81,000 research outputs found
Inteligencia Artificial en Medicina y Salud: revisión y clasificación de las aplicaciones actuales y del futuro cercano y su impacto ético y social
This paper provides an overview of the current and near-future applications of Artificial Intelligence
(AI) in Medicine and Health Care and presents a classification according to their ethical and societal
aspects, potential benefits and pitfalls, and issues that can be considered controversial and are not
deeply discussed in the literature.
This work is based on an analysis of the state of the art of research and technology, including existing
software, personal monitoring devices, genetic tests and editing tools, personalized digital models,
online platforms, augmented reality devices, and surgical and companion robotics.
Motivated by our review, we present and describe the notion of “extended personalized medicine”,
we then review existing applications of AI in medicine and healthcare and explore the public
perception of medical AI systems, and how they show, simultaneously, extraordinary opportunities
and drawbacks that even question fundamental medical concepts. Many of these topics coincide
with urgent priorities recently defined by the World Health Organization for the coming decade. In
addition, we study the transformations of the roles of doctors and patients in an age of ubiquitous
information, identify the risk of a division of Medicine into “fake-based”, “patient-generated”, and
“scientifically tailored”, and draw the attention of some aspects that need further thorough analysis
and public debate
Extending the Carrel system to mediate in the organ and tissue allocation processes: a first approach
In this paper we extend the formalization of Carrel, a virtual organization for the procurement of tissues for transplantation purposes, in order to model also the procurement of human organs for transplants. We will focus in the organ allocation process to show how it can be formalized with the ISLANDER formalism. Also we present a first mechanism to federate the institution in several geographically-distributed platforms.Postprint (published version
Transhumanism Between Human Enhancement and Technological Innovation
Transhumanism introduces from its very beginning a paradigm shift about concepts like human nature, progress and human future. An overview of its ideology reveals a strong belief in the idea of human enhancement through technologically means. The theory of technological singularity, which is more or less a radicalisation of the transhumanist discourse, foresees a radical evolutionary change through artificial intelligence. The boundaries between intelligent machines and human beings will be blurred. The consequence is the upcoming of a post-biological and posthuman future when intelligent technology becomes autonomous and constantly self-improving. Considering these predictions, I will investigate here the way in which the idea of human enhancement modifies our understanding of technological innovation. I will argue that such change goes in at least two directions. On the one hand, innovation is seen as something that will inevitably lead towards intelligent machines and human enhancement. On the other hand, there is a direction such as “Singularity University,” where innovation is called to pragmatically solving human challenges. Yet there is a unifying spirit which holds together the two directions and I think it is the same transhumanist idea
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Technology and Caregiving: Emerging Interventions and Directions for Research.
An array of technology-based interventions has increasingly become available to support family caregivers, primarily focusing on health and well-being, social isolation, financial, and psychological support. More recently the emergence of new technologies such as mobile and cloud, robotics, connected sensors, virtual/augmented/mixed reality, voice, and the evermore ubiquitous tools supported by advanced data analytics, coupled with the integration of multiple technologies through platform solutions, have opened a new era of technology-enabled interventions that can empower and support family caregivers. This paper proposes a conceptual framework for identifying and addressing the challenges that may need to be overcome to effectively apply technology-enabled solutions for family caregivers. The paper identifies a number of challenges that either moderate or mediate the full use of technologies for the benefit of caregivers. The challenges include issues related to equity, inclusion, and access; ethical concerns related to privacy and security; political and regulatory factors affecting interoperability and lack of standards; inclusive/human-centric design and issues; and inherent economic and distribution channel difficulties. The paper concludes with a summary of research questions and issues that form a framework for global research priorities
Artificial Intelligence for Global Health: Learning From a Decade of Digital Transformation in Health Care
The health needs of those living in resource-limited settings are a vastly
overlooked and understudied area in the intersection of machine learning (ML)
and health care. While the use of ML in health care is more recently
popularized over the last few years from the advancement of deep learning,
low-and-middle income countries (LMICs) have already been undergoing a digital
transformation of their own in health care over the last decade, leapfrogging
milestones due to the adoption of mobile health (mHealth). With the
introduction of new technologies, it is common to start afresh with a top-down
approach, and implement these technologies in isolation, leading to lack of use
and a waste of resources. In this paper, we outline the necessary
considerations both from the perspective of current gaps in research, as well
as from the lived experiences of health care professionals in resource-limited
settings. We also outline briefly several key components of successful
implementation and deployment of technologies within health systems in LMICs,
including technical and cultural considerations in the development process
relevant to the building of machine learning solutions. We then draw on these
experiences to address where key opportunities for impact exist in
resource-limited settings, and where AI/ML can provide the most benefit.Comment: Accepted Paper at ICLR 2020 Workshop on Practical ML for Developing
Countrie
Technological Singularity
Hypothetically, technological singularity is considered as irreversible changes
to the mankind resulted from technological growth due to the invention of artificial
super intelligence (AI). The major concern is that AI will come out of the control and,
finally, humanity will be deprived of their position in the world
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