scholarly journals Digital Health Technologies and Artificial Intelligence in the Islamic World: Embracing the Evolution in Healthcare

2021 ◽  
Vol 6 ◽  
Author(s):  
Muhammad Salman Khan ◽  
Hinna Nayab
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
New Technologies ◽  
Wide Spectrum ◽  
Digital Health ◽  
Economic Status ◽  
Healthcare Systems ◽  
Medical Data ◽  
Disease Prediction ◽  
Health Technologies

Health and Healthcare have been highly impacted by the global technological revolution resulting in more intelligent systems, optimised hospital workflows, disease prediction and analytics, precision medicine and personalised patient experience. Digital health offers a wide spectrum with artificial intelligence at the far-end having a significant influence on the healthcare systems and medical practice. Artificial intelligence makes sense of the large volumes of medical data through efficient algorithms, thus transforming healthcare systems. But, has the Muslim world been up to date with the advancements in healthcare? This detailed study presents the importance of adopting and adapting to the new technologies in the field of medicine, taking into consideration that Muslim scientists were, in fact, pioneers in the field, carving new medical techniques. The significance of digital health technologies and artificial intelligence in healthcare is also supported by various issues in Muslim societies related to cross-gender patient-doctor interactions, lack of resources, inefficient healthcare systems, and poor socio-economic status. This study concludes with examples of research studies being carried out in the fields of cardiology, haematology, and radiology where algorithms and systems are developed that enable physicians to perform their job with more ease and higher precision.

scholarly journals The Real Era of the Art of Medicine Begins with Artificial Intelligence (Preprint)

2019 ◽  
Author(s):  
Bertalan Meskó
Keyword(s):  
Artificial Intelligence ◽  
Digital Health ◽  
Medical Science ◽  
Three Dimensional ◽  
Three Dimensional Printing ◽  
The Real ◽  
Art Of Medicine ◽  
Health Technologies ◽  
Based Medicine ◽  
Dimensional Printing

UNSTRUCTURED Physicians have been performing the art of medicine for hundreds of years, and since the ancient era, patients have turned to physicians for help, advice, and cures. When the fathers of medicine started writing down their experience, knowledge, and observations, treating medical conditions became a structured process, with textbooks and professors sharing their methods over generations. After evidence-based medicine was established as the new form of medical science, the art and science of medicine had to be connected. As a result, by the end of the 20th century, health care had become highly dependent on technology. From electronic medical records, telemedicine, three-dimensional printing, algorithms, and sensors, technology has started to influence medical decisions and the lives of patients. While digital health technologies might be considered a threat to the art of medicine, I argue that advanced technologies, such as artificial intelligence, will initiate the real era of the art of medicine. Through the use of reinforcement learning, artificial intelligence could become the stethoscope of the 21st century. If we embrace these tools, the real art of medicine will begin now with the era of artificial intelligence.

Argument Structure Models and Visualization

2009 ◽  
pp. 75-82 ◽  
Author(s):  
Ephraim Nissan
Keyword(s):  
Artificial Intelligence ◽  
Argument Structure ◽  
Intelligent Systems ◽  
Computational Models ◽  
Ad Hoc ◽  
Wide Spectrum ◽  
Tutoring Systems ◽  
Computer Tools ◽  
Legal Evidence ◽  
Visualization Tools

In order to visualize argumentation, there exist tools from multimedia. The most advanced sides of computational modeling of arguments belong in models and tools upstream of visualization tools: the latter are an interface. Computer models of argumentation come in three categories: logic-based (highly theoretical), probablistic, and pragmatic ad hoc treatments. Theoretical formalisms of argumentation were developed by logicists within artificial intelligence (and were implemented and often can be reused outside the original applications), or then the formalisms are rooted in philosophers’ work. We cite some such work, but focus on tools that support argumentation visually. Argumentation turns out in a wide spectrum of everyday life situations, including professional ones. Computational models of argumentation have found application in tutoring systems, tools for marshalling legal evidence, and models of multiagent communication. Intelligent systems and other computer tools potentially stand to benefit as well. Multimedia are applied to argumentation (in visualization tools), and also are a promising field of application (in tutoring systems). The design of networks could potentially benefit, if communication is modeled using multiagent technology.

