scholarly journals Artificial Intelligence in Capsule Endoscopy: A Practical Guide to Its Past and Future Challenges

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1722
Author(s):  
Sang Hoon Kim ◽  
Yun Jeong Lim
Keyword(s):  
Artificial Intelligence ◽  
Capsule Endoscopy ◽  
Reading Time ◽  
Diagnostic Process ◽  
The Past ◽  
Computer Aided ◽  
Future Challenges ◽  
Medical Diagnostic ◽  
Reading System ◽  
Near Future

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-prone process, computerized algorithms have been introduced to automate this process. Over the past decade, the evolution of convolutional neural network (CNN) enabled AI to detect multiple lesions simultaneously with increasing accuracy and sensitivity. Difficulty in validating CNN performance and unique characteristics of capsule endoscopy images make computer-aided reading systems in capsule endoscopy still on a preclinical level. Although AI technology can be used as an auxiliary second observer in capsule endoscopy, it is expected that in the near future, it will effectively reduce the reading time and ultimately become an independent, integrated reading system.

scholarly journals PEACE: Perception and Expectations toward Artificial Intelligence in Capsule Endoscopy

2021 ◽  
Vol 10 (23) ◽  
pp. 5708
Author(s):  
Romain Leenhardt ◽  
Ignacio Fernandez-Urien Sainz ◽  
Emanuele Rondonotti ◽  
Ervin Toth ◽  
Cedric Van de Bruaene ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Capsule Endoscopy ◽  
Online Survey ◽  
Reading Time ◽  
General Information ◽  
Care Group ◽  
Complete Replacement ◽  
National Leaders ◽  
The Mean ◽  
Standardize Reporting

Artificial intelligence (AI) has shown promising results in digestive endoscopy, especially in capsule endoscopy (CE). However, some physicians still have some difficulties and fear the advent of this technology. We aimed to evaluate the perceptions and current sentiments toward the use of AI in CE. An online survey questionnaire was sent to an audience of gastroenterologists. In addition, several European national leaders of the International CApsule endoscopy REsearch (I CARE) Group were asked to disseminate an online survey among their national communities of CE readers (CER). The survey included 32 questions regarding general information, perceptions of AI, and its use in daily life, medicine, endoscopy, and CE. Among 380 European gastroenterologists who answered this survey, 333 (88%) were CERs. The mean average time length of experience in CE reading was 9.9 years (0.5–22). A majority of CERs agreed that AI would positively impact CE, shorten CE reading time, and help standardize reporting in CE and characterize lesions seen in CE. Nevertheless, in the foreseeable future, a majority of CERs disagreed with the complete replacement all CE reading by AI. Most CERs believed in the high potential of AI for becoming a valuable tool for automated diagnosis and for shortening the reading time. Currently, the perception is that AI will not replace CE reading.

scholarly journals Robotics and Artificial Intelligence

2020 ◽  
Vol 10 (2) ◽  
pp. 57-78 ◽  
Author(s):  
Estifanos Tilahun Mihret
Keyword(s):  
Artificial Intelligence ◽  
At Risk ◽  
Human Beings ◽  
The Past ◽  
Near Future ◽  
And Robotics

Artificial intelligence and robotics are very recent technologies and risks for our world. They are developing their capacity dramatically and shifting their origins of developing intention to other dimensions. When humans see the past histories of AI and robotics, human beings can examine and understand the objectives and intentions of them which to make life easy and assist human beings within different circumstances and situations. However, currently and in the near future, due to changing the attitude of robotic and AI inventors and experts as well as based on the AI nature that their capacity of environmental acquisition and adaptation, they may become predators and put creatures at risk. They may also inherit the full nature of creatures. Thus, finally they will create their new universe or the destiny of our universe will be in danger.

scholarly journals Robotics and Artificial Intelligence in Gastrointestinal Endoscopy: Updated Review of the Literature and State of the Art

