scholarly journals A short guide for medical professionals in the era of artificial intelligence

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Bertalan Meskó ◽  
Marton Görög
Keyword(s):  
Artificial Intelligence ◽  
Medical Professional ◽  
Clinical Validation ◽  
Delivery Of Healthcare ◽  
Practice Of Medicine ◽  
Potential Benefits ◽  
Definition Of ◽  
Near Future ◽  
News Headlines ◽  
Simple Definition

Abstract Artificial intelligence (A.I.) is expected to significantly influence the practice of medicine and the delivery of healthcare in the near future. While there are only a handful of practical examples for its medical use with enough evidence, hype and attention around the topic are significant. There are so many papers, conference talks, misleading news headlines and study interpretations that a short and visual guide any medical professional can refer back to in their professional life might be useful. For this, it is critical that physicians understand the basics of the technology so they can see beyond the hype, evaluate A.I.-based studies and clinical validation; as well as acknowledge the limitations and opportunities of A.I. This paper aims to serve as a short, visual and digestible repository of information and details every physician might need to know in the age of A.I. We describe the simple definition of A.I., its levels, its methods, the differences between the methods with medical examples, the potential benefits, dangers, challenges of A.I., as well as attempt to provide a futuristic vision about using it in an everyday medical practice.

The Rise and Application of Artificial Intelligence in Healthcare

2021 ◽  
pp. 28-49
Author(s):  
Ivan Khoo Yi ◽  
Andrew Fang Hao Sen
Keyword(s):  
Artificial Intelligence ◽  
Financial Institutions ◽  
Molecular Level ◽  
Healthcare Providers ◽  
Pharmaceutical Companies ◽  
Healthcare Industry ◽  
Practice Of Medicine ◽  
Potential Benefits ◽  
Legal Professional ◽  
Medical Domain

The overall purpose of this chapter will be to broadly explore both the existing and possible implementations of artificial intelligence (AI) in healthcare. The scope of this chapter will be explored from the unique perspectives of various stakeholders in the healthcare industry, namely the healthcare providers, patients, pharmaceutical companies, healthcare financial institutions, and policymakers. The chapter will seek to identify the potential benefits and pitfalls that faced by these stakeholders in implementing the use of AI, from the molecular level to a macroeconomics level; as well as seeking to understand the legal, professional, and ethical boundaries of the medical domain that are challenged as AI increasingly becomes irreversibly intertwined with the practice of medicine.

scholarly journals Promises and Perils of Artificial Intelligence in Neurosurgery

Neurosurgery ◽  
2019 ◽  
Vol 87 (1) ◽  
pp. 33-44 ◽  
Author(s):  
Sandip S Panesar ◽  
Michel Kliot ◽  
Rob Parrish ◽  
Juan Fernandez-Miranda ◽  
Yvonne Cagle ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Clinical Workflow ◽  
Commercial Aviation ◽  
Healthcare Settings ◽  
Poor Understanding ◽  
Potential Benefits ◽  
Wide Scale ◽  
Near Future

Abstract Artificial intelligence (AI)-facilitated clinical automation is expected to become increasingly prevalent in the near future. AI techniques may permit rapid and detailed analysis of the large quantities of clinical data generated in modern healthcare settings, at a level that is otherwise impossible by humans. Subsequently, AI may enhance clinical practice by pushing the limits of diagnostics, clinical decision making, and prognostication. Moreover, if combined with surgical robotics and other surgical adjuncts such as image guidance, AI may find its way into the operating room and permit more accurate interventions, with fewer errors. Despite the considerable hype surrounding the impending medical AI revolution, little has been written about potential downsides to increasing clinical automation. These may include both direct and indirect consequences. Directly, faulty, inadequately trained, or poorly understood algorithms may produce erroneous results, which may have wide-scale impact. Indirectly, increasing use of automation may exacerbate de-skilling of human physicians due to over-reliance, poor understanding, overconfidence, and lack of necessary vigilance of an automated clinical workflow. Many of these negative phenomena have already been witnessed in other industries that have already undergone, or are undergoing “automation revolutions,” namely commercial aviation and the automotive industry. This narrative review explores the potential benefits and consequences of the anticipated medical AI revolution from a neurosurgical perspective.