Clinical Integration of Digital Solutions in Health Care: An Overview of the Current Landscape of Digital Technologies in Cancer Care

2018 ◽  
pp. 1-9 ◽  
Author(s):  
Shivank Garg ◽  
Noelle L. Williams ◽  
Andrew Ip ◽  
Adam P. Dicker
Keyword(s):  
Quality Of Life ◽  
Artificial Intelligence ◽  
Health Care ◽  
Data Collection ◽  
Patient Outcomes ◽  
Cancer Care ◽  
Digital Health ◽  
Health Technologies ◽  
Health Care Value

Digital health constitutes a merger of both software and hardware technology with health care delivery and management, and encompasses a number of domains, from wearable devices to artificial intelligence, each associated with widely disparate interaction and data collection models. In this review, we focus on the landscape of the current integration of digital health technology in cancer care by subdividing digital health technologies into the following sections: connected devices, digital patient information collection, telehealth, and digital assistants. In these sections, we give an overview of the potential clinical impact of such technologies as they pertain to key domains, including patient education, patient outcomes, quality of life, and health care value. We performed a search of PubMed ( www.ncbi.nlm.nih.gov/pubmed ) and www.ClinicalTrials.gov for numerous terms related to digital health technologies, including digital health, connected devices, smart devices, wearables, activity trackers, connected sensors, remote monitoring, electronic surveys, electronic patient-reported outcomes, telehealth, telemedicine, artificial intelligence, chatbot, and digital assistants. The terms health care and cancer were appended to the previously mentioned terms to filter results for cancer-specific applications. From these results, studies were included that exemplified use of the various domains of digital health technologies in oncologic care. Digital health encompasses the integration of a vast array of technologies with health care, each associated with varied methods of data collection and information flow. Integration of these technologies into clinical practice has seen applications throughout the spectrum of care, including cancer screening, on-treatment patient management, acute post-treatment follow-up, and survivorship. Implementation of these systems may serve to reduce costs and workflow inefficiencies, as well as to improve overall health care value, patient outcomes, and quality of life.

scholarly journals Accounting Practice and Intelligent Technologies

2012 ◽  
Author(s):  
Daniela Postolache (Males)
Keyword(s):  
Artificial Intelligence ◽  
Information Technology ◽  
Technology Management ◽  
Intelligent Systems ◽  
New Technologies ◽  
Accounting Information ◽  
Qualitative Approach ◽  
Information Technology Management ◽  
Accounting Practice ◽  
Area Of Interest

was to determine how intelligent technologies can support accounting practice. Our research allowed for establishment of accounting information intelligent systems typology and for placement of these solutions in the sphere of artificial intelligence applications. It is underlined the intelligent technologies contribution to improve accounting processes and activities, in a qualitative approach, from the hermeneutic perspective. The results of our research are useful for researchers in the fields of applied accounting, intelligent systems for accounting, information technology management. Also, our study is useful in the activity of accounting experts, given the presentation of new technologies used in their area of interest.

scholarly journals Artificial Intelligence in Politics, Media and Public Administration: Reflections on the Thematic Portfolio

2020 ◽  
Vol 4 (2) ◽  
pp. 3-9
Author(s):  
Sergey Fedorchenko
Keyword(s):  
Artificial Intelligence ◽  
Political Science ◽  
Public Administration ◽  
Soft Power ◽  
Intelligent Systems ◽  
New Technologies ◽  
Scientific Discourse ◽  
Political Regime ◽  
Political Agenda ◽  
The Political

