Silicon Revolution in Healthcare

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About this Research Topic

Submission deadlines

  1. Manuscript Submission Deadline 30 April 2025

  2. This Research Topic is still accepting articles.

Background

From the breakthrough of Holter monitoring in the second half of last century, through actigraphy in its last decade, the methods of recording physiological data or physio-logging have become ubiquitous in the so-called ecological — i.e. in daily life — assessment of health and disease. The turn of the millennium provided basis for the future near-limitless progress in bio-sensors, data storage and processing. But perhaps most importantly it also opened the code of our genetic information to reason upon.

We are seemingly at the gate of a new age of ecologically oriented healthcare, where nearly all physiological functions can be sensed, stored and subject to screening. In health and in disease, arming the medical care with the possibility to devise individualised therapy and track its effectiveness, in vivo and in digital twins. This is not limited to physiological function of our bodies but extends to psychological condition - indeed mobile devices monitoring cognitive function and delivering therapy have been proposed and used for the past two decades.

The aim of this topic is to attract submissions from authors who are willing to share their current work and their vision on this potentially groundbreaking impact of technology on healthcare. From technological advances which aim at extending sensory capabilities of physio/psycho-logging through all the computational aspects involved in safely storing and transferring data to feedback scenarios involving point-of-care. Specialising in one classified illness or condition to systemic or medically unexplained diseases. Further, of special interest are the still futuristic applications
involving technology of intelligent houses, offices, personal and public transport, including devices thus far considered off-range for logging purposes. Critical issues in development of such devices (some of which are already in prototyping or initial production stage, such as diagnostic toilets, mirrors, etc.) are the privacy and cyber security considerations in addition to prohibitive cost - common to all novel technology. The advance of machine learning and Artificial Intelligence technology brings a new breath of processing power to these devices. Yet, as is the case with all new technology, advances bring risks, in addition to mentioned before risks of privacy and data security there are growing risks of individual harm, through interference with healthy life, through functionality of early technology to danger of addiction to digital or AI technology geared devices.

Summarising contributions addressing but not restricted to these areas of modern technologies in health and disease are welcome:

- physiological or psychological function monitoring/logging
- critical issues and solutions to security, health impact, cost, etc.
- novel approaches to data aggregation, storage, transmission, etc.
- frontier modelling methodologies, using AI, digital twins technologies etc.
- holistic health assessment, conjoining physiological and psychological wellbeing
- fulfilling the vision and aims of the Primary Health Care (PHC) as defined by WHO and UNICEF

All flavours of work are welcome, from concepts through working prototypes to fully functional systems - medical and technological contributions alike. Review papers, opinion pieces and hypothesis papers are equally welcome.

Topic Editors declare no conflict of interest.

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This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

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Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Keywords: physiological monitoring, psychological logging, machine learning, artificial intelligence, data aggregation, data storage, data transmission, computational modelling, technologies in health, digital twins

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