scholarly journals Artificial Intelligence–Aided Precision Medicine for COVID-19: Strategic Areas of Research and Development

10.2196/22453 ◽  
2021 ◽  
Vol 23 (3) ◽  
pp. e22453 ◽  
Author(s):  
Enrico Santus ◽  
Nicola Marino ◽  
Davide Cirillo ◽  
Emmanuele Chersoni ◽  
Arnau Montagud ◽  
...  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Health Care ◽  
Research And Development ◽  
Precision Medicine ◽  
Patient Outcomes ◽  
Medical Literature ◽  
Drug Repurposing ◽  
Public Health Systems ◽  
Improve Patient

Artificial intelligence (AI) technologies can play a key role in preventing, detecting, and monitoring epidemics. In this paper, we provide an overview of the recently published literature on the COVID-19 pandemic in four strategic areas: (1) triage, diagnosis, and risk prediction; (2) drug repurposing and development; (3) pharmacogenomics and vaccines; and (4) mining of the medical literature. We highlight how AI-powered health care can enable public health systems to efficiently handle future outbreaks and improve patient outcomes.

scholarly journals Artificial Intelligence–Aided Precision Medicine for COVID-19: Strategic Areas of Research and Development (Preprint)

2020 ◽  
Author(s):  
Enrico Santus ◽  
Nicola Marino ◽  
Davide Cirillo ◽  
Emmanuele Chersoni ◽  
Arnau Montagud ◽  
...  
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Health Care ◽  
Research And Development ◽  
Precision Medicine ◽  
Patient Outcomes ◽  
Medical Literature ◽  
Drug Repurposing ◽  
Public Health Systems ◽  
Improve Patient

UNSTRUCTURED Artificial intelligence (AI) technologies can play a key role in preventing, detecting, and monitoring epidemics. In this paper, we provide an overview of the recently published literature on the COVID-19 pandemic in four strategic areas: (1) triage, diagnosis, and risk prediction; (2) drug repurposing and development; (3) pharmacogenomics and vaccines; and (4) mining of the medical literature. We highlight how AI-powered health care can enable public health systems to efficiently handle future outbreaks and improve patient outcomes.

scholarly journals Cochlear Implant Research and Development in the Twenty-first Century: A Critical Update

2021 ◽  
Vol 22 (5) ◽  
pp. 481-508
Author(s):  
Robert P. Carlyon ◽  
Tobias Goehring
Keyword(s):  
Research And Development ◽  
Patient Outcomes ◽  
Speech Processing ◽  
Turn Of The Century ◽  
First Century ◽  
Directional Microphones ◽  
Wide Range ◽  
The Subject ◽  
Processing Algorithms ◽  
Improve Patient

AbstractCochlear implants (CIs) are the world’s most successful sensory prosthesis and have been the subject of intense research and development in recent decades. We critically review the progress in CI research, and its success in improving patient outcomes, from the turn of the century to the present day. The review focuses on the processing, stimulation, and audiological methods that have been used to try to improve speech perception by human CI listeners, and on fundamental new insights in the response of the auditory system to electrical stimulation. The introduction of directional microphones and of new noise reduction and pre-processing algorithms has produced robust and sometimes substantial improvements. Novel speech-processing algorithms, the use of current-focusing methods, and individualised (patient-by-patient) deactivation of subsets of electrodes have produced more modest improvements. We argue that incremental advances have and will continue to be made, that collectively these may substantially improve patient outcomes, but that the modest size of each individual advance will require greater attention to experimental design and power. We also briefly discuss the potential and limitations of promising technologies that are currently being developed in animal models, and suggest strategies for researchers to collectively maximise the potential of CIs to improve hearing in a wide range of listening situations.

scholarly journals Will Artificial Intelligence Replace the Movement Disorders Specialist for Diagnosing and Managing Parkinson’s Disease?

