AIMC Topic:
ROC Curve

Clear Filters Showing 1791 to 1800 of 3214 articles

Same same but different: A Web-based deep learning application revealed classifying features for the histopathologic distinction of cortical malformations.

Epilepsia Feb 20, 2020
OBJECTIVE: The microscopic review of hematoxylin-eosin-stained images of focal cortical dysplasia type IIb and cortical tuber of tuberous sclerosis complex remains challenging. Both entities are distinct subtypes of human malformations of cortical de...
ROC Curve Tuberous Sclerosis Humans Cerebral Cortex Neural Networks, Computer Area Under Curve Proof of Concept Study Algorithms Malformations of Cortical Development, Group I Epilepsy Reproducibility of Results Neuropathology Internet Diagnosis, Computer-Assisted Neurons Deep Learning
View on PubMed DOI

A Machine-learning Approach to Forecast Aggravation Risk in Patients with Acute Exacerbation of Chronic Obstructive Pulmonary Disease with Clinical Indicators.

Scientific reports Feb 20, 2020
Patients with chronic obstructive pulmonary disease (COPD) repeat acute exacerbations (AE). Global Initiative for Chronic Obstructive Lung Disease (GOLD) is only available for patients in stable phase. Currently, there is a lack of assessment and pre...
Disease Progression Comorbidity ROC Curve Decision Support Systems, Clinical Humans Inflammation Machine Learning Models, Statistical Algorithms Aged, 80 and over Decision Trees Prognosis False Positive Reactions Adult Risk Pulmonary Disease, Chronic Obstructive Female Male Reproducibility of Results Middle Aged Hospitalization Aged
View on PubMed DOI

Automatic detection and classification of protruding lesions in wireless capsule endoscopy images based on a deep convolutional neural network.

Gastrointestinal endoscopy Feb 19, 2020
BACKGROUND AND AIMS: Protruding lesions of the small bowel vary in wireless capsule endoscopy (WCE) images, and their automatic detection may be difficult. We aimed to develop and test a deep learning-based system to automatically detect protruding l...
Humans ROC Curve Capsule Endoscopy Neural Networks, Computer Intestine, Small Deep Learning
View on PubMed DOI

Monitoring stance towards vaccination in twitter messages.

BMC medical informatics and decision making Feb 18, 2020
BACKGROUND: We developed a system to automatically classify stance towards vaccination in Twitter messages, with a focus on messages with a negative stance. Such a system makes it possible to monitor the ongoing stream of messages on social media, of...
Humans Machine Learning Support Vector Machine ROC Curve Social Media Vaccination Data Collection Netherlands
View on PubMed DOI

Detecting Congestive Heart Failure by Extracting Multimodal Features and Employing Machine Learning Techniques.

BioMed research international Feb 18, 2020
The adaptability of heart to external and internal stimuli is reflected by the heart rate variability (HRV). Reduced HRV can be a predictor of negative cardiovascular outcomes. Based on the nonlinear, nonstationary, and highly complex dynamics of the...
Heart Rate Humans ROC Curve Machine Learning Algorithms Support Vector Machine Sensitivity and Specificity Models, Statistical Heart Failure
View on PubMed DOI

Application of deep learning to the diagnosis of cervical lymph node metastasis from thyroid cancer with CT: external validation and clinical utility for resident training.

European radiology Feb 17, 2020
PURPOSE: This study aimed to validate a deep learning model's diagnostic performance in using computed tomography (CT) to diagnose cervical lymph node metastasis (LNM) from thyroid cancer in a large clinical cohort and to evaluate the model's clinica...
Neck Lymphatic Metastasis Deep Learning Radiology Cohort Studies Humans Education, Medical, Graduate Multidetector Computed Tomography Thyroid Neoplasms Artificial Intelligence ROC Curve Internship and Residency Algorithms Lymph Nodes Diagnosis, Computer-Assisted
View on PubMed DOI

Prediction of bone mineral density from computed tomography: application of deep learning with a convolutional neural network.

European radiology Feb 14, 2020
OBJECTIVES: To investigate whether a deep learning model can predict the bone mineral density (BMD) of lumbar vertebrae from unenhanced abdominal computed tomography (CT) images.
ROC Curve Abdomen Area Under Curve Lumbar Vertebrae Absorptiometry, Photon Aged Adult Male Middle Aged Deep Learning Osteoporosis Tomography, X-Ray Computed Humans Female Reproducibility of Results Bone Density Retrospective Studies
View on PubMed DOI

CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.

European radiology Feb 13, 2020
OBJECTIVES: To evaluate the deep learning models for differentiating invasive pulmonary adenocarcinomas (IACs) among subsolid nodules (SSNs) considered for resection in a retrospective diagnostic cohort in comparison with a size-based logistic model ...
ROC Curve Lung Neoplasms Logistic Models Radiologists Radiography, Thoracic Aged Male Middle Aged Deep Learning Adenocarcinoma of Lung Humans Retrospective Studies Tomography, X-Ray Computed Female
View on PubMed DOI

Assessment of liver fibrosis severity using computed tomography-based liver and spleen volumetric indices in patients with chronic liver disease.

European radiology Feb 13, 2020
OBJECTIVES: To evaluate whether the liver and spleen volumetric indices, measured on portal venous phase CT images, could be used to assess liver fibrosis severity in chronic liver disease.
Female Adult Male Middle Aged Severity of Illness Index Humans Retrospective Studies Tomography, X-Ray Computed Liver Chronic Disease Case-Control Studies Organ Size Deep Learning Liver Diseases ROC Curve Spleen Liver Cirrhosis
View on PubMed DOI

Artificial intelligence for breast cancer detection in mammography: experience of use of the ScreenPoint Medical Transpara system in 310 Japanese women.

Breast cancer (Tokyo, Japan) Feb 12, 2020
BACKGROUND: To compare the breast cancer detection performance in digital mammograms of a panel of three unaided human readers (HR) versus a stand-alone artificial intelligence (AI)-based Transpara system in a population of Japanese women.
Aged, 80 and over Young Adult Adult Breast Neoplasms Middle Aged Artificial Intelligence Retrospective Studies Female Aged Humans ROC Curve Decision Support Systems, Clinical Early Detection of Cancer Mammography Radiologists Radiographic Image Interpretation, Computer-Assisted Breast Japan Reference Standards
View on PubMed DOI
Popular Topics
Recent Journals