BACKGROUND: This study aimed to establish and validate a machine learning-based model for the prediction of early phase postoperative hypertension (EPOH) requiring the administration of intravenous vasodilators after carotid endarterectomy (CEA).
BACKGROUND: Traditional methods for cardiopulmonary assessment of patients with coronavirus disease 2019 (COVID-19) pose risks to both patients and examiners. This necessitates a remote examination of such patients without sacrificing information qua...
Computer methods and programs in biomedicine
Jul 9, 2020
BACKGROUND AND OBJECTIVE: Recently, deep convolutional neural network has significantly improved image classification and image segmentation. If coronary artery disease (CAD) can be diagnosed through machine learning and deep learning, it will signif...
BACKGROUND: Shunt-dependent hydrocephalus significantly complicates subarachnoid hemorrhage (SAH), and reliable prognosis methods have been sought in recent years to reduce morbidity and costs associated with delayed treatment or neglected onset. Mac...
PURPOSE: To (1) develop a deep learning system (DLS) using a deep convolutional neural network (DCNN) for identification of pneumothorax, (2) compare its performance to first-year radiology residents, and (3) evaluate the ability of a DLS to augment ...
Veterinary journal (London, England : 1997)
Jul 7, 2020
The purpose of this study was to develop a computer-aided detection (CAD) device based on convolutional neural networks (CNNs) to detect cardiomegaly from plain radiographs in dogs. Right lateral chest radiographs (n = 1465) were retrospectively sele...
The international journal of medical robotics + computer assisted surgery : MRCAS
Jul 6, 2020
BACKGROUND: Interstitial brachytherapy (BT) is becoming an accepted treatment option for head and neck cancer patients for whom surgery poses high risks. Multimodal, image-guided, robotic surgery has the potential to allow precise seed implantation i...
OBJECTIVES: We investigated the usefulness of machine learning artificial intelligence (AI) in classifying the severity of ophthalmic emergency for timely hospital visits.
BACKGROUND: In the era of efficient value-based health care, each surgical innovation should be proven to be cost-effective for the patient and the hospital administration.
International journal of radiation oncology, biology, physics
Jul 4, 2020
PURPOSE: To investigate machine segmentation of pelvic anatomy in magnetic resonance imaging (MRI)-assisted radiosurgery (MARS) for prostate cancer using prostate brachytherapy MRIs acquired with different pulse sequences and image contrasts.
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