Role of Artificial Intelligence (AI) in Surgery: Introduction, General Principles, and Potential Applications

2020 ◽  
Author(s):  
Alberto Mangano ◽  
Valentina Valle ◽  
Nicolas Dreifuss ◽  
Gabriela Aguiluz ◽  
Mario Masrur
Keyword(s):  
Artificial Intelligence ◽  
Cognitive Tasks ◽  
Future Perspectives ◽  
General Introduction ◽  
Computing Power ◽  
Interdisciplinary Field ◽  
Potential Applications ◽  
Number Of Publications ◽  
Surgical Setting

AI (Artificial intelligence) is an interdisciplinary field aimed at the development of algorithms to endow machines with the capability of executing cognitive tasks. The number of publications regarding AI and surgery has increased dramatically over the last two decades. This phenomenon can partly be explained by the exponential growth in computing power available to the largest AI training runs. AI can be classified into different sub-domains with extensive potential clinical applications in the surgical setting. AI will increasingly become a major component of clinical practice in surgery. The aim of the present Narrative Review is to give a general introduction and summarized overview of AI, as well as to present additional remarks on potential surgical applications and future perspectives in surgery.

scholarly journals Data for sale: trust, confidence and sharing health data with commercial companies

2021 ◽  
pp. medethics-2021-107464
Author(s):  
Mackenzie Graham
Keyword(s):  
Artificial Intelligence ◽  
Data Sharing ◽  
Health Data ◽  
Computing Power ◽  
Health Institutions

Powered by ‘big health data’ and enormous gains in computing power, artificial intelligence and related technologies are already changing the healthcare landscape. Harnessing the potential of these technologies will necessitate partnerships between health institutions and commercial companies, particularly as it relates to sharing health data. The need for commercial companies to be trustworthy users of data has been argued to be critical to the success of this endeavour. I argue that this approach is mistaken. Our interactions with commercial companies need not, and should not, be based on trust. Rather, they should be based on confidence. I begin by elucidating the differences between trust, reliability, and confidence, and argue that trust is not the appropriate attitude to adopt when it comes to sharing data with commercial companies. I argue that what we really should want is confidence in a system of data sharing. I then provide an outline of what a confidence-worthy system of data sharing with commercial companies might look like, and conclude with some remarks about the role of trust within this system.

A review on the role of artificial intelligence in stem cell therapy: An initiative for modern medicines

2020 ◽  
Vol 21 ◽  
Author(s):  
Pravin Shende ◽  
Nikita P. Devlekar
Keyword(s):  
Artificial Intelligence ◽  
Individual Cell ◽  
Home Automation ◽  
Science And Engineering ◽  
Prediction Of Mortality ◽  
Wide Range ◽  
Potential Applications ◽  
Applications Of Ai

: Stem cells (SCs) show a wide range of applications in the treatment of numerous diseases including neurodegenerative diseases, diabetes, cardiovascular diseases, cancer, etc. SC related research has gained popularity owing to the unique characteristics of self-renewal and differentiation. Artificial intelligence (AI), an emerging field of computer science and engineering has shown potential applications in different fields like robotics, agriculture, home automation, healthcare, banking, and transportation since its invention. This review aims to describe the various applications of AI in SC biology including understanding the behavior of SCs, recognizing individual cell type before undergoing differentiation, characterization of SCs using mathematical models and prediction of mortality risk associated with SC transplantation. This review emphasizes the role of neural networks in SC biology and further elucidates the concepts of machine learning and deep learning and their applications in SC research.

scholarly journals Telepsychiatry and the Role of Artificial Intelligence in Mental Health in Post-COVID-19 India: A Scoping Review on Opportunities

2020 ◽  
Vol 42 (5) ◽  
pp. 428-434
Author(s):  
Thenral M ◽  
Arunkumar Annamalai
Keyword(s):  
Mental Health ◽  
Artificial Intelligence ◽  
Scoping Review ◽  
Scientific Information ◽  
Health Seeking ◽  
Origin And Evolution ◽  
The Status ◽  
Seeking Behavior ◽  
Potential Applications

Background: COVID-19 has a profound impact on people with existing mental disorders, augmenting the prevailing inequalities in mental health. Methods: In order to understand the status of telepsychiatry in India and the role of artificial intelligence (AI) in mental health and its potential applications, a scoping review was done between March 2020 and May 2020. The literature review revealed 253 papers, which were used to derive the primary framework for analysis. The information was then reviewed for ideas and concepts, which were integrated with evidence from gray literature and categorized under broader themes based on the insights derived. Finally, a thematic framework was developed for discussion to tailor scientific information for decision-makers’ needs. Results: Review findings are summarized under the following headings: changing patterns of health-seeking behavior, origin and evolution of telepsychiatry, possible applications of telepsychiatry and AI, technological features, and AI models in mental health. Conclusions: Though there are several potential opportunities, the time is not yet ripe for telepsychiatry and AI to be adopted fully in the field of mental health care. But it is time that we develop indigenous proprietary technology and test and validate it. With many solutions offered by telepsychiatry and AI, psychiatrists must choose an appropriate tool based on their requirements, availability of resources, and feasibility of deployment. Harmony between conventional care and technology-based care must be reached gradually.

