AI Medical Compendium Topic

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Developing a Neural Network Model for a Non-invasive Prediction of Histologic Activity in Inflammatory Bowel Diseases.

The Turkish journal of gastroenterology : the official journal of Turkish Society of Gastroenterology
BACKGROUND: Colonoscopy with biopsy is the "gold" standard for evaluating disease activity in inflammatory bowel diseases (IBD). Current research is geared toward finding non-invasive, cost-efficient methods that estimate disease activity. We aimed t...

Fast and accurate automated recognition of the dominant cells from fecal images based on Faster R-CNN.

Scientific reports
Fecal samples can easily be collected and are representative of a person's current health state; therefore, the demand for routine fecal examination has increased sharply. However, manual operation may pollute the samples, and low efficiency limits t...

Combining deep learning and fluorescence imaging to automatically identify fecal contamination on meat carcasses.

Scientific reports
Food safety and foodborne diseases are significant global public health concerns. Meat and poultry carcasses can be contaminated by pathogens like E. coli and salmonella, by contact with animal fecal matter and ingesta during slaughter and processing...

[Development of the use of artificial intelligence in the management of chronic inflammatory bowel disease].

Annales de pathologie
Complexity of inflammatory bowel diseases (IBD) lies on their management and their biology. Clinics, blood and fecal samples tests, endoscopy and histology are the main tools guiding IBD treatment, but they generate a large amount of data, difficult ...

Generation and application of a convolutional neural networks algorithm in evaluating stool consistency in diapers.

Acta paediatrica (Oslo, Norway : 1992)
AIM: The aim of the study was to develop a deep convolutional neural networks (CNNs) algorithm for automated assessment of stool consistency from diaper photographs and test its performance under real-world conditions.

Artificial Intelligence Evaluation of Stool Quality Guides Management of Hepatic Encephalopathy Using a Smartphone App.

The American journal of gastroenterology
Lactulose-based hepatic encephalopathy treatment requires bowel movements/day titration, which is improved with Bristol stool scale (BSS) incorporation. Dieta app evaluates artificial intelligence (AI)-based BSS (AI-BSS) with stool images. Initially,...

Development of fecal microbial diagnostic marker sets of colorectal cancer using natural language processing method.

The International journal of biological markers
BACKGROUND: Cancer screening and early detection greatly increase the chances of successful treatment. However, most cancer types lack effective early screening biomarkers. In recent years, natural language processing (NLP)-based text-mining methods ...

Artificial Intelligence-Enabled Stool Analysis for Lactulose Titration Assistance in Hepatic Encephalopathy Through a Smartphone Application.

The American journal of gastroenterology
INTRODUCTION: Management of hepatic encephalopathy relies on self-titration of lactulose. In this feasibility trial, we assess an artificial intelligence-enabled tool to guide lactulose use through a smartphone application.

Identification of KRAS mutation-associated gut microbiota in colorectal cancer and construction of predictive machine learning model.

Microbiology spectrum
Gut microbiota has demonstrated an increasingly important role in the onset and development of colorectal cancer (CRC). Nonetheless, the association between gut microbiota and KRAS mutation in CRC remains enigmatic. We conducted 16S rRNA sequencing o...