2021 ◽  
Author(s):  
Ivo Boškoski ◽  
Beatrice Orlandini ◽  
Luigi Giovanni Papparella ◽  
Maria Valeria Matteo ◽  
Martina De Siena ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Gastrointestinal Endoscopy ◽  
State Of The Art ◽  
Unmet Need ◽  
Diagnostic Techniques ◽  
Review Of The Literature ◽  
The Past ◽  
Wide Range ◽  
Near Future ◽  
Artificial Intelligence Systems

Abstract Purpose of Review Gastrointestinal endoscopy includes a wide range of procedures that has dramatically evolved over the past decades. Robotic endoscopy and artificial intelligence are expanding the horizons of traditional techniques and will play a key role in clinical practice in the near future. Understanding the main available devices and procedures is a key unmet need. This review aims to assess the current and future applications of the most recently developed endoscopy robots. Recent Findings Even though a few devices have gained approval for clinical application, the majority of robotic and artificial intelligence systems are yet to become an integral part of the current endoscopic instrumentarium. Some of the innovative endoscopic devices and artificial intelligence systems are dedicated to complex procedures such as endoscopic submucosal dissection, whereas others aim to improve diagnostic techniques such as colonoscopy. Summary A review on flexible endoscopic robotics and artificial intelligence systems is presented here, showing the m3ost recently approved and experimental devices and artificial intelligence systems for diagnosis and robotic endoscopy.

Simultaneous Interpreting (SI): the Holy Grail of Artificial Intelligence – An SI Practitioner’s Perspective

2017 ◽  
Vol 62 (2) ◽  
Author(s):  
Ailing Zhang
Keyword(s):  
Artificial Intelligence ◽  
Computer Program ◽  
Image Recognition ◽  
Human Performance ◽  
Rapid Progress ◽  
Holy Grail ◽  
Simultaneous Interpreting ◽  
The Past ◽  
World Class ◽  
Near Future

AbstractArtificial Intelligence (AI) has been become a household expression, especially in the past couple of years thanks to Google’s AI Computer program AlphaGo defeating a couple of world-class Go masters from Korea and China. In recent years, machines have surpassed humans in the performance of certain specific tasks, such as some aspects of image recognition. Although it is unlikely that machines will exhibit broadly-applicable intelligence comparable to or exceeding that of humans in the near future, experts forecast that rapid progress in the field of specialized AI will continue, with machines reaching and exceeding human performance on an increasing number of tasks. Simultaneous interpreting, being among the most complex of human cognitive/linguistic activities, with all the associated ergonomic elements, has been discussed profusely as one of the most likely to be taken over by AI in a couple of years. Given that so much has to be there simultaneously, i. e. anticipation, restoration of the implicit-explicit balance, and communicative re-packaging (‘re-ostension’

Neurologic Diagnostics in 2035

Neurology ◽  
2021 ◽  
Vol 97 (19) ◽  
pp. 902-907 ◽  
Author(s):  
Olga Ciccarelli ◽  
Massimo Pandolfo
Keyword(s):  
Artificial Intelligence ◽  
Clinical Judgment ◽  
Clinical Skills ◽  
Assistive Technologies ◽  
Diagnostic Tools ◽  
Diagnostic Process ◽  
Neurologic Diseases ◽  
Novel Technologies ◽  
The Past ◽  
Diagnostic Applications

Innovations and advances in technologies over the past few years have yielded faster and wider diagnostic applications to patients with neurologic diseases. This article focuses on the foreseeable developments of the diagnostic tools available to the neurologist in the next 15 years. Clinical judgment is and will remain the cornerstone of the diagnostic process, assisted by novel technologies, such as artificial intelligence and machine learning. Future neurologists must be educated to develop, cultivate, and rely on their clinical skills, while becoming familiar with novel, often complex, assistive technologies.

