scholarly journals Investigating the Ethical and Data Governance Issues of Artificial Intelligence in Surgery: Protocol for a Delphi Study

10.2196/26552 ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. e26552
Author(s):  
Kyle Lam ◽  
Fahad M Iqbal ◽  
Sanjay Purkayastha ◽  
James M Kinross
Keyword(s):  
Artificial Intelligence ◽  
Operating Room ◽  
Digital Technology ◽  
Delphi Study ◽  
A Priori ◽  
Learning Curves ◽  
Future Research ◽  
Free Text ◽  
Data Governance ◽  
Digital Surgery

Background The rapid uptake of digital technology into the operating room has the potential to improve patient outcomes, increase efficiency of the use of operating rooms, and allow surgeons to progress quickly up learning curves. These technologies are, however, dependent on huge amounts of data, and the consequences of their mismanagement are significant. While the field of artificial intelligence ethics is able to provide a broad framework for those designing and implementing these technologies into the operating room, there is a need to determine and address the ethical and data governance challenges of using digital technology in this unique environment. Objective The objectives of this study are to define the term digital surgery and gain expert consensus on the key ethical and data governance issues, barriers, and future research goals of the use of artificial intelligence in surgery. Methods Experts from the fields of surgery, ethics and law, policy, artificial intelligence, and industry will be invited to participate in a 4-round consensus Delphi exercise. In the first round, participants will supply free-text responses across 4 key domains: ethics, data governance, barriers, and future research goals. They will also be asked to provide their understanding of the term digital surgery. In subsequent rounds, statements will be grouped, and participants will be asked to rate the importance of each issue on a 9-point Likert scale ranging from 1 (not at all important) to 9 (critically important). Consensus is defined a priori as a score of 7 to 9 by 70% of respondents and 1 to 3 by less than 30% of respondents. A final online meeting round will be held to discuss inclusion of statements and draft a consensus document. Results Full ethical approval has been obtained for the study by the local research ethics committee at Imperial College, London (20IC6136). We anticipate round 1 to commence in January 2021. Conclusions The results of this study will define the term digital surgery, identify the key issues and barriers, and shape future research in this area. International Registered Report Identifier (IRRID) PRR1-10.2196/26552

scholarly journals Investigating the Ethical and Data Governance Issues of Artificial Intelligence in Surgery: Protocol for a Delphi Study (Preprint)

2020 ◽  
Author(s):  
Kyle Lam ◽  
Fahad M Iqbal ◽  
Sanjay Purkayastha ◽  
James M Kinross
Keyword(s):  
Artificial Intelligence ◽  
Operating Room ◽  
Digital Technology ◽  
Delphi Study ◽  
A Priori ◽  
Learning Curves ◽  
Future Research ◽  
Free Text ◽  
Data Governance ◽  
Digital Surgery

BACKGROUND The rapid uptake of digital technology into the operating room has the potential to improve patient outcomes, increase efficiency of the use of operating rooms, and allow surgeons to progress quickly up learning curves. These technologies are, however, dependent on huge amounts of data, and the consequences of their mismanagement are significant. While the field of artificial intelligence ethics is able to provide a broad framework for those designing and implementing these technologies into the operating room, there is a need to determine and address the ethical and data governance challenges of using digital technology in this unique environment. OBJECTIVE The objectives of this study are to define the term digital surgery and gain expert consensus on the key ethical and data governance issues, barriers, and future research goals of the use of artificial intelligence in surgery. METHODS Experts from the fields of surgery, ethics and law, policy, artificial intelligence, and industry will be invited to participate in a 4-round consensus Delphi exercise. In the first round, participants will supply free-text responses across 4 key domains: ethics, data governance, barriers, and future research goals. They will also be asked to provide their understanding of the term digital surgery. In subsequent rounds, statements will be grouped, and participants will be asked to rate the importance of each issue on a 9-point Likert scale ranging from 1 (not at all important) to 9 (critically important). Consensus is defined a priori as a score of 7 to 9 by 70% of respondents and 1 to 3 by less than 30% of respondents. A final online meeting round will be held to discuss inclusion of statements and draft a consensus document. RESULTS Full ethical approval has been obtained for the study by the local research ethics committee at Imperial College, London (20IC6136). We anticipate round 1 to commence in January 2021. CONCLUSIONS The results of this study will define the term digital surgery, identify the key issues and barriers, and shape future research in this area. INTERNATIONAL REGISTERED REPORT PRR1-10.2196/26552

scholarly journals Improving physical activity, sedentary behaviour and sleep in COPD: perspectives of people with COPD and experts via a Delphi approach