scholarly journals Transporting an Artificial Intelligence Model to Predict Emergency Cesarean Delivery: Overcoming Challenges Posed by Interfacility Variation (Preprint)

2021 ◽  
Author(s):  
Joshua Guedalia ◽  
Michal Lipschuetz ◽  
Sarah M Cohen ◽  
Yishai Sompolinsky ◽  
Asnat Walfisch ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Cesarean Delivery ◽  
Delivery Of Health Care ◽  
Health Care Facilities ◽  
Reporting Practices ◽  
Emergency Cesarean ◽  
Practice Of Medicine ◽  
Care Facilities ◽  
Near Future

UNSTRUCTURED Research using artificial intelligence (AI) in medicine is expected to significantly influence the practice of medicine and the delivery of health care in the near future. However, for successful deployment, the results must be transported across health care facilities. We present a cross-facilities application of an AI model that predicts the need for an emergency caesarean during birth. The transported model showed benefit; however, there can be challenges associated with interfacility variation in reporting practices.

scholarly journals Emergent Bioanalogous Properties of Blockchain-based Distributed Systems

2021 ◽  
Author(s):  
Oleg Abramov ◽  
Kirstin L. Bebell ◽  
Stephen J. Mojzsis
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Artificial Neural Network ◽  
General Intelligence ◽  
Definitions Of Life ◽  
Growth And Change ◽  
Artificial Neural Network Ann ◽  
Definition Of ◽  
Speed Accuracy ◽  
Near Future

AbstractWe apply a novel definition of biological systems to a series of reproducible observations on a blockchain-based distributed virtual machine (dVM). We find that such blockchain-based systems display a number of bioanalogous properties, such as response to the environment, growth and change, replication, and homeostasis, that fit some definitions of life. We further present a conceptual model for a simple self-sustaining, self-organizing, self-regulating distributed ‘organism’ as an operationally closed system that would fulfill all basic definitions and criteria for life, and describe developing technologies, particularly artificial neural network (ANN) based artificial intelligence (AI), that would enable it in the near future. Notably, such systems would have a number of specific advantages over biological life, such as the ability to pass acquired traits to offspring, significantly improved speed, accuracy, and redundancy of their genetic carrier, and potentially unlimited lifespans. Public blockchain-based dVMs provide an uncontained environment for the development of artificial general intelligence (AGI) with the capability to evolve by self-direction.

A SYSTEM FOR LOGIC-BASED INTELLIGENT VIRTUAL AGENTS

2004 ◽  
Vol 13 (03) ◽  
pp. 593-621 ◽  
Author(s):  
G. ANASTASSAKIS ◽  
T. PANAYIOTOPOULOS
Keyword(s):  
Artificial Intelligence ◽  
Virtual Environments ◽  
Intelligent Agent ◽  
Virtual Agents ◽  
Agent System ◽  
Intelligent Virtual Agents ◽  
Potential Benefits ◽  
Evaluation Stage ◽  
Educational Applications ◽  
Definition Of

Combination of logic-based artificial intelligence with virtual reality in intelligent agent systems is an approach not extensively sought after to date. It is our belief that significant gain is to be expected if the technical challenges involved are overcome. In this paper, we describe the mVlTAL intelligent agent system, which is our latest effort towards this direction. The system is a contemporary intelligent agent system with applications in numerous areas, including intelligent virtual environments and formal artificial intelligence research. The system focuses largely on logic-based approaches, which are present in almost every aspect of it, including modeling, knowledge representation, definition of agent behaviors and inter-agent communication. In addition, virtual manifestation of the world and agents is also an inherent characteristic of the system. The system, even if still in a development and evaluation stage, has already been employed in experimental and educational applications, demonstrating the potential benefits of such an approach.