The issue «Artificial Intelligence in the Sphere of Politics, Media Space and Public Administration» was conceived after updating the topic of artificial intelligence in the socio-political and value sphere at several scientific events organized by the Department of History, Political Science and Law of Moscow Region State University: Scientific and Public Forum «Values and artificial intelligence» (10.11.2019) and the round table «Ethics and artificial intelligence» (04.16.2019). This issue includes works devoted to the issues of the practice of artificial intelligence in public administration, public policy and other fields. The authors also touched on the nuances of scientific discourse and futorology. The compiler of the issue is Candidate of Political Sciences, associate professor Fedorchenko Sergey Nikolaevich. Artificial intelligence technologies are a pretty debatable topic. Artificial intelligence technologies are a pretty debatable topic. Currently, political leaders, scientists and members of the public are actively discussing the problems of artificial intelligence related to the following aspects: new opportunities for political communication; media policy, mediation of the political sphere; axiological policy; social networks, bots; government departments; opportunities and limitations of new technologies in political analysis; the importance of intelligent systems for democracy and democratic procedures; threats of cyber autocracy; legitimacy of the political regime and national security; political values, political propaganda, frames, political myths, stereotypes, «soft power», «smart power»; digital diplomacy; the risks of media manipulation, information wars, the formation of a political agenda; experience of using intelligent systems in the organization of high-quality communication between society and the state. The theme of the issue is extremely relevant for modern academic political science. artificial intelligence, digitalization, political science, scientific discourse, futorology, state, democracy, manipulation, political communications. The issue is aimed at specialists, political scientists, graduate students and all those who are interested in this difficult issue in an interdisciplinary manner.

scholarly journals The potential use of digital health technologies in the African context: a systematic review of evidence from Ethiopia

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Tsegahun Manyazewal ◽  
Yimtubezinash Woldeamanuel ◽  
Henry M. Blumberg ◽  
Abebaw Fekadu ◽  
Vincent C. Marconi
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Systematic Review ◽  
Digital Health ◽  
Global Strategy ◽  
Health Conditions ◽  
Health Practices ◽  
Health Technologies ◽  
Link Type ◽  
Potential Use

AbstractThe World Health Organization (WHO) recently put forth a Global Strategy on Digital Health 2020–2025 with several countries having already achieved key milestones. We aimed to understand whether and how digital health technologies (DHTs) are absorbed in Africa, tracking Ethiopia as a key node. We conducted a systematic review, searching PubMed-MEDLINE, Embase, ScienceDirect, African Journals Online, Cochrane Central Registry of Controlled Trials, ClinicalTrials.gov, and the WHO International Clinical Trials Registry Platform databases from inception to 02 February 2021 for studies of any design that investigated the potential of DHTs in clinical or public health practices in Ethiopia. This review was registered with PROSPERO (CRD42021240645) and it was designed to inform our ongoing DHT-enabled randomized controlled trial (RCT) (ClinicalTrials.gov ID: NCT04216420). We found 27,493 potentially relevant citations, among which 52 studies met the inclusion criteria, comprising a total of 596,128 patients, healthy individuals, and healthcare professionals. The studies involved six DHTs: mHealth (29 studies, 574,649 participants); electronic health records (13 studies, 4534 participants); telemedicine (4 studies, 465 participants); cloud-based application (2 studies, 2382 participants); information communication technology (3 studies, 681 participants), and artificial intelligence (1 study, 13,417 participants). The studies targeted six health conditions: maternal and child health (15), infectious diseases (14), non-communicable diseases (3), dermatitis (1), surgery (4), and general health conditions (15). The outcomes of interest were feasibility, usability, willingness or readiness, effectiveness, quality improvement, and knowledge or attitude toward DHTs. Five studies involved RCTs. The analysis showed that although DHTs are a relatively recent phenomenon in Ethiopia, their potential harnessing clinical and public health practices are highly visible. Their adoption and implementation in full capacity require more training, access to better devices such as smartphones, and infrastructure. DHTs hold much promise tackling major clinical and public health backlogs and strengthening the healthcare ecosystem in Ethiopia. More RCTs are needed on emerging DHTs including artificial intelligence, big data, cloud, cybersecurity, telemedicine, and wearable devices to provide robust evidence of their potential use in such settings and to materialize the WHO’s Global Strategy on Digital Health.

scholarly journals Prediction of a Ship’s Operational Parameters Using Artificial Intelligence Techniques

