AIMC Topic: Biopsy
Clear Filters Showing 181 to 190 of 441 articles
Deep neural network for video colonoscopy of ulcerative colitis: a cross-sectional study.
The lancet. Gastroenterology & hepatology
Nov 29, 2021
BACKGROUND: A combination of endoscopic and histological evaluation is important in the management of patients with ulcerative colitis. We aimed to adapt our previous deep neural network system (deep neural ulcerative colitis [DNUC]) to full video co...
Optical Biopsy Using a Neural Network to Predict Gene Expression From Photos of Wounds.
The Journal of surgical research
Nov 23, 2021
BACKGROUND: The clinical characterization of the biological status of complex wounds remains a considerable challenge. Digital photography provides a non-invasive means of obtaining wound information and is currently employed to assess wounds qualita...
Classification of renal biopsy direct immunofluorescence image using multiple attention convolutional neural network.
Computer methods and programs in biomedicine
Nov 21, 2021
BACKGROUND AND OBJECTIVES: Direct immunofluorescence (DIF) is an important medical evaluation tool for renal pathology. In the DIF images, the deposition appearances and locations of immunoglobulin on glomeruli involve immunological characteristics o...
Influence of the time interval between biopsy and surgery on the biochemical recurrence after robot-assisted radical prostatectomy in Japanese patients.
Asian journal of surgery
Nov 19, 2021
OBJECTIVE: We evaluated the impact of the duration between the biopsy and surgery on the biochemical recurrence (BCR) after robot-assisted radical prostatectomy (RARP).
Automated Whole-Liver MRI Segmentation to Assess Steatosis and Iron Quantification in Chronic Liver Disease.
Radiology
Nov 16, 2021
Background Standardized manual region of interest (ROI) sampling strategies for hepatic MRI steatosis and iron quantification are time consuming, with variable results. Purpose To evaluate the performance of automatic MRI whole-liver segmentation (WL...
Supervised learning based on tumor imaging and biopsy transcriptomics predicts response of hepatocellular carcinoma to transarterial chemoembolization.
Cell reports. Medicine
Nov 16, 2021
Although transarterial chemoembolization (TACE) is the most widely used treatment for intermediate-stage, unresectable hepatocellular carcinoma (HCC), it is only effective in a subset of patients. In this study, we combine clinical, radiological, and...
Deep learning-based classification of kidney transplant pathology: a retrospective, multicentre, proof-of-concept study.
The Lancet. Digital health
Nov 15, 2021
BACKGROUND: Histopathological assessment of transplant biopsies is currently the standard method to diagnose allograft rejection and can help guide patient management, but it is one of the most challenging areas of pathology, requiring considerable e...
Using deep learning for quantification of cellularity and cell lineages in bone marrow biopsies and comparison to normal age-related variation.
Pathology
Nov 10, 2021
Cellularity estimation forms an important aspect of the visual examination of bone marrow biopsies. In clinical practice, cellularity is estimated by eye under a microscope, which is rapid, but subjective and subject to inter- and intraobserver varia...
A neural network for glomerulus classification based on histological images of kidney biopsy.
BMC medical informatics and decision making
Nov 1, 2021
BACKGROUND: Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results....
Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies.
Kidney international
Oct 30, 2021
Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft failure. Here we sought an objective, quantitative pathological assessment of these lesions to improve predictive utility and constructed a deep-learn...
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