AIMC Topic: Sensitivity and Specificity
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Development and validation of a difficult laryngoscopy prediction model using machine learning of neck circumference and thyromental height.
BMC anesthesiology
Apr 21, 2021
BACKGROUND: Predicting difficult airway is challengeable in patients with limited airway evaluation. The aim of this study is to develop and validate a model that predicts difficult laryngoscopy by machine learning of neck circumference and thyroment...
Classification of COVID-19 Chest CT Images Based on Ensemble Deep Learning.
Journal of healthcare engineering
Apr 20, 2021
Novel coronavirus pneumonia (NCP) has become a global pandemic disease, and computed tomography-based (CT) image analysis and recognition are one of the important tools for clinical diagnosis. In order to assist medical personnel to achieve an effici...
Application of deep learning to establish a diagnostic model of breast lesions using two-dimensional grayscale ultrasound imaging.
Clinical imaging
Apr 19, 2021
PURPOSE: There are currently few specific artificial intelligence (AI) studies for Breast Imaging Reporting and Data System (BI-RADS) category 4A lesions. This study aimed to establish an AI diagnostic model of breast lesions using two-dimensional gr...
Assessing the Outbreak Risk of Epidemics Using Fuzzy Evidential Reasoning.
Risk analysis : an official publication of the Society for Risk Analysis
Apr 17, 2021
Epidemic diseases (EDs) present a significant but challenging risk endangering public health, evidenced by the outbreak of COVID-19. Compared to other risks affecting public health such as flooding, EDs attract little attention in terms of risk asses...
Using rADioMIcs and machine learning with ultrasonography for the differential diagnosis of myometRiAL tumors (the ADMIRAL pilot study). Radiomics and differential diagnosis of myometrial tumors.
Gynecologic oncology
Apr 16, 2021
OBJECTIVE: To develop and evaluate the performance of a radiomics and machine learning model applied to ultrasound (US) images in predicting the risk of malignancy of a uterine mesenchymal lesion.
Deep learning assistance increases the detection sensitivity of radiologists for secondary intracranial aneurysms in subarachnoid hemorrhage.
Neuroradiology
Apr 10, 2021
PURPOSE: To evaluate whether a deep learning model (DLM) could increase the detection sensitivity of radiologists for intracranial aneurysms on CT angiography (CTA) in aneurysmal subarachnoid hemorrhage (aSAH).
Ability of artificial intelligence to detect T1 esophageal squamous cell carcinoma from endoscopic videos and the effects of real-time assistance.
Scientific reports
Apr 8, 2021
Diagnosis using artificial intelligence (AI) with deep learning could be useful in endoscopic examinations. We investigated the ability of AI to detect superficial esophageal squamous cell carcinoma (ESCC) from esophagogastroduodenoscopy (EGD) videos...
Machine Learning-Based Multiparametric Magnetic Resonance Imaging Radiomics for Prediction of H3K27M Mutation in Midline Gliomas.
World neurosurgery
Apr 2, 2021
OBJECTIVE: H3K27M mutation in gliomas has prognostic implications. Previous magnetic resonance imaging (MRI) studies have reported variable rates of tumoral enhancement, necrotic changes, and peritumoral edema in H3K27M-mutant gliomas, with no distin...
Male
Middle Aged
Adolescent
Cohort Studies
Young Adult
Adult
Sensitivity and Specificity
Brain Neoplasms
Magnetic Resonance Imaging
Child
Predictive Value of Tests
ROC Curve
Area Under Curve
Humans
Image Processing, Computer-Assisted
Mutation
Machine Learning
Glioma
Histones
Algorithms
Female
Reproducibility of Results
Ultra-high-frequency ultrasound and machine learning approaches for the differential diagnosis of melanocytic lesions.
Experimental dermatology
Mar 31, 2021
Malignant melanoma (MM) is one of the most dangerous skin cancers. The aim of this study was to present a potential new method for the differential diagnosis of MM from melanocytic naevi (MN). We examined 20 MM and 19 MN with a new ultra-high-frequen...
Automated system for diagnosing endometrial cancer by adopting deep-learning technology in hysteroscopy.
PloS one
Mar 31, 2021
Endometrial cancer is a ubiquitous gynecological disease with increasing global incidence. Therefore, despite the lack of an established screening technique to date, early diagnosis of endometrial cancer assumes critical importance. This paper presen...
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