2021 ◽  
Vol 9 (6) ◽  
pp. 681
Author(s):  
Kiriakos Alexiou ◽  
Efthimios G. Pariotis ◽  
Theodoros C. Zannis ◽  
Helen C. Leligou
Keyword(s):  
Artificial Intelligence ◽  
Intelligent Systems ◽  
New Technologies ◽  
Operating Costs ◽  
Maritime Industry ◽  
Data Logging ◽  
K Nearest Neighbor ◽  
Operational Parameters ◽  
Maximum Absolute Error ◽  
Regression Algorithms

The maritime industry is one of the most competitive industries today. However, there is a tendency for the profit margins of shipping companies to reduce due to an increase in operational costs, and it does not seem that this trend will change in the near future. The most important reason for the increase in operating costs relates to the increase in fuel prices. To compensate for the increase in operating costs, shipping companies can either renew their fleet or try to make use of new technologies to optimize the performance of their existing one. The software structure in the maritime industry has changed and is now leaning towards the use of Artificial Intelligence (AI) and, more specifically, Machine Learning (ML) for calculating its operational scenarios as a way to compensate the reduction of profit. While AI is a technology for creating intelligent systems that can simulate human intelligence, ML is a subfield of AI, which enables machines to learn from past data without being explicitly programmed. ML has been used in other industries for increasing both availability and profitability, and it seems that there is also great potential for the maritime industry. In this paper the authors compares the performance of multiple regression algorithms like Artificial Neural Network (ANN), Tree Regressor (TRs), Random Forest Regressor (RFR), K-Nearest Neighbor (kNN), Linear Regression, and AdaBoost, in predicting the output power of the Main Engines (M/E) of an ocean going vessel. These regression algorithms are selected because they are commonly used and are well supported by the main software developers in the area of ML. For this scope, measured values that are collected from the onboard Automated Data Logging & Monitoring (ADLM) system of the vessel for a period of six months have been used. The study shows that ML, with the proper processing of the measured parameters based on fundamental knowledge of naval architecture, can achieve remarkable prediction results. With the use of the proposed method there was a vast reduction in both the computational power needed for calculations, and the maximum absolute error value of prediction.

scholarly journals Predicted Influences of Artificial Intelligence on the Domains of Nursing: Scoping Review (Preprint)

2020 ◽  
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health System ◽  
Scoping Review ◽  
Predictive Analytics ◽  
Digital Health ◽  
Shared Responsibility ◽  
Compassionate Care ◽  
Health Technologies ◽  
Emerging Trends ◽  
Research Questions

BACKGROUND Artificial intelligence (AI) is set to transform the health system, yet little research to date has explored its influence on nurses—the largest group of health professionals. Furthermore, there has been little discussion on how AI will influence the experience of person-centered compassionate care for patients, families, and caregivers. OBJECTIVE This review aims to summarize the extant literature on the emerging trends in health technologies powered by AI and their implications on the following domains of nursing: administration, clinical practice, policy, and research. This review summarizes the findings from 3 research questions, examining how these emerging trends might influence the roles and functions of nurses and compassionate nursing care over the next 10 years and beyond. METHODS Using an established scoping review methodology, MEDLINE, CINAHL, EMBASE, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Center, Scopus, Web of Science, and ProQuest databases were searched. In addition to the electronic database searches, a targeted website search was performed to access relevant gray literature. Abstracts and full-text studies were independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included articles focused on nursing and digital health technologies that incorporate AI. Data were charted using structured forms and narratively summarized. RESULTS A total of 131 articles were retrieved from the scoping review for the 3 research questions that were the focus of this manuscript (118 from database sources and 13 from targeted websites). Emerging AI technologies discussed in the review included predictive analytics, smart homes, virtual health care assistants, and robots. The results indicated that AI has already begun to influence nursing roles, workflows, and the nurse-patient relationship. In general, robots are not viewed as replacements for nurses. There is a consensus that health technologies powered by AI may have the potential to enhance nursing practice. Consequently, nurses must proactively define how person-centered compassionate care will be preserved in the age of AI. CONCLUSIONS Nurses have a shared responsibility to influence decisions related to the integration of AI into the health system and to ensure that this change is introduced in a way that is ethical and aligns with core nursing values such as compassionate care. Furthermore, nurses must advocate for patient and nursing involvement in all aspects of the design, implementation, and evaluation of these technologies. INTERNATIONAL REGISTERED REPORT RR2-10.2196/17490

scholarly journals Nursing in the Age of Artificial Intelligence: Protocol for a Scoping Review

