Abstract
The standard of care for a physician to review laboratory tests results is to weigh each individual laboratory test result and compare it to against a standard reference range. Such a method of scanning can lead to missing high-level information. Different methods have tried to overcome a part of the problem by creating new types of reference values. This research proposes looking at test scores in a higher dimension space. And using machine learning approach, determine whether a subject has abnormal tests result that, according to current practice, would be defined as valid-and thus indicating a possible disease or illness. To determine health status, we look both at a disease-specific level and disease-independent level, while looking at several different outcomes.
| Original language | English |
|---|---|
| Title of host publication | Challenges of Trustable AI and Added-Value on Health - Proceedings of MIE 2022 |
| Editors | Brigitte Seroussi, Patrick Weber, Ferdinand Dhombres, Cyril Grouin, Jan-David Liebe, Jan-David Liebe, Jan-David Liebe, Sylvia Pelayo, Andrea Pinna, Bastien Rance, Bastien Rance, Lucia Sacchi, Adrien Ugon, Adrien Ugon, Arriel Benis, Parisis Gallos |
| Publisher | IOS Press BV |
| Pages | 219-223 |
| Number of pages | 5 |
| ISBN (Electronic) | 9781643682846 |
| DOIs | |
| State | Published - 25 May 2022 |
| Externally published | Yes |
| Event | 32nd Medical Informatics Europe Conference, MIE 2022 - Nice, France Duration: 27 May 2022 → 30 May 2022 |
Publication series
| Name | Studies in Health Technology and Informatics |
|---|---|
| Volume | 294 |
| ISSN (Print) | 0926-9630 |
| ISSN (Electronic) | 1879-8365 |
Conference
| Conference | 32nd Medical Informatics Europe Conference, MIE 2022 |
|---|---|
| Country/Territory | France |
| City | Nice |
| Period | 27/05/22 → 30/05/22 |
Bibliographical note
Publisher Copyright:© 2022 European Federation for Medical Informatics (EFMI) and IOS Press.
Keywords
- Electronic Health Records
- Laboratory Tests
- Machine Learning
- UK Biobank
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