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 Recommendations for the Management of Incidental Hepatobiliary Findings in Adults: Endorsement and Adaptation of the 2017 and 2013 ACR Incidental Findings Committee White Papers by the Canadian Association of Radiologists Incidental Findings Working Group

2020 ◽  
Vol 71 (4) ◽  
pp. 437-447
Author(s):  
Jeffery R. Bird ◽  
Gary L. Brahm ◽  
Christopher Fung ◽  
Sunit Sebastian ◽  
Iain D. C. Kirkpatrick
Keyword(s):  
Computed Tomography ◽  
Patient Care ◽  
Working Group ◽  
Incidental Findings ◽  
Practice Patterns ◽  
Cost Effective ◽  
Initial Assessment ◽  
Wall Thickening ◽  
Canadian Association

The Canadian Association of Radiologists Incidental Findings Working Group consists of both academic subspecialty and general radiologists and is tasked with adapting and expanding upon the American College of Radiology incidental findings white papers to more closely apply to Canadian practice patterns, particularly more comprehensively dealing with the role of ultrasound and pursuing more cost-effective approaches to the workup of incidental findings without compromising patient care. Presented here are the 2020 Canadian guidelines for the management of hepatobiliary incidental findings. Topics covered include initial assessment of hepatic steatosis and cirrhosis, the workup of incidental liver masses identified on ultrasound and computed tomography (with algorithms presented), incidental gallbladder findings (wall thickening, calcification, and polyps), and management of incidental biliary dilatation.

scholarly journals Recommendations for the Management of Incidental Pancreatic Findings in Adults by the Canadian Association of Radiologists Incidental Findings Working Group

2021 ◽  
pp. 084653712110210
Author(s):  
Christopher I. Fung ◽  
David L. Bigam ◽  
Clarence K. W. Wong ◽  
Casey Hurrell ◽  
Jeffery R. Bird ◽  
...  
Keyword(s):  
Working Group ◽  
Incidental Findings ◽  
Practice Patterns ◽  
Cost Effective ◽  
Pancreatic Cysts ◽  
Canadian Association ◽  
Pancreatic Calcifications ◽  
Fatty Atrophy ◽  
Anatomic Variants

The Canadian Association of Radiologists Incidental Findings Working Group consists of both academic subspecialty and general radiologists and is tasked with adapting and expanding upon the American College of Radiology incidental findings white papers to more closely apply to Canadian practice patterns, particularly more comprehensively dealing with the role of ultrasound and pursuing more cost-effective approaches to the workup of incidental findings without compromising patient care. Presented here are the 2021 Canadian guidelines for the management of pancreatic incidental findings. Topics covered include anatomic variants, fatty atrophy, pancreatic calcifications, ductal ectasia, and management of incidental pancreatic cysts.

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.

scholarly journals Optometric Care of the Patient with Diabetes 2008: A Core Document of the Canadian Association of Optometrists

2008 ◽  
Vol 70 (6) ◽  
Author(s):  
Len Koltun
Keyword(s):  
Cost Effective ◽  
Morbidity And Mortality ◽  
Evidence Based ◽  
Eye Care ◽  
Patient Centered ◽  
Healthcare Burden ◽  
Canadian Association ◽  
Effective Role

The objective of this document is to provide the reader with an overview of the epidemic of diabetes currently facing Canada and the morbidity and mortality associated with this growing healthcare burden. Specifically, an evidence based, patient centered, cost effective role of the optometrist in the eye care of Canadians with diabetes will be presented.

scholarly journals Ethical Considerations in the Advent of Artificial Intelligence in Otolaryngology

2019 ◽  
Vol 162 (1) ◽  
pp. 38-39
Author(s):  
Alexandra M. Arambula ◽  
Andrés M. Bur
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Decision Making ◽  
Medical Ethics ◽  
Patient Care ◽  
Care Delivery ◽  
Shared Decision ◽  
Ethical Considerations ◽  
Widespread Implementation

Artificial intelligence (AI) is quickly expanding within the sphere of health care, offering the potential to enhance the efficiency of care delivery, diminish costs, and reduce diagnostic and therapeutic errors. As the field of otolaryngology also explores use of AI technology in patient care, a number of ethical questions warrant attention prior to widespread implementation of AI. This commentary poses many of these ethical questions for consideration by the otolaryngologist specifically, using the 4 pillars of medical ethics—autonomy, beneficence, nonmaleficence, and justice—as a framework and advocating both for the assistive role of AI in health care and for the shared decision-making, empathic approach to patient care.

scholarly journals Canadian Association of Radiologists White Paper on Ethical and Legal Issues Related to Artificial Intelligence in Radiology

2019 ◽  
Vol 70 (2) ◽  
pp. 107-118 ◽  
Author(s):  
◽  
Jacob L. Jaremko ◽  
Marleine Azar ◽  
Rebecca Bromwich ◽  
Andrea Lum ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Data Privacy ◽  
Ethical Issues ◽  
Expert Knowledge ◽  
Disease Diagnosis ◽  
White Paper ◽  
Imaging Features ◽  
Learning Approaches ◽  
Treatment Optimization ◽  
Canadian Association

Artificial intelligence (AI) software that analyzes medical images is becoming increasingly prevalent. Unlike earlier generations of AI software, which relied on expert knowledge to identify imaging features, machine learning approaches automatically learn to recognize these features. However, the promise of accurate personalized medicine can only be fulfilled with access to large quantities of medical data from patients. This data could be used for purposes such as predicting disease, diagnosis, treatment optimization, and prognostication. Radiology is positioned to lead development and implementation of AI algorithms and to manage the associated ethical and legal challenges. This white paper from the Canadian Association of Radiologists provides a framework for study of the legal and ethical issues related to AI in medical imaging, related to patient data (privacy, confidentiality, ownership, and sharing); algorithms (levels of autonomy, liability, and jurisprudence); practice (best practices and current legal framework); and finally, opportunities in AI from the perspective of a universal health care system.

scholarly journals Challenges of consumer protection regarding artificial intelligence

2021 ◽  
Vol 11 (5) ◽  
pp. 325-331
Author(s):  
Ibolya Stefán
Keyword(s):  
Artificial Intelligence ◽  
European Union ◽  
Data Storage ◽  
Consumer Protection ◽  
Data Protection ◽  
White Paper ◽  
The European Union ◽  
Computing Power ◽  
The Past ◽  
Digital Era

Artificial intelligence has gained more significance in the past few years because of the advanced algorithms, increased data storage and computing power. On the contrary, the novelty has several disadvantages, such as lack of transparency or the possibility of data protection problems. Thereby, there is an urgent need to regulate it properly. As a result of the phenomenon, the European Commission has created a Proposal for a Regulation of the European Parliament and of the Council Laying Down Harmonised Rules on Artificial Intelligence and Amending Certain Union Legislative Act’ in order to protect EU citizens, consumers. The so-called ‘Artificial Intelligence Act’ highlights the importance of consumer protection, as it was established in a previous EU document, the White paper on Artificial Intelligence. This paper aims to examine the regulatory framework of AI on the level of the European Union and to describe the challenges of consumer protection in this new digital era.

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