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e4604 ◽  
Author(s):  
Hayley Lewthwaite ◽  
Tanja W. Effing ◽  
Anke Lenferink ◽  
Tim Olds ◽  
Marie T. Williams
Keyword(s):  
Physical Activity ◽  
Sedentary Behaviour ◽  
Delphi Study ◽  
A Priori ◽  
South Australia ◽  
Chronic Obstructive ◽  
Free Text ◽  
Obstructive Pulmonary Disease ◽  
Delphi Approach ◽  
Multifactorial Approach

Background Little is known about how to achieve enduring improvements in physical activity (PA), sedentary behaviour (SB) and sleep for people with chronic obstructive pulmonary disease (COPD). This study aimed to: (1) identify what people with COPD from South Australia and the Netherlands, and experts from COPD- and non-COPD-specific backgrounds considered important to improve behaviours; and (2) identify areas of dissonance between these different participant groups. Methods A four-round Delphi study was conducted, analysed separately for each group. Free-text responses (Round 1) were collated into items within themes and rated for importance on a 9-point Likert scale (Rounds 2–3). Items meeting a priori criteria from each group were retained for rating by all groups in Round 4. Items and themes achieving a median Likert score of ≥7 and an interquartile range of ≤2 across all groups at Round 4 were judged important. Analysis of variance with Tukey’s post-hoc tested for statistical differences between groups for importance ratings. Results Seventy-three participants consented to participate in this study, of which 62 (85%) completed Round 4. In Round 4, 81 items (PA n = 54; SB n = 24; sleep n = 3) and 18 themes (PA n = 9; SB n = 7; sleep n = 2) were considered important across all groups concerning: (1) symptom/disease management, (2) targeting behavioural factors, and (3) less commonly, adapting the social/physical environments. There were few areas of dissonance between groups. Conclusion Our Delphi participants considered a multifactorial approach to be important to improve PA, SB and sleep. Recognising and addressing factors considered important to recipients and providers of health care may provide a basis for developing behaviour-specific interventions leading to long-term behaviour change in people with COPD.

scholarly journals Disagreement and Uncertainty Among Experts About how to Respond to Marijuana Use in Patients on Long-term Opioids for Chronic Pain: Results of a Delphi Study

Pain Medicine ◽  
2019 ◽  
Author(s):  
Joanna L Starrels ◽  
Sarah R Young ◽  
Soraya S Azari ◽  
William C Becker ◽  
E Jennifer Edelman ◽  
...  
Keyword(s):  
Chronic Pain ◽  
Delphi Study ◽  
A Priori ◽  
Management Strategies ◽  
Marijuana Use ◽  
Initial Response ◽  
The United States ◽  
Opioid Therapy ◽  
Free Text

Abstract Background Marijuana use is common among patients on long-term opioid therapy (LTOT) for chronic pain, but there is a lack of evidence to guide clinicians’ response. Objective To generate expert consensus about responding to marijuana use among patients on LTOT. Design Analysis from an online Delphi study. Setting/Subjects Clinician experts in pain and opioid management across the United States. Methods Participants generated management strategies in response to marijuana use without distinction between medical and nonmedical use, then rated the importance of each management strategy from 1 (not at all important) to 9 (extremely important). A priori rules for consensus were established, and disagreement was explored using cases. Thematic analysis of free-text responses examined factors that influenced participants’ decision-making. Results Of 42 participants, 64% were internal medicine physicians. There was consensus that it is not important to taper opioids as an initial response to marijuana use. There was disagreement about the importance of tapering opioids if there is a pattern of repeated marijuana use without clinical suspicion for a cannabis use disorder (CUD) and consensus that tapering is of uncertain importance if there is suspicion for CUD. Three themes influenced experts’ perceptions of the importance of tapering: 1) benefits and harms of marijuana for the individual patient, 2) a spectrum of belief about the overall riskiness of marijuana use, and 3) variable state laws or practice policies. Conclusions Experts disagree and are uncertain about the importance of opioid tapering for patients with marijuana use. Experts were influenced by patient factors, provider beliefs, and marijuana policy, highlighting the need for further research.

