AIMC Topic: Sensitivity and Specificity
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Predicting youth diabetes risk using NHANES data and machine learning.
Scientific reports
May 27, 2021
Prediabetes and diabetes mellitus (preDM/DM) have become alarmingly prevalent among youth in recent years. However, simple questionnaire-based screening tools to reliably assess diabetes risk are only available for adults, not youth. As a first step ...
COVID-19 diagnosis by routine blood tests using machine learning.
Scientific reports
May 24, 2021
Physicians taking care of patients with COVID-19 have described different changes in routine blood parameters. However, these changes hinder them from performing COVID-19 diagnoses. We constructed a machine learning model for COVID-19 diagnosis that ...
Performance and reading time of lung nodule identification on multidetector CT with or without an artificial intelligence-powered computer-aided detection system.
Clinical radiology
May 19, 2021
AIM: To compare the performance and reading time of different readers using automatic artificial intelligence (AI)-powered computer-aided detection (CAD) to detect lung nodules in different reading modes.
Specificity of SARS-CoV-2 Real-Time PCR Improved by Deep Learning Analysis.
Journal of clinical microbiology
May 19, 2021
Real-time PCR (RT-PCR) is widely used to diagnose human pathogens. RT-PCR data are traditionally analyzed by estimating the threshold cycle ( ) at which the fluorescence signal produced by emission of a probe crosses a baseline level. Current models ...
Automatic Detection of Thyroid and Adrenal Incidentals Using Radiology Reports and Deep Learning.
The Journal of surgical research
May 18, 2021
BACKGROUND: Computed tomography (CT) is commonly performed when evaluating trauma patients with up to 55% showing incidental findings. Current workflows to identify and inform patients are time-consuming and prone to error. Our objective was to autom...
A deep learning model for detection of cervical spinal cord compression in MRI scans.
Scientific reports
May 18, 2021
Magnetic Resonance Imaging (MRI) evidence of spinal cord compression plays a central role in the diagnosis of degenerative cervical myelopathy (DCM). There is growing recognition that deep learning models may assist in addressing the increasing volum...
Predicting nodal metastases in papillary thyroid carcinoma using artificial intelligence.
American journal of surgery
May 13, 2021
BACKGROUND: The presence of nodal metastases is important in the treatment of papillary thyroid carcinoma (PTC). We present our experience using a convolutional neural network (CNN) to predict the presence of nodal metastases in a series of PTC patie...
Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.
Clinical radiology
May 11, 2021
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...
ai-corona: Radiologist-assistant deep learning framework for COVID-19 diagnosis in chest CT scans.
PloS one
May 7, 2021
The development of medical assisting tools based on artificial intelligence advances is essential in the global fight against COVID-19 outbreak and the future of medical systems. In this study, we introduce ai-corona, a radiologist-assistant deep lea...
Understanding inherent image features in CNN-based assessment of diabetic retinopathy.
Scientific reports
May 6, 2021
Diabetic retinopathy (DR) is a leading cause of blindness and affects millions of people throughout the world. Early detection and timely checkups are key to reduce the risk of blindness. Automated grading of DR is a cost-effective way to ensure earl...
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