Smart Endoscopy Is Greener Endoscopy: Leveraging Artificial Intelligence and Blockchain Technologies to Drive Sustainability in Digestive Health Care

Author:

Mascarenhas Miguel123ORCID,Ribeiro Tiago23,Afonso João23,Mendes Francisco23ORCID,Cardoso Pedro23ORCID,Martins Miguel23ORCID,Ferreira João4,Macedo Guilherme123ORCID

Affiliation:

1. Faculty of Medicine, University of Porto, 4200-319 Porto, Portugal

2. Precision Medicine Unit, Department of Gastroenterology, Hospital São João, 4200-437 Porto, Portugal

3. WGO Training Center, 4200-437 Porto, Portugal

4. Faculty of Engineering, University of Porto, 4200-465 Porto, Portugal

Abstract

The surge in the implementation of artificial intelligence (AI) in recent years has permeated many aspects of our life, and health care is no exception. Whereas this technology can offer clear benefits, some of the problems associated with its use have also been recognised and brought into question, for example, its environmental impact. In a similar fashion, health care also has a significant environmental impact, and it requires a considerable source of greenhouse gases. Whereas efforts are being made to reduce the footprint of AI tools, here, we were specifically interested in how employing AI tools in gastroenterology departments, and in particular in conjunction with capsule endoscopy, can reduce the carbon footprint associated with digestive health care while offering improvements, particularly in terms of diagnostic accuracy. We address the different ways that leveraging AI applications can reduce the carbon footprint associated with all types of capsule endoscopy examinations. Moreover, we contemplate how the incorporation of other technologies, such as blockchain technology, into digestive health care can help ensure the sustainability of this clinical speciality and by extension, health care in general.

Publisher

MDPI AG

Subject

Clinical Biochemistry

Reference97 articles.

1. (2023, August 31). Artificial Intelligence (AI) in Healthcare Market Size, Growth Report Analysis 2031. Available online: https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-healthcare-market-54679303.html.

2. Artificial Intelligence-Supported Screen Reading versus Standard Double Reading in the Mammography Screening with Artificial Intelligence Trial (MASAI): A Clinical Safety Analysis of a Randomised, Controlled, Non-Inferiority, Single-Blinded, Screening Accuracy Study;Josefsson;Lancet Oncol.,2023

3. A Survey on Deep Learning in Medical Image Analysis;Litjens;Med. Image Anal.,2017

4. Machine Learning in Medical Imaging;Giger;J. Am. Coll. Radiol.,2018

5. Artificial Intelligence in Radiology;Hosny;Nat. Rev. Cancer,2018

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3