2021 ◽  
pp. 1-6
Author(s):  
Matt Landers ◽  
Suchi Saria ◽  
Alberto J. Espay
Keyword(s):  
Artificial Intelligence ◽  
Parkinson’S Disease ◽  
Parkinson's Disease ◽  
Precision Medicine ◽  
Movement Disorders ◽  
Living Environment ◽  
Patient Status ◽  
Patient Symptom ◽  
Molecular Therapies ◽  
Improve Patient

The use of artificial intelligence (AI) to help diagnose and manage disease is of increasing interest to researchers and clinicians. Volumes of health data are generated from smartphones and ubiquitous inexpensive sensors. By using these data, AI can offer otherwise unobtainable insights about disease burden and patient status in a free-living environment. Moreover, from clinical datasets AI can improve patient symptom monitoring and global epidemiologic efforts. While these applications are exciting, it is necessary to examine both the utility and limitations of these novel analytic methods. The most promising uses of AI remain aspirational. For example, defining the molecular subtypes of Parkinson’s disease will be assisted by future applications of AI to relevant datasets. This will allow clinicians to match patients to molecular therapies and will thus help launch precision medicine. Until AI proves its potential in pushing the frontier of precision medicine, its utility will primarily remain in individualized monitoring, complementing but not replacing movement disorders specialists.

scholarly journals Modeling Research Topics for Artificial Intelligence Applications in Medicine: Latent Dirichlet Allocation Application Study

10.2196/15511 ◽  
2019 ◽  
Vol 21 (11) ◽  
pp. e15511 ◽  
Author(s):  
Bach Xuan Tran ◽  
Son Nghiem ◽  
Oz Sahin ◽  
Tuan Manh Vu ◽  
Giang Hai Ha ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Health Care ◽  
Precision Medicine ◽  
Data Science ◽  
Latent Dirichlet Allocation ◽  
Developed Countries ◽  
Theory And Practice ◽  
Clinical Practices ◽  
Research Topics ◽  
Dirichlet Allocation

Background Artificial intelligence (AI)–based technologies develop rapidly and have myriad applications in medicine and health care. However, there is a lack of comprehensive reporting on the productivity, workflow, topics, and research landscape of AI in this field. Objective This study aimed to evaluate the global development of scientific publications and constructed interdisciplinary research topics on the theory and practice of AI in medicine from 1977 to 2018. Methods We obtained bibliographic data and abstract contents of publications published between 1977 and 2018 from the Web of Science database. A total of 27,451 eligible articles were analyzed. Research topics were classified by latent Dirichlet allocation, and principal component analysis was used to identify the construct of the research landscape. Results The applications of AI have mainly impacted clinical settings (enhanced prognosis and diagnosis, robot-assisted surgery, and rehabilitation), data science and precision medicine (collecting individual data for precision medicine), and policy making (raising ethical and legal issues, especially regarding privacy and confidentiality of data). However, AI applications have not been commonly used in resource-poor settings due to the limit in infrastructure and human resources. Conclusions The application of AI in medicine has grown rapidly and focuses on three leading platforms: clinical practices, clinical material, and policies. AI might be one of the methods to narrow down the inequality in health care and medicine between developing and developed countries. Technology transfer and support from developed countries are essential measures for the advancement of AI application in health care in developing countries.

scholarly journals 人工智能醫學應用的前景與風險

2019 ◽  
Vol 17 (2) ◽  
pp. 79-109
Author(s):  
Robert SPARROW ◽  
Joshua HATHERLEY
Keyword(s):  
Public Health ◽  
Artificial Intelligence ◽  
Health Care ◽  
Healthcare Systems ◽  
Business Practices ◽  
Medical Decisions ◽  
Diagnostic Aid ◽  
Healthcare Settings ◽  
Digital Commons ◽  
Distribution Of Power

