AIMC Topic: ROC Curve

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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.
Image-Guided Biopsy Unnecessary Procedures Multiparametric Magnetic Resonance Imaging Radiography Prostatic Neoplasms Prostate-Specific Antigen Prostate Validation Studies as Topic Aged Aged, 80 and over Male Middle Aged Ultrasonography ROC Curve Logistic Models Support Vector Machine Decision Trees Area Under Curve Humans Machine Learning Retrospective Studies Reproducibility of Results
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The value of artificial neural networks for predicting length of stay, discharge disposition, and inpatient costs after anatomic and reverse shoulder arthroplasty.

Journal of shoulder and elbow surgery Jun 9, 2020
HYPOTHESIS/PURPOSE: The objective is to develop and validate an artificial intelligence model, specifically an artificial neural network (ANN), to predict length of stay (LOS), discharge disposition, and inpatient charges for primary anatomic total (...
Female Reproducibility of Results Aged Aged, 80 and over Male Humans Neural Networks, Computer Machine Learning Forecasting Databases, Factual Hemiarthroplasty Shoulder Injuries Patient Discharge Osteoarthritis Hospital Costs Hospital Charges Arthroplasty, Replacement, Shoulder Middle Aged Postoperative Complications Length of Stay ROC Curve 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 Machine Learning Forecasting Anti-Bacterial Agents Retrospective Studies Female Aged Male Middle Aged Diarrhea ROC Curve Humans
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An improved clear cell renal cell carcinoma stage prediction model based on gene sets.

BMC bioinformatics Jun 8, 2020
BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is the most common subtype of renal cell carcinoma and accounts for cancer-related deaths. Survival rates are very low when the tumor is discovered in the late-stage. Thus, developing an efficient s...
Humans Machine Learning RNA Kidney Neoplasms Carcinoma, Renal Cell Female ROC Curve Logistic Models Area Under Curve Neoplasm Staging
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Prospective Analysis Using a Novel CNN Algorithm to Distinguish Atypical Ductal Hyperplasia From Ductal Carcinoma in Situ in Breast.

Clinical breast cancer Jun 7, 2020
INTRODUCTION: We previously developed a convolutional neural networks (CNN)-based algorithm to distinguish atypical ductal hyperplasia (ADH) from ductal carcinoma in situ (DCIS) using a mammographic dataset. The purpose of this study is to further va...
Humans Neural Networks, Computer Prospective Studies Female Aged Adult Breast Neoplasms Middle Aged Carcinoma, Intraductal, Noninfiltrating Datasets as Topic Hyperplasia Mammary Glands, Human ROC Curve Mammography Diagnosis, Differential Biopsy Radiographic Image Interpretation, Computer-Assisted
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Matrix factorization with neural network for predicting circRNA-RBP interactions.

BMC bioinformatics Jun 5, 2020
BACKGROUND: Circular RNA (circRNA) has been extensively identified in cells and tissues, and plays crucial roles in human diseases and biological processes. circRNA could act as dynamic scaffolding molecules that modulate protein-protein interactions...
Humans Neural Networks, Computer Area Under Curve RNA, Circular Databases, Factual Neoplasms Cell Line, Tumor ROC Curve RNA-Binding Proteins
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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 Taiwan Models, Biological Datasets as Topic Time-to-Treatment Disease Progression Comorbidity Severity of Illness Index Time Factors Humans ROC Curve Machine Learning Retrospective Studies Renal Replacement Therapy Clinical Decision-Making
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Identification of feature risk pathways of smoking-induced lung cancer based on SVM.

PloS one Jun 4, 2020
OBJECTIVE: The present study aims to explore the role of smoking factors in the risk of lung cancer and screen the feature risk pathways of smoking-induced lung cancer.
High-Throughput Nucleotide Sequencing Humans Smoking Risk Factors DNA, Neoplasm Gene Expression Profiling Gene Ontology ROC Curve Protein Interaction Mapping Lung Neoplasms Signal Transduction Support Vector Machine Databases, Genetic Cluster Analysis Area Under Curve
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Machine-learning based MRI radiomics models for early detection of radiation-induced brain injury in nasopharyngeal carcinoma.

BMC cancer Jun 1, 2020
BACKGROUND: Early radiation-induced temporal lobe injury (RTLI) diagnosis in nasopharyngeal carcinoma (NPC) is clinically challenging, and prediction models of RTLI are lacking. Hence, we aimed to develop radiomic models for early detection of RTLI.
Nasopharyngeal Neoplasms Temporal Lobe Aftercare Models, Biological Image Interpretation, Computer-Assisted Radiation Injuries Nasopharyngeal Carcinoma Humans Machine Learning Algorithms ROC Curve Longitudinal Studies Magnetic Resonance Imaging Brain Injuries Predictive Value of Tests Retrospective Studies Female Adult Male Middle Aged
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CRISPRpred(SEQ): a sequence-based method for sgRNA on target activity prediction using traditional machine learning.

BMC bioinformatics Jun 1, 2020
BACKGROUND: The latest works on CRISPR genome editing tools mainly employs deep learning techniques. However, deep learning models lack explainability and they are harder to reproduce. We were motivated to build an accurate genome editing tool using ...
Humans Machine Learning Algorithms Reproducibility of Results Deep Learning ROC Curve Databases, Genetic Area Under Curve CRISPR-Cas Systems HEK293 Cells Base Sequence Gene Editing RNA, Guide, CRISPR-Cas Systems
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