Differentiation between Crohn's disease and intestinal tuberculosis is difficult but crucial for medical decisions. This study aims to develop an effective framework to distinguish these two diseases through an explainable machine learning (ML) model...
Computational and mathematical methods in medicine
Feb 2, 2022
This research was aimed at exploring the application value of coronary angiography (CAG) based on a convolutional neural network algorithm in analyzing the distribution characteristics of ST-segment elevation myocardial infarction (STEMI) and non-ST-...
Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted ...
Spirometers are important devices for following up patients with respiratory diseases. These are mainly located only at hospitals, with all the disadvantages that this can entail. This limits their use and consequently, the supervision of patients. R...
BACKGROUND: Fungal spondylodiscitis is a rare infectious disease. The secondary lumbar spinal stenosis and postoperative discal pseudocyst were even rarer. The surgical interventions were disputed, yet endoscopic and robot-assisted techniques may be ...
Computational and mathematical methods in medicine
Jan 29, 2022
METHODS: We compare nine index values, select CNN+EEG, which has good correlation with BIS index, as an anesthesia state observation index to identify the parameters of the model, and establish a model based on self-attention and dual resistructure c...
AIMS: To apply a deep learning model for automatic localisation of the scleral spur (SS) in anterior segment optical coherence tomography (AS-OCT) images and compare the reproducibility of anterior chamber angle (ACA) width between deep learning loca...
Using deep learning models to analyze patients with intracranial tumors, to study the image segmentation and standard results by clinical depiction complications of cerebral edema after receiving radiotherapy. In this study, patients with intracrania...
OBJECTIVE: To evaluate the image quality and lesion detectability of lower-dose CT (LDCT) of the abdomen and pelvis obtained using a deep learning image reconstruction (DLIR) algorithm compared with those of standard-dose CT (SDCT) images.
PURPOSE: Targeted treatment for brainstem lesions requires above all a precise histopathological and molecular diagnosis. In the current technological era, robot-assisted stereotactic biopsies represent an accurate and safe procedure for tissue diagn...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.