scholarly journals A Review on the Current Applications of Artificial Intelligence in the Operating Room

2021 ◽  
pp. 155335062199696
Author(s):  
David C. Birkhoff ◽  
Anne Sophie H.M. van Dalen ◽  
Marlies P. Schijven
Keyword(s):  
Artificial Intelligence ◽  
Operating Room ◽  
Guidance System ◽  
Cochrane Library ◽  
Future Research ◽  
Surgical Safety ◽  
Analysis Workflow ◽  
Endoscopic Guidance ◽  
Clinical Conditions ◽  
Applications Of Ai

Background. Artificial intelligence (AI) is an era upcoming in medicine and, more recently, in the operating room (OR). Existing literature elaborates mainly on the future possibilities and expectations for AI in surgery. The aim of this study is to systematically provide an overview of the current actual AI applications used to support processes inside the OR. Methods. PubMed, Embase, Cochrane Library, and IEEE Xplore were searched using inclusion criteria for relevant articles up to August 25th, 2020. No study types were excluded beforehand. Articles describing current AI applications for surgical purposes inside the OR were reviewed. Results. Nine studies were included. An overview of the researched and described applications of AI in the OR is provided, including procedure duration prediction, gesture recognition, intraoperative cancer detection, intraoperative video analysis, workflow recognition, an endoscopic guidance system, knot-tying, and automatic registration and tracking of the bone in orthopedic surgery. These technologies are compared to their, often non-AI, baseline alternatives. Conclusions. Currently described applications of AI in the OR are limited to date. They may, however, have a promising future in improving surgical precision, reduce manpower, support intraoperative decision-making, and increase surgical safety. Nonetheless, the application and implementation of AI inside the OR still has several challenges to overcome. Clear regulatory, organizational, and clinical conditions are imperative for AI to redeem its promise. Future research on use of AI in the OR should therefore focus on clinical validation of AI applications, the legal and ethical considerations, and on evaluation of implementation trajectory.

scholarly journals The evolution of surgical education

2021 ◽  
Vol 17 (1) ◽  
pp. 1-5
Author(s):  
Eugen Târcoveanu ◽  
R. Moldovanu
Keyword(s):  
Artificial Intelligence ◽  
Operating Room ◽  
Surgical Education ◽  
Rapid Development ◽  
Surgical Care ◽  
Basic Research ◽  
Surgical Patient ◽  
Training Methods ◽  
Knowledge Based ◽  
Digital Surgery

Surgery is constantly evolving along the history. Surgery has seen an impressive evolution due to advances in anesthesia, basic research, means of exploration, immunology, genetics, pharmacology and especially in artificial intelligence. Surgery has evolved from open surgery to minimally invasive surgery, then to robotic surgery and in future to digital surgery. The five pillars of digital surgery are: (1) robotics, (2) advanced instrumentation, (3) enhanced visualization, (4) connectivity, and (5) data analytics and machine learning. Surgical education has evolved from Halsted's model (one see, one do, one teach) to special training programs such as the Rasmussen model in 3 stages: skill based behavior, ruled based behavior, knowledge based behavior. Digital technologies are changing surgical education. New terms appear such as: Massive open online courses, Flipped classrooms, Digital badges, Virtual anatomy, Medical holograms. Artificial intelligence can improve surgical education. It can bring transparency to the operating room and accelerate surgical education. Digital Mentoring provides the next generation of the digital platform with the transfer of surgical knowledge from an expert to a practitioner and allows surgeons to evolve to achieve the best results. In addition, all members of the operative team can benefit from training using augmented virtual reality. Establishing an infrastructure that allows the perfect integration of robotics, artificial intelligence, advanced instrumentation, advanced training methods, educational programs will allow the rapid development of innovation and surgical progress. In this way, digital surgery will provide globally advanced surgical care in continuous improvement. The classical methods still remain valid in the training of young surgeons. The most important aspect remains the training in the operating room. The new methods do not exclude the classic training that gave good results, but they complement and make general surgery more attractive for the new generation. In the desire to reform surgical education we have actually lost the purpose of training - the surgical patient, which is real, not virtual. The most important aspect that must be transmitted to young surgeons is the humanism of our profession, which for the time being cannot take the digital form.