LANGUAGE NOTE | Document text in English; abstract also in Chinese.人工智能（ＡＩ）將如何促進人類的醫療保健？如果我們擔心人工智能介入醫療的風險，我們又應該關注什麽呢？本文試圖概述此類問題，並對人工智能介入醫療的風險與希望作一個初步評價。人工智能作為一種研究工具和診斷工具具有巨大的潛力，特別是在基因組學和公共衛生領域中。人工智能在醫療中的廣泛使用可能還會對醫療系統的組織方式和商業實踐產生深刻的影響，而這些影響的方式與程度還沒有被充分認識到。在人工智能醫學的熱情擁護者看來，應用人工智能可以幫助醫生集中精力在對他們和病人而言真正重要的問題上。然而，本文將論證這些樂觀的判斷是基於對現代醫療環境下機構和經濟運行規則的一些不合情理的假設之上。本文將聚焦於如下一 些重要議題：大資料中的隱私、監管和偏見，過分信任機器的風險，透明度問題，醫療專業人士的“去技能化”問題，人工智能重塑醫療保健的方式，以及人工智能對醫療保健中權力分配的影響。其中有兩個關鍵的問題尤其值得哲學家和生命倫理學家的進一步關注。第一，當醫生不僅需要處理人而且需要處理資料的時候，醫療實踐會呈現出什麽樣的形態？第二，在醫療決策權衡中，我們應該给予來自機器的意見以多大的權重？What does Artificial Intelligence (AI) have to contribute to health care? And what should we be looking out for if we are worried about its risks? In this paper we offer a survey, and initial evaluation, of hopes and fears about the applications of artificial intelligence in medicine. AI clearly has enormous potential as a research tool, in genomics and public health especially, as well as a diagnostic aid. It’s also highly likely to impact on the organisational and business practices of healthcare systems in ways that are perhaps under-appreciated. Enthusiasts for AI have held out the prospect that it will free physicians up to spend more time attending to what really matters to them and their patients. We will argue that this claim depends upon implausible assumptions about the institutional and economic imperatives operating in contemporary healthcare settings. We will also highlight important concerns about privacy, surveillance, and bias in big data, as well as the risks of over trust in machines, the challenges of transparency, the deskilling of healthcare practitioners, the way AI reframes healthcare, and the implications of AI for the distribution of power in healthcare institutions. We will suggest that two questions, in particular, are deserving of further attention from philosophers and bioethicists. What does care look like when one is dealing with data as much as people? And, what weight should we give to the advice of machines in our own deliberations about medical decisions?DOWNLOAD HISTORY | This article has been downloaded 119 times in Digital Commons before migrating into this platform.

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.

Are Transplant Centers That Meet Insurer Minimum Volume Requirements Better Quality?

2020 ◽  
pp. 107755872091927
Author(s):  
Lauren Hersch Nicholas ◽  
Sarah See Stith
Keyword(s):  
Health Care ◽  
Patient Outcomes ◽  
Health Care Services ◽  
Minimum Volume ◽  
Patient Volume ◽  
Care Services ◽  
Elective Surgical Procedures ◽  
Proxy Measure ◽  
Instrumental Variables Approach ◽  
Improve Patient

A pervasive viewpoint in health care is that higher patient volume leads to better outcomes, implying that facility volume can be used to identify high-quality providers. Hundreds of studies documenting a positive correlation between hospital volume and patient survival have motivated payers to use arbitrary minimum volume standards for elective surgical procedures, though it is unknown whether these policies actually improve patient outcomes. Using an instrumental variables approach, we show that minimum volume requirements in kidney transplantation do not reduce posttransplant mortality. These results suggest minimum volume requirements are not a useful proxy measure for quality and that restricting the number of hospitals from which patients can receive care could reduce access to necessary health care services.

scholarly journals How Structural Compensation Facilitates Health Care for the Homeless. A Comparative View on Four European Union Member States

2020 ◽  
Vol 17 (23) ◽  
pp. 9114
Author(s):  
Ursula Trummer ◽  
Sonja Novak-Zezula ◽  
Mariola Chrzanowska ◽  
Christos Michalakelis ◽  
Roido Mitoula ◽  
...  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Health Systems ◽  
Health Care Provision ◽  
Care Provision ◽  
Public Health Systems ◽  
Wide Range ◽  
Legal Frameworks ◽  
European Union Member States ◽  
Desk Research