10.2196/17490 ◽  
2020 ◽  
Vol 9 (4) ◽  
pp. e17490 ◽  
Author(s):  
Christine Buchanan ◽  
M Lyndsay Howitt ◽  
Rita Wilson ◽  
Richard G Booth ◽  
Tracie Risling ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Education Policy ◽  
Scoping Review ◽  
Digital Health ◽  
Clinical Care ◽  
Electronic Database ◽  
Health Technologies ◽  
Care Education ◽  
Emerging Trends ◽  
Briefing Paper

Background It is predicted that digital health technologies that incorporate artificial intelligence will transform health care delivery in the next decade. Little research has explored how emerging trends in artificial intelligence–driven digital health technologies may influence the relationship between nurses and patients. Objective The purpose of this scoping review is to summarize the findings from 4 research questions regarding emerging trends in artificial intelligence–driven digital health technologies and their influence on nursing practice across the 5 domains outlined by the Canadian Nurses Association framework: administration, clinical care, education, policy, and research. Specifically, this scoping review will examine how emerging trends will transform the roles and functions of nurses over the next 10 years and beyond. Methods Using an established scoping review methodology, MEDLINE, Cumulative Index to Nursing and Allied Health Literature, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane Central, Education Resources Information Centre, Scopus, Web of Science, and Proquest databases were searched. In addition to the electronic database searches, a targeted website search will be performed to access relevant grey literature. Abstracts and full-text studies will be independently screened by 2 reviewers using prespecified inclusion and exclusion criteria. Included literature will focus on nursing and digital health technologies that incorporate artificial intelligence. Data will be charted using a structured form and narratively summarized. Results Electronic database searches have retrieved 10,318 results. The scoping review and subsequent briefing paper will be completed by the fall of 2020. Conclusions A symposium will be held to share insights gained from this scoping review with key thought leaders and a cross section of stakeholders from administration, clinical care, education, policy, and research as well as patient advocates. The symposium will provide a forum to explore opportunities for action to advance the future of nursing in a technological world and, more specifically, nurses’ delivery of compassionate care in the age of artificial intelligence. Results from the symposium will be summarized in the form of a briefing paper and widely disseminated to relevant stakeholders. International Registered Report Identifier (IRRID) DERR1-10.2196/17490

scholarly journals Big Data and the Threat to Moral Responsibility in Healthcare

2021 ◽  
pp. 11-25
Author(s):  
Daniel W. Tigard
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Moral Responsibility ◽  
Intelligent Systems ◽  
Healthcare Systems ◽  
Ethical Challenges ◽  
Trade Offs ◽  
The Social ◽  
Healthcare Technologies

AbstractTechnological innovations in healthcare, perhaps now more than ever, are posing decisive opportunities for improvements in diagnostics, treatment, and overall quality of life. The use of artificial intelligence and big data processing, in particular, stands to revolutionize healthcare systems as we once knew them. But what effect do these technologies have on human agency and moral responsibility in healthcare? How can patients, practitioners, and the general public best respond to potential obscurities in responsibility? In this paper, I investigate the social and ethical challenges arising with newfound medical technologies, specifically the ways in which artificially intelligent systems may be threatening moral responsibility in the delivery of healthcare. I argue that if our ability to locate responsibility becomes threatened, we are left with a difficult choice of trade-offs. In short, it might seem that we should exercise extreme caution or even restraint in our use of state-of-the-art systems, but thereby lose out on such benefits as improved quality of care. Alternatively, we could embrace novel healthcare technologies but in doing so we might need to loosen our commitment to locating moral responsibility when patients come to harm; for even if harms are fewer – say, as a result of data-driven diagnostics – it may be unclear who or what is responsible when things go wrong. What is clear, at least, is that the shift toward artificial intelligence and big data calls for significant revisions in expectations on how, if at all, we might locate notions of responsibility in emerging models of healthcare.

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