AIMC Topic: Biopsy

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A Machine Learning Approach Enables Quantitative Measurement of Liver Histology and Disease Monitoring in NASH.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Manual histological assessment is currently the accepted standard for diagnosing and monitoring disease progression in NASH, but is limited by variability in interpretation and insensitivity to change. Thus, there is a critical n...

Deep learning-based framework for the distinction of membranous nephropathy: a new approach through hyperspectral imagery.

BMC nephrology
BACKGROUND: Common subtypes seen in Chinese patients with membranous nephropathy (MN) include idiopathic membranous nephropathy (IMN) and hepatitis B virus-related membranous nephropathy (HBV-MN). However, the morphologic differences are not visible ...

Clinical characteristics and oncological outcomes in negative multiparametric MRI patients undergoing robot-assisted radical prostatectomy.

The Prostate
BACKGROUND: Efforts are ongoing to try and find ways to reduce the number of unnecessary prostate biopsies without missing clinically significant prostate cancers (csPCa). The utility of multiparametric magnetic resonance imaging (mpMRI) in detecting...

Deep-Learning-Driven Quantification of Interstitial Fibrosis in Digitized Kidney Biopsies.

The American journal of pathology
Interstitial fibrosis and tubular atrophy (IFTA) on a renal biopsy are strong indicators of disease chronicity and prognosis. Techniques that are typically used for IFTA grading remain manual, leading to variability among pathologists. Accurate IFTA ...

Artificial intelligence for advance requesting of immunohistochemistry in diagnostically uncertain prostate biopsies.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The use of immunohistochemistry in the reporting of prostate biopsies is an important adjunct when the diagnosis is not definite on haematoxylin and eosin (H&E) morphology alone. The process is however inherently inefficient with delays while waiting...

Quantitative assessment of inflammatory infiltrates in kidney transplant biopsies using multiplex tyramide signal amplification and deep learning.

Laboratory investigation; a journal of technical methods and pathology
Delayed graft function (DGF) is a strong risk factor for development of interstitial fibrosis and tubular atrophy (IFTA) in kidney transplants. Quantitative assessment of inflammatory infiltrates in kidney biopsies of DGF patients can reveal predicti...

Development and head-to-head comparison of machine-learning models to identify patients requiring prostate biopsy.

BMC urology
BACKGROUND: Machine learning has many attractive theoretic properties, specifically, the ability to handle non predefined relations. Additionally, studies have validated the clinical utility of mpMRI for the detection and localization of CSPCa (Gleas...

Validation of a machine learning approach using FIB-4 and APRI scores assessed by the metavir scoring system: A cohort study.

Arab journal of gastroenterology : the official publication of the Pan-Arab Association of Gastroenterology
BACKGROUND AND STUDY AIM: The study aim was to improve and validate the accuracy of the fibrosis-4 (FIB-4) and aspartate aminotransferase-to-platelet ratio index (APRI) scores for use in a potential machine-learning (ML) method that accurately predic...

Texture analysis of muscle MRI: machine learning-based classifications in idiopathic inflammatory myopathies.

Scientific reports
To develop a machine learning (ML) model that predicts disease groups or autoantibodies in patients with idiopathic inflammatory myopathies (IIMs) using muscle MRI radiomics features. Twenty-two patients with dermatomyositis (DM), 14 with amyopathic ...