Manias, G;
Op Den Akker, H;
Azqueta, A;
Burgos, D;
Capocchiano, ND;
Crespo, BL;
Dalianis, A;
... Wajid, U; + view all
(2021)
IHELP: Personalised Health Monitoring and Decision Support Based on Artificial Intelligence and Holistic Health Records.
Presented at: 2021 IEEE Symposium on Computers and Communications (ISCC), Greece, Athens.
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Abstract
Scientific and clinical research have advanced the ability of healthcare professionals to more precisely define diseases and classify patients into different groups based on their likelihood of responding to a given treatment, and on their future risks. However, a significant gap remains between the delivery of stratified healthcare and personalization. The latter implies solutions that seek to treat each citizen as a truly unique individual, as opposed to a member of a group with whom they share common risks or health-related characteristics. Personalisation also implies an approach that takes into account personal characteristics and conditions of individuals. This paper investigates how these desirable attributes can be developed and introduces a holistic environment, the iHELP, that incorporates big data management and Artificial Intelligence (AI) approaches to enable the realization of data-driven pathways where awareness, care and decision support is provided based on person-centric early risk prediction, prevention and intervention measures.
| Type: | Conference item (Paper) |
|---|---|
| Title: | IHELP: Personalised Health Monitoring and Decision Support Based on Artificial Intelligence and Holistic Health Records |
| Event: | 2021 IEEE Symposium on Computers and Communications (ISCC) |
| Location: | Greece, Athens |
| Dates: | 5th-8th September 2021 |
| ISBN-13: | 978-1-6654-2744-9 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/ISCC53001.2021.9631475 |
| Publisher version: | http://dx.doi.org/10.1109/iscc53001.2021.9631475 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher's terms and conditions. |
| Keywords: | Holistic Health Records (HHRs), Pancreatic Cancer, Artificial Intelligence |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10200568 |
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