scholarly journals Canadian Association of Radiologists White Paper on Artificial Intelligence in Radiology

2018 ◽  
Vol 69 (2) ◽  
pp. 120-135 ◽  
Author(s):  
An Tang ◽  
Roger Tam ◽  
Alexandre Cadrin-Chênevert ◽  
Will Guest ◽  
Jaron Chong ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Patient Care ◽  
Working Group ◽  
White Paper ◽  
Patient Centered ◽  
Computing Power ◽  
Implementation Phase ◽  
Early Adoption ◽  
Canadian Association

Artificial intelligence (AI) is rapidly moving from an experimental phase to an implementation phase in many fields, including medicine. The combination of improved availability of large datasets, increasing computing power, and advances in learning algorithms has created major performance breakthroughs in the development of AI applications. In the last 5 years, AI techniques known as deep learning have delivered rapidly improving performance in image recognition, caption generation, and speech recognition. Radiology, in particular, is a prime candidate for early adoption of these techniques. It is anticipated that the implementation of AI in radiology over the next decade will significantly improve the quality, value, and depth of radiology's contribution to patient care and population health, and will revolutionize radiologists' workflows. The Canadian Association of Radiologists (CAR) is the national voice of radiology committed to promoting the highest standards in patient-centered imaging, lifelong learning, and research. The CAR has created an AI working group with the mandate to discuss and deliberate on practice, policy, and patient care issues related to the introduction and implementation of AI in imaging. This white paper provides recommendations for the CAR derived from deliberations between members of the AI working group. This white paper on AI in radiology will inform CAR members and policymakers on key terminology, educational needs of members, research and development, partnerships, potential clinical applications, implementation, structure and governance, role of radiologists, and potential impact of AI on radiology in Canada.

scholarly journals Applications of Artificial Intelligence for the Diagnosis of Gastrointestinal Diseases

Diagnostics ◽  
2021 ◽  
Vol 11 (9) ◽  
pp. 1575
Author(s):  
Silvia Pecere ◽  
Sebastian Manuel Milluzzo ◽  
Gianluca Esposito ◽  
Emanuele Dilaghi ◽  
Andrea Telese ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Care Professionals ◽  
Gastrointestinal Diseases ◽  
Controlled Trials ◽  
Clinical Settings ◽  
High Quality ◽  
Potential Applications ◽  
Malignant Lesions ◽  
Applications Of Ai

The development of convolutional neural networks has achieved impressive advances of machine learning in recent years, leading to an increasing use of artificial intelligence (AI) in the field of gastrointestinal (GI) diseases. AI networks have been trained to differentiate benign from malignant lesions, analyze endoscopic and radiological GI images, and assess histological diagnoses, obtaining excellent results and high overall diagnostic accuracy. Nevertheless, there data are lacking on side effects of AI in the gastroenterology field, and high-quality studies comparing the performance of AI networks to health care professionals are still limited. Thus, large, controlled trials in real-time clinical settings are warranted to assess the role of AI in daily clinical practice. This narrative review gives an overview of some of the most relevant potential applications of AI for gastrointestinal diseases, highlighting advantages and main limitations and providing considerations for future development.

scholarly journals Engineering and clinical use of artificial intelligence (AI) with machine learning and data science advancements: radiology leading the way for future

2021 ◽  
Vol 13 ◽  
pp. 175628722110448
Author(s):  
B.M. Zeeshan Hameed ◽  
Gayathri Prerepa ◽  
Vathsala Patil ◽  
Pranav Shekhar ◽  
Syed Zahid Raza ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Machine Learning ◽  
Human Error ◽  
Data Science ◽  
Image Interpretation ◽  
X Ray ◽  
X Ray Imaging ◽  
Potential Applications ◽  
Efficiency And Productivity

Over the years, many clinical and engineering methods have been adapted for testing and screening for the presence of diseases. The most commonly used methods for diagnosis and analysis are computed tomography (CT) and X-ray imaging. Manual interpretation of these images is the current gold standard but can be subject to human error, is tedious, and is time-consuming. To improve efficiency and productivity, incorporating machine learning (ML) and deep learning (DL) algorithms could expedite the process. This article aims to review the role of artificial intelligence (AI) and its contribution to data science as well as various learning algorithms in radiology. We will analyze and explore the potential applications in image interpretation and radiological advances for AI. Furthermore, we will discuss the usage, methodology implemented, future of these concepts in radiology, and their limitations and challenges.

