AIMC Topic: ROC Curve

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Accuracy of deep learning for automated detection of pneumonia using chest X-Ray images: A systematic review and meta-analysis.

Computers in biology and medicine Jul 14, 2020
BACKGROUND: Recently, deep learning (DL) algorithms have received widespread popularity in various medical diagnostics. This study aimed to evaluate the diagnostic performance of DL models in the detection and classifying of pneumonia using chest X-r...
X-Rays Humans Deep Learning ROC Curve Pneumonia Thorax
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Machine Learning Based Radiomic HPV Phenotyping of Oropharyngeal SCC: A Feasibility Study Using MRI.

The Laryngoscope Jul 13, 2020
OBJECTIVES: To investigate whether a radiomic MRI feature-based prediction model can differentiate oropharyngeal squamous cell carcinoma (SCC) according to the human papillomavirus (HPV) status.
Humans Machine Learning Retrospective Studies Female Aged Squamous Cell Carcinoma of Head and Neck Magnetic Resonance Imaging Predictive Value of Tests Feasibility Studies Oropharyngeal Neoplasms Alphapapillomavirus Male Middle Aged ROC Curve Papillomavirus Infections Logistic Models
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A priori prediction of tumour response to neoadjuvant chemotherapy in breast cancer patients using quantitative CT and machine learning.

Scientific reports Jul 2, 2020
Response to Neoadjuvant chemotherapy (NAC) has demonstrated a high correlation to survival in locally advanced breast cancer (LABC) patients. An early prediction of responsiveness to NAC could facilitate treatment adjustments on an individual patient...
Aged Aged, 80 and over Young Adult Adult Breast Neoplasms Humans Machine Learning Prognosis Tomography, X-Ray Computed Female Middle Aged Follow-Up Studies Receptors, Estrogen Adolescent Receptor, ErbB-2 ROC Curve Receptors, Progesterone Carcinoma, Ductal, Breast Antineoplastic Combined Chemotherapy Protocols Carcinoma, Lobular Neoadjuvant Therapy
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Development of a Deep Learning Model to Identify Lymph Node Metastasis on Magnetic Resonance Imaging in Patients With Cervical Cancer.

JAMA network open Jul 1, 2020
IMPORTANCE: Accurate identification of lymph node metastasis preoperatively and noninvasively in patients with cervical cancer can avoid unnecessary surgical intervention and benefit treatment planning.
Adult Uterine Cervical Neoplasms Middle Aged Deep Learning Humans China Software Retrospective Studies Female ROC Curve Lymphatic Metastasis Magnetic Resonance Imaging Area Under Curve Program Development
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Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis.

European radiology Jun 30, 2020
OBJECTIVES: The aim of this study was to systematically review the literature and perform a meta-analysis of machine learning (ML) diagnostic accuracy studies focused on clinically significant prostate cancer (csPCa) identification on MRI.
Prostatectomy Machine Learning Magnetic Resonance Imaging Area Under Curve Algorithms Humans Prostatic Neoplasms Prevalence Male Diagnosis, Computer-Assisted Biopsy ROC Curve Reference Standards
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Machine Learning Prediction of Extracapsular Extension in Human Papillomavirus-Associated Oropharyngeal Squamous Cell Carcinoma.

Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery Jun 30, 2020
OBJECTIVE: To determine whether machine learning (ML) can predict the presence of extracapsular extension (ECE) prior to treatment, using common oncologic variables, in patients with human papillomavirus (HPV)-associated oropharyngeal squamous cell c...
Retrospective Studies Female Aged Male Middle Aged ROC Curve Papillomavirus Infections Logistic Models Squamous Cell Carcinoma of Head and Neck Oropharyngeal Neoplasms Humans Machine Learning Databases, Factual Prognosis Alphapapillomavirus Extranodal Extension
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Challenge for Diagnostic Assessment of Deep Learning Algorithm for Metastases Classification in Sentinel Lymph Nodes on Frozen Tissue Section Digital Slides in Women with Breast Cancer.

Cancer research and treatment Jun 30, 2020
PURPOSE: Assessing the status of metastasis in sentinel lymph nodes (SLNs) by pathologists is an essential task for the accurate staging of breast cancer. However, histopathological evaluation of SLNs by a pathologist is not easy and is a tedious and...
Deep Learning ROC Curve Image Processing, Computer-Assisted Lymphatic Metastasis Predictive Value of Tests Aged Frozen Sections Aged, 80 and over Humans Neoplasm Staging Adult Republic of Korea Sentinel Lymph Node Breast Neoplasms Female Middle Aged Sentinel Lymph Node Biopsy
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Machine learning prediction of combat basic training injury from 3D body shape images.

PloS one Jun 30, 2020
INTRODUCTION: Athletes and military personnel are both at risk of disabling injuries due to extreme physical activity. A method to predict which individuals might be more susceptible to injury would be valuable, especially in the military where basic...
ROC Curve Imaging, Three-Dimensional United States Humans Models, Statistical Military Personnel Risk Factors Machine Learning Physical Fitness Anthropometry Young Adult Female Physical Endurance Male Occupational Injuries Risk Assessment Adolescent
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Solitary solid pulmonary nodules: a CT-based deep learning nomogram helps differentiate tuberculosis granulomas from lung adenocarcinomas.

European radiology Jun 27, 2020
OBJECTIVES: To evaluate the differential diagnostic performance of a computed tomography (CT)-based deep learning nomogram (DLN) in identifying tuberculous granuloma (TBG) and lung adenocarcinoma (LAC) presenting as solitary solid pulmonary nodules (...
Diagnostic Tests, Routine Observer Variation Pattern Recognition, Automated Calibration Adenocarcinoma of Lung Lung Neoplasms Logistic Models Nomograms Age Factors Solitary Pulmonary Nodule Regression Analysis Diagnosis, Differential Granuloma Tuberculosis Sex Factors Middle Aged Diagnosis, Computer-Assisted Deep Learning ROC Curve Image Processing, Computer-Assisted Retrospective Studies Tomography, X-Ray Computed Female Adult Male Humans Algorithms
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An Artificial Intelligence Model for Predicting 1-Year Survival of Bone Metastases in Non-Small-Cell Lung Cancer Patients Based on XGBoost Algorithm.

BioMed research international Jun 27, 2020
Non-small-cell lung cancer (NSCLC) patients often develop bone metastases (BM), and the overall survival for these patients is usually perishing. However, a model with high accuracy for predicting the survival of NSCLC with BM is still lacking. Here,...
Logistic Models Nomograms Carcinoma, Non-Small-Cell Lung Bone Neoplasms Models, Biological Survival Analysis Humans Reproducibility of Results Multivariate Analysis Artificial Intelligence Aged Algorithms Male Prognosis ROC Curve Female Lung Neoplasms
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