Research output per year
Research output per year
Project Details
Description
The framework 'P4 Medicine' (predictive, preventative, personalized, participatory) was developed to detect and prevent disease through close monitoring, deep statistical analysis, biomarker testing, and patient health coaching to best use the limited healthcare resources and produce maximum benefit for all patients. However, we have seen only few feasible examples over the past 10 years.
The Finding Endometriosis using Machine Learning (FEMaLe) project will revitalise the concept to develop and demonstrate the Scalable Multi-Omics Platform (SMOP) that converts multi-omic person population datasets into a personalised predictive model to improve intervention along the continuum of care for people with endometriosis.
SMOP will be based on open protocol, embedded in all ethical and legal frameworks, to enable tailored and personalised usage to improve the lives of patients across Europe beyond the project period.
The Finding Endometriosis using Machine Learning (FEMaLe) project will revitalise the concept to develop and demonstrate the Scalable Multi-Omics Platform (SMOP) that converts multi-omic person population datasets into a personalised predictive model to improve intervention along the continuum of care for people with endometriosis.
SMOP will be based on open protocol, embedded in all ethical and legal frameworks, to enable tailored and personalised usage to improve the lives of patients across Europe beyond the project period.
Key findings
We will rely on participatory processes, advanced computer sciences, state-of-the-art technologies, and patient-shared data to deliver:
1) mobile health app for people with endometriosis,
2) three clinical decision support (CDS) tools for targeted healthcare providers (risk stratification tool for general practitioners, multi-marker signature tool for gynaecologists, and non-invasive diagnostic tool for radiologist), and
3) computer vision-based software tool for real time augmented reality guided surgery of endometriosis.
Health maintenance organisations (HMO) expect to be able to reduce overall cost of treatment by at least 20%, while improving patient outcomes, using CDS tools.
1) mobile health app for people with endometriosis,
2) three clinical decision support (CDS) tools for targeted healthcare providers (risk stratification tool for general practitioners, multi-marker signature tool for gynaecologists, and non-invasive diagnostic tool for radiologist), and
3) computer vision-based software tool for real time augmented reality guided surgery of endometriosis.
Health maintenance organisations (HMO) expect to be able to reduce overall cost of treatment by at least 20%, while improving patient outcomes, using CDS tools.
Layman's description
We will design, validate and implement a comprehensive model for the detection and management of people with endometriosis to facilitate shared decision making between the patient and the healthcare provider, enable the delivery of precision medicine, and drive new discoveries in endometriosis treatment to deliver novel therapies and improve quality of life for patients.
| Short title | FEMaLe |
|---|---|
| Acronym | FEMaLe |
| Status | Active |
| Effective start/end date | 01/01/2021 → 31/12/2024 |
Funding
- Horizon 2020 - EU: DKK44,581,000.00
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.
Research output
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Endometriosis: time to think differently (and together)
Dixon, S., Mawson, R., Kirk, U. B. & Horne, A. W., May 2024, In: British Journal of General Practice. 74, 742, p. 200-201 2 p.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Editorial › peer-review
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FEMaLe: The use of machine learning for early diagnosis of endometriosis based on patient self-reported data-Study protocol of a multicenter trial
Balogh, D. B., Hudelist, G., Bļizņuks, D., Raghothama, J., Becker, C. M., Horace, R., Krentel, H., Horne, A. W., Bourdel, N., Marki, G., Tomassetti, C., Kirk, U. B., Acs, N. & Bokor, A., May 2024, In: PLOS ONE. 19, 5 May, p. e0300186 e0300186.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Journal article › Research › peer-review
Open Access -
Forskere om invaliderende kvindesygdom: Ny forskning sker i udlandet, ikke her, selvom vi nok ville kunne gøre det bedre
Kirk, U., 27 Jun 2024, In: Berlingske Tidende. Sektion 1, p. 16-17 2 p.Research output: Contribution to journal/Conference contribution in journal/Contribution to newspaper › Contribution to newspaper - Feature article
Activities
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Oral Presentation: "Finding Endometriosis using Machine Learning: A bird's-eye view of the FEMaLe project"
Kirk, U. B. (Lecturer)
30 May 2024Activity: Talk or presentation types › Lecture and oral contribution
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Akademiet for Talentfulde Unge | Midt
Kirk, U. B. (Chair person)
16 Apr 2024Activity: Participating in or organising an event types › Participation in or organisation of workshop, seminar or course
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Oral Presentation: "Skal Danmark have et videncenter for Endometriose?"
Kirk, U. B. (Lecturer)
12 Apr 2024Activity: Talk or presentation types › Lecture and oral contribution
Press/Media
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Sygdommen blev kaldt "en del af at være kvinde". Nu taler forskere om et gennembrud
31/07/2024
1 Media contribution
Press/Media: Press / Media
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Endometriose-kvinder går mere til læge end andre kvinder
23/08/2023
1 Media contribution
Press/Media: Press / Media