports Aug 26, 2021
The quality of treatment and prognosis after pediatric congenital heart surgery remains unsatisfactory. A reliable prediction model for postoperative complications of congenital heart surgery patients is essential to enable prompt initiation of thera...
Humans Machine Learning Child, Preschool Male Algorithms ROC Curve Models, Cardiovascular Outcome Assessment, Health Care Postoperative Complications Prognosis Cardiac Surgical Procedures Infant Heart Defects, Congenital Female
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