AIMC Topic: Sensitivity and Specificity
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Reply: Deep Learning on Bone Scintigraphy.
JACC. Cardiovascular imaging
Aug 1, 2023
Deep Learning on Bone Scintigraphy.
JACC. Cardiovascular imaging
Aug 1, 2023
Feature extraction of time series data on functional near-infrared spectroscopy and comparison of deep learning performance for classifying patients with Alzheimer's-related mild cognitive impairment: a post-hoc analysis of a diagnostic interventional trial.
European review for medical and pharmacological sciences
Jul 1, 2023
OBJECTIVE: This study aimed to define a method of classifying patients with mild cognitive impairment caused by Alzheimer's disease by the retrieval of functional near-infrared spectroscopy (fNIRS) signal characteristics obtained during olfactory sti...
A deep learning system for quantitative assessment of microvascular abnormalities in nailfold capillary images.
Rheumatology (Oxford, England)
Jun 1, 2023
OBJECTIVES: Nailfold capillaroscopy is key to timely diagnosis of SSc, but is often not used in rheumatology clinics because the images are difficult to interpret. We aimed to develop and validate a fully automated image analysis system to fill this ...
The rise of artificial intelligence reading of chest X-rays for enhanced TB diagnosis and elimination.
The international journal of tuberculosis and lung disease : the official journal of the International Union against Tuberculosis and Lung Disease
May 1, 2023
We provide an overview of the latest evidence on computer-aided detection (CAD) software for automated interpretation of chest radiographs (CXRs) for TB detection. CAD is a useful tool that can assist in rapid and consistent CXR interpretation for TB...
Use of artificial intelligence for cancer clinical trial enrollment: a systematic review and meta-analysis.
Journal of the National Cancer Institute
Apr 11, 2023
BACKGROUND: The aim of this study is to provide a comprehensive understanding of the current landscape of artificial intelligence (AI) for cancer clinical trial enrollment and its predictive accuracy in identifying eligible patients for inclusion in ...
Effects of Expert-Determined Reference Standards in Evaluating the Diagnostic Performance of a Deep Learning Model: A Malignant Lung Nodule Detection Task on Chest Radiographs.
Korean journal of radiology
Feb 1, 2023
OBJECTIVE: Little is known about the effects of using different expert-determined reference standards when evaluating the performance of deep learning-based automatic detection (DLAD) models and their added value to radiologists. We assessed the conc...
A Self-Interpretable Deep Learning Model for Seizure Prediction Using a Multi-Scale Prototypical Part Network.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jan 1, 2023
The epileptic seizure prediction (ESP) method aims to timely forecast the occurrence of seizures, which is crucial to improving patients' quality of life. Many deep learning-based methods have been developed to tackle this issue and achieve significa...
A deep learning-based method for cervical transformation zone classification in colposcopy images.
Technology and health care : official journal of the European Society for Engineering and Medicine
Jan 1, 2023
BACKGROUND: Colposcopy is one of the common methods of cervical cancer screening. The type of cervical transformation zone is considered one of the important factors for grading colposcopic findings and choosing treatment.
Diagnostic performance of corona virus disease 2019 chest computer tomography image recognition based on deep learning: Systematic review and meta-analysis.
Medicine
Oct 21, 2022
BACKGROUND: To analyze the diagnosis performance of deep learning model used in corona virus disease 2019 (COVID-19) computer tomography(CT) chest scans. The included sample contains healthy people, confirmed COVID-19 patients and unconfirmed suspect...
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