Artificial Intelligence in Government: Taking Stock and Moving Forward

2021 ◽  
pp. 089443932110340
Author(s):  
Rony Medaglia ◽  
J. Ramon Gil-Garcia ◽  
Theresa A. Pardo
Keyword(s):  
Artificial Intelligence ◽  
State Of The Art ◽  
Future Research ◽  
Special Issue ◽  
Data Governance ◽  
Research And Practice ◽  
Policy Initiatives ◽  
Current Trends ◽  
The Social ◽  
The World

The use of artificial intelligence (AI) applications in government is receiving increasing attention from global research and practice communities. This article, introducing a Special Issue on Artificial Intelligence in Government published in the Social Science Computer Review, presents an overview of some of the main policy initiatives across the world in relation to AI in government and discusses the state of the art of existing research. Based on an analysis of current trends in research and practice, we highlight four areas to be the focus of future research on AI in government: governance of AI, trustworthy AI, impact assessment methodologies, and data governance.

Prophetic Leadership Model: Conceptualizing a Prophet’s Leadership Behaviour, Leader-Follower Mutuality and Altruism to Decision Making Quality

2015 ◽  
Vol 3 (1) ◽  
pp. 93
Author(s):  
Nik Maheran Nik Muhammad
Keyword(s):  
Decision Making ◽  
Social Network ◽  
A Priori ◽  
Complex Function ◽  
Spiritual Leadership ◽  
Leadership Theory ◽  
Future Research ◽  
Leadership Model ◽  
Leadership Behaviour ◽  
Current Leadership

This article advocates that research is lacking on the connection between leadership theory and social network theory. To date, little empirical research has been conducted on leadership and social networks. Thus, the proposition of this article goes beyond traditional leadership models to advocate for a fuller and more integrative focus that is multilevel, multi-component and interdisciplinary, while recognizing that leadership is a complex function of both the organisational leaders and the followers who perform tasks, all of which subsequently leads to decision making qualities. Indeed, the current leadership model focuses on leadership behaviour and the ability to gain followers mutuality, to achieve decision making quality involving the integration of leadership and social network theories. Given the apparent mutable palette of contemporary leadership theory, this emergent construct of the leadership paradigm can expand the poles of the leadership continuum and contribute to a richer and deeper understanding of the relationships and responsibilities of leaders and followers as they relate to decision making qualities. This new construct, which is termed prophetic leadership, explores the literature of the life experiences of the prophet in the ‘Abrahamic Faith’ religion. Drawing on a priori links between the personality trait and spiritual leadership that has recently garnered the interest of scholars, the present study asserts a normative leadership theory that links the personal quality of a leader, posture and principal (based on the Prophet’s leadership behaviour) to synergy and decision making quality. Altruism is proposed to enhance relationships between leadership behaviour and decision making quality. For future research, much work needs to be done specifically aiming to (a) achieve greater clarity of construct definitions, (b) address measurement issues, and (c) avoid construct redundancy.

Prophetic Leadership Model: Conceptualizing a Prophet’s Leadership Behaviour, Leader-Follower Mutuality and Altruism to Decision Making Quality

2015 ◽  
Vol 1 (3) ◽  
pp. 93
Author(s):  
Nik Maheran Nik Muhammad
Keyword(s):  
Decision Making ◽  
Social Network ◽  
A Priori ◽  
Complex Function ◽  
Spiritual Leadership ◽  
Leadership Theory ◽  
Future Research ◽  
Leadership Model ◽  
Leadership Behaviour ◽  
Current Leadership