Michael Kelly, Hilary Footitt, Myriam Salama-Carr (eds.): The Palgrave Handbook of Languages and Conflict

2020 ◽  
Vol 55 (2) ◽  
Author(s):  
Ľubomír Zvada
Keyword(s):  
International Relations ◽  
Foreign Languages ◽  
Military Operations ◽  
Sources Of Information ◽  
War And Peace ◽  
Interdisciplinary Field ◽  
Speakers Of Other Languages ◽  
War And Conflict ◽  
Almost All

This Handbook maps the contours of an exciting and burgeoning interdisciplinary field concerned with the role of language and languages in situations of conflict. It explores conceptual approaches, sources of information that are available, and the institutions and actors that mediate language encounters. It examines case studies of the role that languages have played in specific conflicts, from colonial times through to the Middle East and Africa today. The contributors provide vibrant evidence to challenge the monolingual assumptions that have affected traditional views of war and conflict. They show that languages are woven into every aspect of the making of war and peace, and demonstrate how language shapes public policy and military strategy, setting frameworks and expectations. The Handbook's 22 chapters powerfully illustrate how the encounter between languages is integral to almost all conflicts, to every phase of military operations and to the lived experiences of those on the ground, who meet, work and fight with speakers of other languages. This comprehensive work will appeal to scholars from across the disciplines of linguistics, translation studies, history, and international relations; and provide fresh insights for a broad range of practitioners interested in understanding the role and implications of foreign languages in war.

Management of Economics and State "Bottom"

2020 ◽  
Vol 17 (6) ◽  
pp. 76-91
Author(s):  
E. D. Solozhentsev
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Probabilistic Models ◽  
Human Life ◽  
Special Software ◽  
Human Quality ◽  
Relationship Of ◽  
The Relationship

The scientific problem of economics “Managing the quality of human life” is formulated on the basis of artificial intelligence, algebra of logic and logical-probabilistic calculus. Managing the quality of human life is represented by managing the processes of his treatment, training and decision making. Events in these processes and the corresponding logical variables relate to the behavior of a person, other persons and infrastructure. The processes of the quality of human life are modeled, analyzed and managed with the participation of the person himself. Scenarios and structural, logical and probabilistic models of managing the quality of human life are given. Special software for quality management is described. The relationship of human quality of life and the digital economy is examined. We consider the role of public opinion in the management of the “bottom” based on the synthesis of many studies on the management of the economics and the state. The bottom management is also feedback from the top management.

Artificial Intelligence in Logistics

2019 ◽  
Vol 12 (1) ◽  
pp. 47-60
Author(s):  
László Kota
Keyword(s):  
Artificial Intelligence ◽  
Computing Power ◽  
Self Driving Cars

The artificial intelligence undergoes an enormous development since its appearance in the fifties. The computing power has grown exponentially since then, enabling the use of artificial intelligence applications in different areas. Since then, artificial intelligence applications are not only present in the industry, but they have slowly conquered households as well. Their use in logistics is becoming more and more widespread, just think of self-driving cars and trucks. In this paper, the author attempts to summarize and present the artificial intelligence logistical applications, its development and impact on logistics.

Artificial intelligence and the management transformation

2020 ◽  
Vol 16 (4) ◽  
pp. 600-612
Author(s):  
L.F. Nikulin ◽  
V.V. Velikorossov ◽  
S.A. Filin ◽  
A.B. Lanchakov
Keyword(s):  
Artificial Intelligence ◽  
Social Life ◽  
Soft Power ◽  
Process Integration ◽  
Management Practice ◽  
Scientific School ◽  
Strategic Culture ◽  
Analysis And Synthesis ◽  
And Training

Subject. The article discusses how management transforms as artificial intelligence gets more important in governance, production and social life. Objectives. We identify and substantiate trends in management transformation as artificial intelligence evolves and gets more important in governance, production and social life. The article also provides our suggestions for management and training of managers dealing with artificial intelligence. Methods. The study employs methods of logic research, analysis and synthesis through the systems and creative approach, methodology of technological waves. Results. We analyzed the scope of management as is and found that threats and global challenges escalate due to the advent of artificial intelligence. We provide the rationale for recognizing the strategic culture as the self-organizing system of business process integration. We suggest and substantiate the concept of soft power with reference to strategic culture, which should be raised, inter alia, through the scientific school of conflict studies. We give our recommendations on how management and training of managers should be improved in dealing with artificial intelligence as it evolves. The novelty hereof is that we trace trends in management transformation as the role of artificial intelligence evolves and growth in governance, production and social life. Conclusions and Relevance. Generic solutions are not very effective for the Russian management practice during the transition to the sixth and seventh waves of innovation. Any programming product represents artificial intelligence, which simulates a personality very well, though unable to substitute a manager in motivating, governing and interacting with people.

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