OBJECTIVES: This study was conducted to evaluate the effect of dose reduction on the performance of a deep learning (DL)-based computer-aided diagnosis (CAD) system regarding pulmonary nodule detection in a virtual screening scenario.
PURPOSE: The aim of this study was to evaluate whether a novel head and neck artificial intelligence (AI)-assisted diagnostic system based on a three-dimensional convolutional neural network (3D-CNN) could improve the accuracy, efficiency and working...
We developed and validated a deep learning (DL)-based model using the segmentation method and assessed its ability to detect lung cancer on chest radiographs. Chest radiographs for use as a training dataset and a test dataset were collected separatel...
Analytical and bioanalytical chemistry
Jan 13, 2022
A photonic crystal fiber (PCF)-based fluorescence sensor is developed for rapid and sensitive detection of lactic acid (LA) enantiomers in serum samples. The sensor is fabricated by chemical binding dual enzymes on the inner surface of the PCF with n...
Endometriosis-a systemic and chronic condition occurring in women of childbearing age-is a highly enigmatic disease with unresolved questions. While multiple biomarkers, genomic analysis, questionnaires, and imaging techniques have been advocated as ...
In diabetic retinopathy (DR), the early signs that may lead the eyesight towards complete vision loss are considered as microaneurysms (MAs). The shape of these MAs is almost circular, and they have a darkish color and are tiny in size, which means t...
OBJECTIVES: To evaluate the clinical impact of a deep learning system (DLS) for automated detection of pulmonary nodules on computed tomography (CT) images as a second reader.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jan 6, 2022
OBJECTIVE: To develop an adaptive framework for seizure detection in real-time that is practical to use in the Epilepsy Monitoring Unit (EMU) as a warning signal, and whose output helps characterize epileptiform activity.
OBJECTIVE: To develop and evaluate a deep learning-based artificial intelligence (AI) model for detecting skull fractures on plain radiographs in children.
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