There is robust evidence that homelessness and the associated life conditions of a homeless person may cause and exacerbate a wide range of health problems, while healthcare for the homeless is simultaneously limited in accessibility, availability, and appropriateness. This article investigates legal frameworks of health care provision, existing knowledge on numbers of homeless to be considered, and current means of health care provision for four EU countries with different economic and public health background: Austria, Greece, Poland, and Romania. National experts investigated the respective regulations and practices in place with desk research. The results show differences in national frameworks of inclusion into health care provision and knowledge on the number of people experiencing homelessness, but high similarity when it comes to main actors of actual health care provision for homeless populations. In all included countries, despite their differences in economic investments and universality of access to public health systems, it is mainly NGOs providing health care to those experiencing homelessness. This phenomenon fits into conceptual frameworks developed around service provision for vulnerable population groups, wherein it has been described as “structural compensation,” meaning that NGOs compensate a structural inappropriateness that can be observed within public health systems.

scholarly journals Workshop: Better prison health for better public health

2019 ◽  
Vol 29 (Supplement_4) ◽  
Author(s):  
Keyword(s):  
Public Health ◽  
Health Care ◽  
Drug Use ◽  
Prison Population ◽  
Community Services ◽  
Health Issues ◽  
Public Health Systems ◽  
Prison Health ◽  
Problem Drug Use ◽  
Problem Drug

Abstract According to the latest data, in 2018 about 590,000 people were held in prison on any given day in the EU, and more than double in the entire region. People in prison face multiple and complex health care issues, including a higher prevalence of communicable diseases than the general population. These are likely to be the result of a combination of overlapping, and sometimes interlinked, risk factors for infection, ill-health, and incarceration, such as problem drug use. Incarceration may facilitate the offer of quality health care services to people who are otherwise hard to reach and provide an occasion to target socially deprived groups who often have low level of healthcare access when in the community. Delivering health protection and harm reduction programmes in prisons not only benefits the prison population but also has the potential to reduce the risk of transmission of some infectious diseases in the community, intervening earlier in the natural history of disease. They are also likely also to have a knock-on effect in supporting individuals’ reintegration into community life and future health - providing a ‘community dividend’ to health interventions in prisons. Yet, such health gains may be diminished by suboptimal integration with community services. Continuity of care, or throughcare, between prison and community services is a mainstay of any health care interventions delivered in detention, especially when tackling chronic conditions (e.g. HIV, mental illnesses) or problem drug use. The World Health Organization (WHO) has long supported the concept of prison health as an inseparable component of public health. This view is enshrined by the principle of Equivalence of Care between prison and community, endorsed by the United Nations in the Nelson Mandela Rules. During the 2019 WHO Prison Health Conference in Helsinki, it was acknowledged that prisons contribute to achieving the UN’s Sustainable Development Goals through improving health, reducing health inequalities and provide a fairer and safer society for all. However, a number of challenges hampers the successful implementation of such a concept, including the need for evidence-based decision making, inter-sectoral partnerships and adequate monitoring systems. This workshop will provide attendees with a comprehensive overview of prison health and the relevance of a multi-sectorial public health approach to frame and address it. The workshop will be structured around three main topics: governance of prison health and current models in Europe; health issues and disease burden in the prison population; current and future perspectives for evidence-based approaches to prison health. The discussion of two case studies, problem drug use and HCV micro-elimination, will create the context for an in-depth analysis of key challenges for prison health implementation, reflecting on aspects such as health needs, equity, multidisciplinarity, continuity of care, monitoring and community dividend. Key messages Provide a comprehensive picture of the main challenges of prison health in Europe, the public health issues affecting the prison population and how these relate to community public health systems. Reflect on how public health systems need to incorporate prison health into their strategies for reducing inequalities and improving health outcomes of vulnerable and socially deprived populations.

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