scholarly journals Transporting an Artificial Intelligence Model to Predict Emergency Cesarean Delivery: Overcoming Challenges Posed by Interfacility Variation

10.2196/28120 ◽  
2021 ◽  
Vol 23 (12) ◽  
pp. e28120
Author(s):  
Joshua Guedalia ◽  
Michal Lipschuetz ◽  
Sarah M Cohen ◽  
Yishai Sompolinsky ◽  
Asnat Walfisch ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Cesarean Delivery ◽  
Delivery Of Health Care ◽  
Health Care Facilities ◽  
Reporting Practices ◽  
Emergency Cesarean ◽  
Practice Of Medicine ◽  
Care Facilities ◽  
Near Future

Research using artificial intelligence (AI) in medicine is expected to significantly influence the practice of medicine and the delivery of health care in the near future. However, for successful deployment, the results must be transported across health care facilities. We present a cross-facilities application of an AI model that predicts the need for an emergency caesarean during birth. The transported model showed benefit; however, there can be challenges associated with interfacility variation in reporting practices.

Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey (Preprint)

2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Online Survey ◽  
Medical Professionals ◽  
Medical Field ◽  
Acceptance Level ◽  
Professional Workers ◽  
Basic Understanding ◽  
Comparative Survey ◽  
Definition Of

BACKGROUND Artificial intelligence (AI) is widely applied in the medical field, especially in ophthalmology. In the development of ophthalmic artificial intelligence, some problems worthy of attention have gradually emerged, among which the ophthalmic AI-related recognition issues are particularly prominent. That is to say, currently, there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. OBJECTIVE This survey aims to assess medical workers’ and other professional technicians’ familiarity with AI, as well as their attitudes toward and concerns of ophthalmic AI. METHODS An electronic questionnaire was designed through the Questionnaire Star APP, an online survey software and questionnaire tool, and was sent to relevant professional workers through Wechat, China’s version of Facebook or WhatsApp. The participation was based on a voluntary and anonymous principle. The questionnaire mainly consisted of four parts, namely the participant’s background, the participant's basic understanding of AI, the participant's attitude toward AI, and the participant's concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS A total of 562 professional workers completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 37.9% of the participants understood AI, and 31.67% understood ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that ophthalmic AI would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with ophthalmic AI application experiences (30.6%), respectively about 84.25% of medical professionals and 73.33% of other professional technicians held a full acceptance attitude toward ophthalmic AI. The participants expressed concerns that ophthalmic AI might bring about issues such as the unclear definition of medical responsibilities, the difficulty of ensuring service quality, and the medical ethics risks. And among the medical workers and other professional technicians who understood ophthalmic AI, 98.39%, and 95.24%, respectively, said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS Analysis of the questionnaire results shows that the medical workers have a higher understanding level of ophthalmic AI than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI, but generally had a relatively high acceptance level of ophthalmic AI, believing that doctors would partly be replaced by it and that there was a need to strengthen research into medical ethics issues of the field.

Health, Illness, and Disease

2018 ◽  
Author(s):  
J. Donald Boudreau ◽  
Eric J. Cassell ◽  
Abraham Fuks
Keyword(s):  
Medical Education ◽  
Practice Of Medicine ◽  
Definition Of ◽  
Contemporary Practice ◽  
Illness And Disease ◽  
Negative Sense

This introduction discusses traditional meanings of the following concepts: health, sickness, disease, suffering, and healing. The point is made that “disease” is an abstract phenomenon, albeit one that is critically important to the contemporary practice of medicine. Unfortunately, the term disease has often come to occupy the center of physicians’ preoccupations. Currently, health is considered in a negative sense, as an “absence of disease.” This chapter proposes a new and bold definition of sickness, one that revolves around the notion of function. This opens up possibilities for the goals of physicians and for medical education to be truly person centered.

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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