Journal of clinical laboratory analysis
Nov 22, 2021
BACKGROUND AND AIM: Gastrointestinal endoscopy and biopsy-based pathological findings are needed to diagnose early gastric cancer. However, the information of biopsy specimen is limited because of the topical procedure; therefore, pathology doctors s...
Corneal opacities are important causes of blindness, and their major etiology is infectious keratitis. Slit-lamp examinations are commonly used to determine the causative pathogen; however, their diagnostic accuracy is low even for experienced ophtha...
An accurate assessment of preoperative risk may improve use of hospital resources and reduce morbidity and mortality in high-risk surgical patients. This study aims at implementing an automated surgical risk calculator based on Artificial Neural Netw...
The COVID-19 pandemic continues to impact people worldwide-steadily depleting scarce resources in healthcare. Medical Artificial Intelligence (AI) promises a much-needed relief but only if the technology gets adopted at scale. The present research in...
BACKGROUND: Minimally invasive liver resection is gradually becoming the preferred technique to treat liver tumors due its salutary benefits when compared with traditional "open" method. While robotic technology improves surgeon dexterity to better p...
OBJECTIVE: We evaluated the impact of the duration between the biopsy and surgery on the biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP).
Diagnostic and interventional imaging
Nov 19, 2021
PURPOSE: The purpose of this study was to conduct an external validation of a fracture assessment deep learning algorithm (Rayvolve®) using digital radiographs from a real-life cohort of children presenting routinely to the emergency room.
Malformations of cortical development (MCD) comprise a broad spectrum of structural brain lesions frequently associated with epilepsy. Disease definition and diagnosis remain challenging and are often prone to arbitrary judgment. Molecular classifica...
In recent years, 2D convolutional neural networks (CNNs) have been extensively used to diagnose neurological diseases from magnetic resonance imaging (MRI) data due to their potential to discern subtle and intricate patterns. Despite the high perform...
Chronic disease prediction is a critical task in healthcare. Existing studies fulfil this requirement by employing machine learning techniques based on patient features, but they suffer from high dimensional data problems and a high level of bias. We...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.