Artificial intelligence in colorectal cancer screening, diagnosis and treatment. A new era

A Mitsala, C Tsalikidis, M Pitiakoudis, C Simopoulos… - Current …, 2021 - mdpi.com
The development of artificial intelligence (AI) algorithms has permeated the medical field
with great success. The widespread use of AI technology in diagnosing and treating several …

[HTML][HTML] Endoscopic diagnosis and treatment of gastric dysplasia and early cancer: Current evidence and what the future may hold

E Young, H Philpott, R Singh - World Journal of Gastroenterology, 2021 - ncbi.nlm.nih.gov
Gastric cancer accounts for a significant proportion of worldwide cancer-related morbidity
and mortality. The well documented precancerous cascade provides an opportunity for …

[PDF][PDF] Artificial intelligence in digital marketing influences consumer behaviour: a review and theoretical foundation for future research

F Rabby, R Chimhundu, R Hassan - Academy of marketing studies …, 2021 - academia.edu
Tracking the customer journey has become more challenging because of the changing
marketing environment. The market is getting bigger and better, with digital markets offering …

Artificial intelligence in capsule endoscopy: A practical guide to its past and future challenges

SH Kim, YJ Lim - Diagnostics, 2021 - mdpi.com
Artificial intelligence (AI) has revolutionized the medical diagnostic process of various
diseases. Since the manual reading of capsule endoscopy videos is a time-intensive, error …

Predicting colorectal cancer occurrence in IBD

M Yalchin, AM Baker, TA Graham, A Hart - Cancers, 2021 - mdpi.com
Simple Summary Patients with inflammatory bowel disease are at an increased risk of
developing colorectal cancer, and so are enrolled in a surveillance colonoscopy programme …

Deep learning-based clinical decision support system for gastric neoplasms in real-time endoscopy: development and validation study

EJ Gong, CS Bang, JJ Lee, GH Baik, H Lim… - …, 2023 - thieme-connect.com
Background Deep learning models have previously been established to predict the
histopathology and invasion depth of gastric lesions using endoscopic images. This study …

Assessing the risk of dengue severity using demographic information and laboratory test results with machine learning

SW Huang, HP Tsai, SJ Hung, WC Ko… - PLoS neglected tropical …, 2020 - journals.plos.org
Background Dengue virus causes a wide spectrum of disease, which ranges from
subclinical disease to severe dengue shock syndrome. However, estimating the risk of …

Role of artificial intelligence in video capsule endoscopy

I Tziortziotis, FM Laskaratos, S Coda - Diagnostics, 2021 - mdpi.com
Capsule endoscopy (CE) has been increasingly utilised in recent years as a minimally
invasive tool to investigate the whole gastrointestinal (GI) tract and a range of capsules are …

Artificial intelligence for colonoscopy: past, present, and future

W Tavanapong, JH Oh, MA Riegler… - IEEE journal of …, 2022 - ieeexplore.ieee.org
During the past decades, many automated image analysis methods have been developed
for colonoscopy. Real-time implementation of the most promising methods during …

Prediction of submucosal invasion for gastric neoplasms in endoscopic images using deep-learning

BJ Cho, CS Bang, JJ Lee, CW Seo, JH Kim - Journal of Clinical Medicine, 2020 - mdpi.com
Endoscopic resection is recommended for gastric neoplasms confined to mucosa or
superficial submucosa. The determination of invasion depth is based on gross morphology …