AIMC Topic: Retrospective Studies

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Diagnostic evaluation of a deep learning model for optical diagnosis of colorectal cancer.

Nature communications Jun 11, 2020
Colonoscopy is commonly used to screen for colorectal cancer (CRC). We develop a deep learning model called CRCNet for optical diagnosis of CRC by training on 464,105 images from 12,179 patients and test its performance on 2263 patients from three in...
Humans Machine Learning Retrospective Studies Female Aged Colorectal Neoplasms Male Gastroenterology Middle Aged Colonoscopy Deep Learning
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Corneal Topography Raw Data Classification Using a Convolutional Neural Network.

American journal of ophthalmology Jun 10, 2020
PURPOSE: We investigated the efficiency of a convolutional neural network applied to corneal topography raw data to classify examinations of 3 categories: normal, keratoconus (KC), and history of refractive surgery (RS).
Female Reproducibility of Results Adult Sensitivity and Specificity Male Corneal Pachymetry Middle Aged Humans Refractive Errors Neural Networks, Computer Keratoconus Machine Learning Corneal Topography Retrospective Studies Refractive Surgical Procedures Healthy Volunteers
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Clinico-radiological characteristic-based machine learning in reducing unnecessary prostate biopsies of PI-RADS 3 lesions with dual validation.

European radiology Jun 10, 2020
OBJECTIVE: To evaluate machine learning-based classifiers in detecting clinically significant prostate cancer (PCa) with Prostate Imaging Reporting and Data System (PI-RADS) score 3 lesions.
Multiparametric Magnetic Resonance Imaging Logistic Models Support Vector Machine Decision Trees Area Under Curve Radiography Prostatic Neoplasms Prostate-Specific Antigen Prostate Validation Studies as Topic Image-Guided Biopsy Unnecessary Procedures Aged, 80 and over Male Middle Aged Ultrasonography ROC Curve Humans Machine Learning Retrospective Studies Reproducibility of Results Aged
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Deep learning analysis using FDG-PET to predict treatment outcome in patients with oral cavity squamous cell carcinoma.

European radiology Jun 10, 2020
OBJECTIVE: To assess the utility of deep learning analysis using F-fluorodeoxyglucose (FDG) uptake by positron emission tomography (PET/CT) to predict disease-free survival (DFS) in patients with oral cavity squamous cell carcinoma (OCSCC).
Reproducibility of Results Aged Aged, 80 and over Adult Sensitivity and Specificity Male Humans Algorithms Retrospective Studies Female Squamous Cell Carcinoma of Head and Neck Predictive Value of Tests Positron Emission Tomography Computed Tomography Neoplasm Staging Mouth Neoplasms Disease-Free Survival Middle Aged Diagnosis, Computer-Assisted Deep Learning Glycolysis Treatment Outcome Tumor Burden Fluorodeoxyglucose F18 Kaplan-Meier Estimate
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Assessment of liver metastases radiomic feature reproducibility with deep-learning-based semi-automatic segmentation software.

Acta radiologica (Stockholm, Sweden : 1987) Jun 9, 2020
BACKGROUND: Good feature reproducibility enhances model reliability. The manual segmentation of gastric cancer with liver metastasis (GCLM) can be time-consuming and unstable.
Stomach Neoplasms Male Middle Aged Deep Learning Liver Neoplasms Image Processing, Computer-Assisted Retrospective Studies Adenocarcinoma Tomography, X-Ray Computed Observer Variation Female Humans Reproducibility of Results Software Aged
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Using Artificial Intelligence to Predict Surgical Shunts in Men with Ischemic Priapism.

The Journal of urology Jun 9, 2020
PURPOSE: Ischemic priapism is a urological emergency that requires prompt intervention to preserve erectile function. Characteristics that influence escalation to surgical intervention remain unclear. We identified factors and developed machine learn...
Middle Aged Risk Assessment Adolescent Time Factors Treatment Outcome Models, Statistical Aged Aged, 80 and over Young Adult Adult Male Penis Likelihood Functions Penile Erection Emergency Treatment Priapism Urologic Surgical Procedures, Male Emergency Service, Hospital Humans Anastomosis, Surgical Machine Learning Phenylephrine Retrospective Studies Paracentesis Erectile Dysfunction
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Added Value of Intraoperative Data for Predicting Postoperative Complications: The MySurgeryRisk PostOp Extension.

The Journal of surgical research Jun 9, 2020
BACKGROUND: Models that predict postoperative complications often ignore important intraoperative events and physiological changes. This study tested the hypothesis that accuracy, discrimination, and precision in predicting postoperative complication...
Female Humans Male Middle Aged Machine Learning Forecasting Postoperative Complications Retrospective Studies Hospital Mortality Models, Statistical
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Modest Clostridiodes difficile infection prediction using machine learning models in a tertiary care hospital.

Diagnostic microbiology and infectious disease Jun 8, 2020
Previous studies have shown promising results of machine learning (ML) models for predicting health outcomes. We develop and test ML models for predicting Clostridioides difficile infection (CDI) in hospitalized patients. This is a retrospective coho...
Clostridioides difficile Logistic Models Area Under Curve Bayes Theorem Tertiary Care Centers Clostridium Infections Female Humans Aged Machine Learning Male Forecasting Middle Aged Anti-Bacterial Agents Diarrhea Retrospective Studies ROC Curve
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A novel model for predicting the outcome of intracerebral hemorrhage: Based on 1186 Patients.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Jun 8, 2020
OBJECTIVE: To establish a model for predicting the outcome according to the clinical and computed tomography(CT) image data of patients with intracerebral hemorrhage(ICH).
Time Factors Nomograms Support Vector Machine Cerebral Hemorrhage Predictive Value of Tests Risk Factors Male Humans Middle Aged Decision Support Techniques Risk Assessment Prognosis China Retrospective Studies Tomography, X-Ray Computed Female
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Using machine learning models to predict the initiation of renal replacement therapy among chronic kidney disease patients.

PloS one Jun 5, 2020
Starting renal replacement therapy (RRT) for patients with chronic kidney disease (CKD) at an optimal time, either with hemodialysis or kidney transplantation, is crucial for patient's well-being and for successful management of the condition. In thi...
Renal Insufficiency, Chronic Disease Progression Humans Taiwan Comorbidity Severity of Illness Index Models, Biological Machine Learning Time Factors Datasets as Topic Retrospective Studies ROC Curve Time-to-Treatment Renal Replacement Therapy Clinical Decision-Making
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