AIMC Topic: ROC Curve

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Prediction of ISUP grading of clear cell renal cell carcinoma using support vector machine model based on CT images.

Medicine Apr 1, 2019
BACKGROUND: To explore whether radiomics combined with computed tomography (CT) images can be used to establish a model for differentiating high grade (International Society of Urological Pathology [ISUP] grade III-IV) from low-grade (ISUP I-II) clea...
ROC Curve Support Vector Machine Diagnosis, Differential Predictive Value of Tests Area Under Curve Neoplasm Grading Kidney Neoplasms Retrospective Studies Carcinoma, Renal Cell Tomography, X-Ray Computed Female Male Middle Aged Humans
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Supervised machine learning for the prediction of infection on admission to hospital: a prospective observational cohort study.

The Journal of antimicrobial chemotherapy Apr 1, 2019
BACKGROUND: Infection diagnosis can be challenging, relying on clinical judgement and non-specific markers of infection. We evaluated a supervised machine learning (SML) algorithm for diagnosing bacterial infection using routinely available blood par...
Aged, 80 and over Young Adult Adult Male Middle Aged Biomarkers Prognosis Clinical Decision-Making Female Humans Aged Algorithms Disease Management Diagnostic Tests, Routine Infections Cohort Studies Patient Admission ROC Curve Hematologic Tests Decision Support Systems, Clinical Follow-Up Studies Supervised Machine Learning
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Deep Learning Approach for Assessment of Bladder Cancer Treatment Response.

Tomography (Ann Arbor, Mich.) Mar 1, 2019
We compared the performance of different Deep learning-convolutional neural network (DL-CNN) models for bladder cancer treatment response assessment based on transfer learning by freezing different DL-CNN layers and varying the DL-CNN structure. Pre-...
Urography Transfer, Psychology Neoadjuvant Therapy Urinary Bladder Neoplasms Deep Learning Humans Drug Monitoring ROC Curve Tomography, X-Ray Computed Radiographic Image Interpretation, Computer-Assisted Decision Support Systems, Clinical Sensitivity and Specificity Cystectomy Treatment Outcome Antineoplastic Agents
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Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation.

Journal of glaucoma Mar 1, 2019
UNLABELLED: PRéCIS:: The novel proposed algorithm using deep learning classifier and polar transformation technique can be an economical as well as an effective tool for early detection of glaucomatous RNFL defect.
Retinal Ganglion Cells Ophthalmologic Surgical Procedures Diagnostic Techniques, Ophthalmological Photography Glaucoma, Open-Angle ROC Curve Area Under Curve Tomography, Optical Coherence Image Interpretation, Computer-Assisted Nerve Fibers Humans Retrospective Studies Female Adult Intraocular Pressure Male Middle Aged Deep Learning
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Natural language processing and machine learning to identify alcohol misuse from the electronic health record in trauma patients: development and internal validation.

Journal of the American Medical Informatics Association : JAMIA Mar 1, 2019
OBJECTIVE: Alcohol misuse is present in over a quarter of trauma patients. Information in the clinical notes of the electronic health record of trauma patients may be used for phenotyping tasks with natural language processing (NLP) and supervised ma...
Male Middle Aged Cohort Studies ROC Curve Natural Language Processing Humans Machine Learning Electronic Health Records Female Adult Alcoholism Wounds and Injuries Trauma Centers
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Angiography-Based Machine Learning for Predicting Fractional Flow Reserve in Intermediate Coronary Artery Lesions.

Journal of the American Heart Association Feb 19, 2019
Background An angiography-based supervised machine learning ( ML ) algorithm was developed to classify lesions as having fractional flow reserve ≤0.80 versus >0.80. Methods and Results With a 4:1 ratio, 1501 patients with 1501 intermediate lesions we...
Coronary Stenosis Fractional Flow Reserve, Myocardial Humans Severity of Illness Index Machine Learning ROC Curve Imaging, Three-Dimensional Algorithms Coronary Angiography Retrospective Studies Coronary Vessels Female Male Middle Aged
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Low coherence quantitative phase microscopy with machine learning model and Raman spectroscopy for the study of breast cancer cells and their classification.

Applied optics Feb 10, 2019
Early-stage detection of breast cancer is the primary requirement in modern healthcare as it is the most common cancer among women worldwide. Histopathology is the most widely preferred method for the diagnosis of breast cancer, but it requires long ...
Interferometry Sensitivity and Specificity Humans Breast Neoplasms Machine Learning ROC Curve Female Spectrum Analysis, Raman Reproducibility of Results Microscopy, Interference
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Deep Learning for Prediction of AMD Progression: A Pilot Study.

Investigative ophthalmology & visual science Feb 1, 2019
PURPOSE: To develop and assess a method for predicting the likelihood of converting from early/intermediate to advanced wet age-related macular degeneration (AMD) using optical coherence tomography (OCT) imaging and methods of deep learning.
Follow-Up Studies Tomography, Optical Coherence Wet Macular Degeneration Humans Diagnosis, Computer-Assisted Neural Networks, Computer Deep Learning Machine Learning Pilot Projects Female Aged ROC Curve Aged, 80 and over Male Middle Aged Disease Progression
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Heart rate variability based machine learning models for risk prediction of suspected sepsis patients in the emergency department.

Medicine Feb 1, 2019
Early identification of high-risk septic patients in the emergency department (ED) may guide appropriate management and disposition, thereby improving outcomes. We compared the performance of machine learning models against conventional risk stratifi...
Middle Aged Severity of Illness Index Sepsis Hospital Mortality Systemic Inflammatory Response Syndrome ROC Curve Socioeconomic Factors Triage Emergency Service, Hospital Singapore Female Heart Rate Reproducibility of Results Humans Aged Organ Dysfunction Scores Aged, 80 and over Machine Learning Male
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Machine Learning for the Prediction of New-Onset Diabetes Mellitus during 5-Year Follow-up in Non-Diabetic Patients with Cardiovascular Risks.

Yonsei medical journal Feb 1, 2019
PURPOSE: Many studies have proposed predictive models for type 2 diabetes mellitus (T2DM). However, these predictive models have several limitations, such as user convenience and reproducibility. The purpose of this study was to develop a T2DM predic...
Cardiovascular Diseases Middle Aged ROC Curve Diabetes Mellitus, Type 2 Logistic Models Follow-Up Studies Humans Machine Learning Algorithms Republic of Korea Female Reproducibility of Results Risk Factors Male
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