Project Details
Description
In terms of healthcare domains there is a focus on:
* Perintal Health: To study risk and prognostic factors for perinatal mortality and other adverse outcomes
* Intensive Care: To investigate prognostic models of adverse outcomes and effectivity of decision support systems
* Geriatrics: To study optimization of workflows, development of prediction models, decision support for professionals and selfmanagement for patients
* Primary Care: Natural Language Processing for early detection of cancer and Decision support systems for optimizing care for elderly patients
Specific research projects in the research programme Methodology in Medical Informatics include:
* (ZonMW/NPO) ICOVE: Development of a pro-active Decision Support System based on the ACOVE criteria in Primary and Secondary Care.
* (ZonMW/ICT&DM) PROFIT: Prevention of Falls using infomration technology and disease management principles.
* Uses and abuses of benchmarking healthproviders
* Predictive models using breathprints obtained from an electronic nose.
* Prognostic (temporal) Models for individual Intensive Care patients based on the SOFA daily scores
* Perinatal Health informatics: Epidemiology and prognosis for asphyxia.
* Decision support for improving atrial fibrillation in general practice.
*(ZonMW) SIMPLIFY: Identification and prevention of drug-drug interactions in the Intensive Care.
* Prediction models and geographic and temporal validation in cardiology (TAVI) patients
* (NWO) SNOWDROP: Identification of patients at increased risk of falls due to medications, and a decision support system to improve joint decision making between the patient and the promary care physician about medication prescribing.
* (ZonMW and Innovation impulse) REMEDY and RESCUE: reducing ADEs and improving medication prescribing in the intensive care
* (ZonMW) ADFICE: Improving medication prescribing for older patients in hospitals
* (Innovation Impulse) SCOPE: Decision support for frail elders in the hospital
* OOD: Facing population shift by detecting out-of-distribution instances over time.
* Responsible NLP: Explainability of deep learning NLP models
* (NWO) LEAPFROG: AI-based decision support systems
* Perintal Health: To study risk and prognostic factors for perinatal mortality and other adverse outcomes
* Intensive Care: To investigate prognostic models of adverse outcomes and effectivity of decision support systems
* Geriatrics: To study optimization of workflows, development of prediction models, decision support for professionals and selfmanagement for patients
* Primary Care: Natural Language Processing for early detection of cancer and Decision support systems for optimizing care for elderly patients
Specific research projects in the research programme Methodology in Medical Informatics include:
* (ZonMW/NPO) ICOVE: Development of a pro-active Decision Support System based on the ACOVE criteria in Primary and Secondary Care.
* (ZonMW/ICT&DM) PROFIT: Prevention of Falls using infomration technology and disease management principles.
* Uses and abuses of benchmarking healthproviders
* Predictive models using breathprints obtained from an electronic nose.
* Prognostic (temporal) Models for individual Intensive Care patients based on the SOFA daily scores
* Perinatal Health informatics: Epidemiology and prognosis for asphyxia.
* Decision support for improving atrial fibrillation in general practice.
*(ZonMW) SIMPLIFY: Identification and prevention of drug-drug interactions in the Intensive Care.
* Prediction models and geographic and temporal validation in cardiology (TAVI) patients
* (NWO) SNOWDROP: Identification of patients at increased risk of falls due to medications, and a decision support system to improve joint decision making between the patient and the promary care physician about medication prescribing.
* (ZonMW and Innovation impulse) REMEDY and RESCUE: reducing ADEs and improving medication prescribing in the intensive care
* (ZonMW) ADFICE: Improving medication prescribing for older patients in hospitals
* (Innovation Impulse) SCOPE: Decision support for frail elders in the hospital
* OOD: Facing population shift by detecting out-of-distribution instances over time.
* Responsible NLP: Explainability of deep learning NLP models
* (NWO) LEAPFROG: AI-based decision support systems
| Status | Active |
|---|---|
| Effective start/end date | 1/01/2008 → … |