AIMC Topic: ROC Curve

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Unenhanced CT texture analysis with machine learning for differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma.

Nagoya journal of medical science Feb 1, 2021
Differentiating between nasopharyngeal cancer and nasopharyngeal malignant lymphoma (ML) remains challenging on cross-sectional images. The aim of this study is to investigate the usefulness of texture features on unenhanced CT for differentiating be...
Nasopharyngeal Neoplasms Biopsy Carcinoma Radiopharmaceuticals Image Interpretation, Computer-Assisted Fluorodeoxyglucose F18 Female Aged Adult Male Middle Aged ROC Curve Support Vector Machine Lymphoma Diagnosis, Differential Area Under Curve Positron Emission Tomography Computed Tomography Humans
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Screening and identifying hepatobiliary diseases through deep learning using ocular images: a prospective, multicentre study.

The Lancet. Digital health Feb 1, 2021
BACKGROUND: Ocular changes are traditionally associated with only a few hepatobiliary diseases. These changes are non-specific and have a low detection rate, limiting their potential use as clinically independent diagnostic features. Therefore, we ai...
Humans Algorithms Prospective Studies Computer Simulation Mass Screening Liver Area Under Curve Conjunctiva Fundus Oculi Models, Biological Adult Middle Aged Deep Learning China ROC Curve Sclera Iris Photography Eye Digestive System Diseases Slit Lamp Microscopy
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Low Predictability of Readmissions and Death Using Machine Learning in Cirrhosis.

The American journal of gastroenterology Feb 1, 2021
INTRODUCTION: Readmission and death in cirrhosis are common, expensive, and difficult to predict. Our aim was to evaluate the abilities of multiple artificial intelligence (AI) techniques to predict clinical outcomes based on variables collected at a...
Gastrointestinal Hemorrhage Proton Pump Inhibitors Infections Hepatic Encephalopathy Paracentesis Rifaximin Lactulose Mortality beta-Lactams Hydrothorax Adrenergic beta-Antagonists Humans Reproducibility of Results Ascites Clinical Decision Rules Machine Learning Aged End Stage Liver Disease Gastrointestinal Agents Anti-Bacterial Agents Male Cohort Studies Water-Electrolyte Imbalance Female Middle Aged ROC Curve Patient Readmission Severity of Illness Index Logistic Models Liver Cirrhosis Support Vector Machine Kidney Diseases
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Early prediction of mortality risk among patients with severe COVID-19, using machine learning.

International journal of epidemiology Jan 23, 2021
BACKGROUND: Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 infection, has been spreading globally. We aimed to develop a clinical model to predict the outcome of patients with severe COVID-19 infection ...
Hospitals Case-Control Studies ROC Curve Patient Admission Aged Sensitivity and Specificity Male Middle Aged Risk Assessment Humans Machine Learning COVID-19 Female SARS-CoV-2 Hospitalization
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Evaluation of Combined Cancer Markers With Lactate Dehydrogenase and Application of Machine Learning Algorithms for Differentiating Benign Disease From Malignant Ovarian Cancer.

Cancer control : journal of the Moffitt Cancer Center Jan 1, 2021
BACKGROUND: The differential diagnosis of ovarian cancer is important, and there has been ongoing research to identify biomarkers with higher performance. This study aimed to evaluate the diagnostic utility of combinations of cancer markers classifie...
Diagnosis, Differential Middle Aged Ovarian Neoplasms Humans ROC Curve Leukocyte Count Lymphocytes Membrane Proteins Machine Learning WAP Four-Disulfide Core Domain Protein 2 L-Lactate Dehydrogenase Female Neutrophils CA-125 Antigen Adult Early Detection of Cancer Biomarkers, Tumor
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Colorectal Cancer Detected by Machine Learning Models Using Conventional Laboratory Test Data.

Technology in cancer research & treatment Jan 1, 2021
Current diagnostic methods for colorectal cancer (CRC) are colonoscopy and sigmoidoscopy, which are invasive and complex procedures with possible complications. This study aimed to determine models for CRC identification that involve minimally invas...
Male Female Middle Aged Humans Aged Case-Control Studies Machine Learning Support Vector Machine Adult ROC Curve Retrospective Studies Area Under Curve Colorectal Neoplasms Logistic Models Electronic Health Records Diagnostic Tests, Routine Biomarkers, Tumor
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Automated Identification of Dental Implants Using Artificial Intelligence.

The International journal of oral & maxillofacial implants Jan 1, 2021
PURPOSE: To develop and evaluate the accuracy of a computer-assisted system based on artificial intelligence for detecting and identifying dental implant brands using digital periapical radiographs.
Neural Networks, Computer Artificial Intelligence Algorithms ROC Curve Dental Implants
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Differentiation of Intrahepatic Cholangiocarcinoma and Hepatic Lymphoma Based on Radiomics and Machine Learning in Contrast-Enhanced Computer Tomography.

Technology in cancer research & treatment Jan 1, 2021
This study aimed to explore the ability of texture parameters combining with machine learning methods in distinguishing intrahepatic cholangiocarcinoma (ICCA) and hepatic lymphoma (HL). A total of 28 patients with HL and 101 patients with ICCA were...
Radiographic Image Enhancement Diagnosis, Differential Neoplasm Grading Tumor Burden Bile Duct Neoplasms Algorithms Cholangiocarcinoma Middle Aged Tomography, X-Ray Computed ROC Curve Female Image Processing, Computer-Assisted Reproducibility of Results Lymphoma Humans Aged Contrast Media Machine Learning Male
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Deep Learning Models for Gastric Signet Ring Cell Carcinoma Classification in Whole Slide Images.

Technology in cancer research & treatment Jan 1, 2021
Signet ring cell carcinoma (SRCC) of the stomach is a rare type of cancer with a slowly rising incidence. It tends to be more difficult to detect by pathologists, mainly due to its cellular morphology and diffuse invasion manner, and it has poor prog...
Humans Stomach Neoplasms Deep Learning ROC Curve Computational Biology Area Under Curve Carcinoma, Signet Ring Cell Supervised Machine Learning False Negative Reactions False Positive Reactions
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Dr. Answer AI for Prostate Cancer: Predicting Biochemical Recurrence Following Radical Prostatectomy.

Technology in cancer research & treatment Jan 1, 2021
OBJECTIVES: To develop a model to predict biochemical recurrence (BCR) after radical prostatectomy (RP), using artificial intelligence (AI) techniques.
Prostatic Neoplasms Prostate-Specific Antigen Models, Biological Neoplasm Recurrence, Local Prostatectomy Adult Humans Artificial Intelligence Male Software Middle Aged Aged ROC Curve Aged, 80 and over Decision Trees Area Under Curve
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