This article advocates that research is lacking on the connection between leadership theory and social network theory. To date, little empirical research has been conducted on leadership and social networks. Thus, the proposition of this article goes beyond traditional leadership models to advocate for a fuller and more integrative focus that is multilevel, multi-component and interdisciplinary, while recognizing that leadership is a complex function of both the organisational leaders and the followers who perform tasks, all of which subsequently leads to decision making qualities. Indeed, the current leadership model focuses on leadership behaviour and the ability to gain followers mutuality, to achieve decision making quality involving the integration of leadership and social network theories. Given the apparent mutable palette of contemporary leadership theory, this emergent construct of the leadership paradigm can expand the poles of the leadership continuum and contribute to a richer and deeper understanding of the relationships and responsibilities of leaders and followers as they relate to decision making qualities. This new construct, which is termed prophetic leadership, explores the literature of the life experiences of the prophet in the ‘Abrahamic Faith’ religion. Drawing on a priori links between the personality trait and spiritual leadership that has recently garnered the interest of scholars, the present study asserts a normative leadership theory that links the personal quality of a leader, posture and principal (based on the Prophet’s leadership behaviour) to synergy and decision making quality. Altruism is proposed to enhance relationships between leadership behaviour and decision making quality. For future research, much work needs to be done specifically aiming to (a) achieve greater clarity of construct definitions, (b) address measurement issues, and (c) avoid construct redundancy.

ICD10Net: An Artificial Intelligence Algorithm with Medical Background Conducts ICD-10-CM Coding Task with Outstanding Performance (Preprint)

2019 ◽  
Author(s):  
Chin Lin ◽  
Yu-Sheng Lou ◽  
Chia-Cheng Lee ◽  
Chia-Jung Hsu ◽  
Ding-Chung Wu ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
General Hospital ◽  
Pearson Correlation ◽  
Model Performance ◽  
International Classification Of Diseases ◽  
Free Text ◽  
Daily Work ◽  
Medical Background ◽  
Icd 10 ◽  
F Measure

BACKGROUND An artificial intelligence-based algorithm has shown a powerful ability for coding the International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) in discharge notes. However, its performance still requires improvement compared with human experts. The major disadvantage of the previous algorithm is its lack of understanding medical terminologies. OBJECTIVE We propose some methods based on human-learning process and conduct a series of experiments to validate their improvements. METHODS We compared two data sources for training the word-embedding model: English Wikipedia and PubMed journal abstracts. Moreover, the fixed, changeable, and double-channel embedding tables were used to test their performance. Some additional tricks were also applied to improve accuracy. We used these methods to identify the three-chapter-level ICD-10-CM diagnosis codes in a set of discharge notes. Subsequently, 94,483-labeled discharge notes from June 1, 2015 to June 30, 2017 were used from the Tri-Service General Hospital in Taipei, Taiwan. To evaluate performance, 24,762 discharge notes from July 1, 2017 to December 31, 2017, from the same hospital were used. Moreover, 74,324 additional discharge notes collected from other seven hospitals were also tested. The F-measure is the major global measure of effectiveness. RESULTS In understanding medical terminologies, the PubMed-embedding model (Pearson correlation = 0.60/0.57) shows a better performance compared with the Wikipedia-embedding model (Pearson correlation = 0.35/0.31). In the accuracy of ICD-10-CM coding, the changeable model both used the PubMed- and Wikipedia-embedding model has the highest testing mean F-measure (0.7311 and 0.6639 in Tri-Service General Hospital and other seven hospitals, respectively). Moreover, a proposed method called a hybrid sampling method, an augmentation trick to avoid algorithms identifying negative terms, was found to additionally improve the model performance. CONCLUSIONS The proposed model architecture and training method is named as ICD10Net, which is the first expert level model practically applied to daily work. This model can also be applied in unstructured information extraction from free-text medical writing. We have developed a web app to demonstrate our work (https://linchin.ndmctsgh.edu.tw/app/ICD10/).

Europe

2020 ◽  
pp. 649-666
Author(s):  
Andrea Renda
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Policy Framework ◽  
Expert Group ◽  
Ethical Guidelines ◽  
Ethical Implications ◽  
Strong Focus ◽  
Ethics Guidelines ◽  
Definition Of ◽  
High Level

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.

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