SYSTEM ANALYSIS OF THE PROBLEMS OF THE SCIENCE AND TECHNOLOGY FIELD «MEDICAL COMPUTER-AIDED DESIGN»

2021 ◽  
Vol 13 (4) ◽  
pp. 38-52
Author(s):  
Rashit Nasyrov ◽  
Oleg Tiunov ◽  
Igor Tiunov
Keyword(s):  
Computer Aided Design ◽  
Business Processes ◽  
System Analysis ◽  
Subject Area ◽  
Diagnostic Process ◽  
Computer Aided ◽  
Medical Computer ◽  
Medical Diagnostic ◽  
Design Systems ◽  
Aided Design

The article provides a system analysis of many problems that hinder the development of medical computer-aided design systems (CAD), in order to identify the most important problems of the subject area. An analysis is made of the key participant roles of the development and practical use process of medical CAD systems in order to determine the degree of their contribution to the final comprehensive result. The structure of business processes is being developed to ensure the completeness and relevance of the developed problematic model. The results can be useful for researchers and developers of medical computer-aided design systems, for experts of related specialties and potential consumers; for doctors studying or actively using computer modeling in the medical diagnostic process; for students studying medical informatics and students of biotechnological specialties, as well as teachers of relevant disciplines.

THE NEW GENERATION OF EXPRESS VIEW IS HIGHLY ACCURATE AND IS EFFECTIVE TO REDUCE CAPSULE ENDOSCOPY READING TIME

2020 ◽  
Author(s):  
S Piccirelli ◽  
A Mussetto ◽  
A Bellumat ◽  
R Cannizzaro ◽  
M Pennazio ◽  
...  
Keyword(s):  
Capsule Endoscopy ◽  
Reading Time ◽  
New Generation

Virtual Screening Meets Deep Learning

2018 ◽  
Vol 15 (1) ◽  
pp. 6-28 ◽  
Author(s):  
Javier Pérez-Sianes ◽  
Horacio Pérez-Sánchez ◽  
Fernando Díaz
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Deep Learning ◽  
Virtual Screening ◽  
Great Increase ◽  
New Drugs ◽  
Learning Approach ◽  
Screening Strategies ◽  
Computer Aided ◽  
Recent Developments

Background: Automated compound testing is currently the de facto standard method for drug screening, but it has not brought the great increase in the number of new drugs that was expected. Computer- aided compounds search, known as Virtual Screening, has shown the benefits to this field as a complement or even alternative to the robotic drug discovery. There are different methods and approaches to address this problem and most of them are often included in one of the main screening strategies. Machine learning, however, has established itself as a virtual screening methodology in its own right and it may grow in popularity with the new trends on artificial intelligence. Objective: This paper will attempt to provide a comprehensive and structured review that collects the most important proposals made so far in this area of research. Particular attention is given to some recent developments carried out in the machine learning field: the deep learning approach, which is pointed out as a future key player in the virtual screening landscape.

Understanding Molecular Process and Chemotherapeutics for the Management of Breast Cancer.

2020 ◽  
Vol 14 ◽  
Author(s):  
Abhishek Kumar ◽  
Neeraj Masand ◽  
Vaishali M. Patil
Keyword(s):  
Breast Cancer ◽  
Molecular Mechanisms ◽  
Molecular Targets ◽  
Molecular Classification ◽  
Neoplastic Disease ◽  
Molecular Process ◽  
The Past ◽  
Anti Cancer ◽  
Molecular Etiology ◽  
Near Future

Abstract: Breast cancer is the most common and highly heterogeneous neoplastic disease comprised of several subtypes with distinct molecular etiology and clinical behaviours. The mortality observed over the past few decades and the failure in eradicating the disease is due to the lack of specific etiology, molecular mechanisms involved in initiation and progression of breast cancer. Understanding of the molecular classes of breast cancer may also lead to new biological insights and eventually to better therapies. The promising therapeutic targets and novel anti-cancer approaches emerging from these molecular targets that could be applied clinically in the near future are being highlighted. In addition, this review discusses some of the details of current molecular classification and available chemotherapeutics

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