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Introduction:
Knowledge is power -- and in healthcare, that
holds absolutely true. Yet, for an industry that
is under financial stress, increasing complexity
of disease and co-morbidity, and burdened by
capacity constraints -- why has data not been
healthcare's savvier? Three major challenges have
inhibited this:
- data is not accessible and remains in silos;
- data is not analysed to derive meaningful
clinical insights;
- insight isn't accessible for actioning by
providers or patients to self/joint manage their
condition.
Our consortium of medical professionals, data
scientists, IT-infrastructure experts, machine
learning researchers and legal experts have
designed Enabling Patient Interventions to
liberate, analyse, and action that data in a
trustworthy way. EPI aims to empower patients and
providers through self-management, shared
management, and personalization across the full
health spectrum. To do so, we will build a fuller
picture of the person by linking traditional
eHealth data sets with new sources of data.
Further, we will develop a platform based upon a
secure and trustworthy distributed data
infrastructure, combining data analytics,
including machine learning, and health decision
support algorithms to create new, actionable, and
personalized insights for prevention, management,
and intervention to providers and patients. We
will develop new machine learning methods for
determining and analysing optimal interventions
within small patient groups.
Our insights will be applied in healthcare use
cases representing a spectrum of health management
challenges ranging from common chronic to highly
lethal orphan diseases, and will empower better
self/joint management of these conditions to
improve cost, quality, and outcomes of care.
Here are introductory slides about the project:
in Dutch,
and in English.
Research topics:
The overall aim of this project is to explore the
use and effectiveness of data driven development
of scientific algorithms, supporting personalized
self- and joint management during medical
interventions / treatments. The key objective is
to use data science promoting health practically
with data from various sources to formulate
lifestyle advice, prevention, diagnostics, and
treatment tailored to the individual, and to
provide personalized, effective, real-time
feedback via a concept referred in this proposal
as a digital health twin. The project addresses
six research questions:
- RQ1/2: Dynamically Analyzing
Interventions based on Small Groups: how
can we determine, based on as little
data as possible, whether an
intervention does or does not work for a
small group or even an individual
patient? And how can we identify
effective intervention strategies and
optimize personalization strategies
applicable for different patient and
lifestyle profiles via dynamic (on-line)
clustering of patients?
- Lead CWI: Rosanne Turner, Peter
Grunwald
- RQ3: Data and Algorithm Distribution:
what are the consequences of a
distributed, multi-platform,
multi-domain, multi-data-source big data
infrastructure on the machine learning
algorithms and what are potential
consequences on performance?
- Lead: VU, Corinne Allaart, Henri
Bal
- RQ4: Adaptive health diagnosis
leading to optimized intervention: how
can we enhance self- / joint management
by dynamically integrating updated
models generated from machine learning
from various data sources in state of
the art health support systems that
based on personal health records,
knowledge of health modes and effective
interventions?
- Lead: UvA, Saba Amiri, Adam
Belloum
- RQ5: Regulatory constraints and data
governance: how can we create scalable
solutions that meet legal requirements
and consent or medical necessity-based
access to data for allowed data
processing and preventing breaches of
these rules by embedded compliance,
providing evidence trails and
transparency, thus building trust in a
sensitive big data sharing
infrastructure?
- Lead: UvA, Milen Girma Kebede,
Giovanni Sileno, Tom van Engers
- RQ6: Infrastructure: how can the
various requirements from the use-cases
be implemented using a single functional
ICT-infrastructure architecture?
- Lead: UvA, Jamila Kassem, Paola
Grosso
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Contact:
- Principle Investigators: Prof.dr.ir.
C.T.A.M. de Laat, <delaat@uva.nl>,
prof. dr. Sander Klous
<Klous.Sander@kpmg.nl>
- Project contact: Marloes Bons
<Bons.Marloes@kpmg.nl> or
+31 20 656 7859
- This work is part of the project
Enabling Personalized Interventions
(EPI) and is supported by NWO in the Commit2Data
– Data2Person
program under contract 628.011.028.
For more information see: https://enablingpersonalizedinterventions.nl
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References:
- Leon Gommans, John Vollbrecht, Betty Gommans
- de Bruijn, Cees de Laat, "The Service Provider
Group Framework; A framework for arranging trust
and power to facilitate authorization of network
services.", Future Generation Computer Systems,
(Accepted paper), June 2014
- Leon Gommans, "Multi-Domain Authorization for
e-Infrastructures", UvA, Dec 2014.
- Internet2 2012 session: "Trust Framework for
Multi-Domain Authorization".
- speakers: Leon Gommans , John Vollbrecht,
chair: Cees de Laat.
- Managing
Our Hub Economy, Marco Iansiti, Karim R.
Lakhani, Harvard Business review,
September-October 2017 issue, [local
copy]
- NWO
press release: Enabling Personalized
Interventions - EPI.
Outcome:
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2020-12-09 |
Paper: Kebede Girma, M., Sileno, G., and van
Engers, T., A critical reflection on ODRL.
Proceedings of the 11th Workshop on Artificial
Intelligence and the Complexity of Legal Systems
AICOL2020, in conjunction with JURIX 2020. |
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2020-11-09 |
Short Paper: R.J. Turner and P.D. Grünwald. "Safe
Tests for 2 x 2 Contingency Tables and the
Cochran-Mantel-Haenszel Test" presentation at BNAIC/
BENELEARN 2020. |
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2020-09-24 |
Paper: Jamila Alsayed Kassem, Cees de Laat, Arie
Taal, and Paola Grosso, The EPI Framework: A dynamic
data sharing framework for healthcare use
cases", IEEE Acees journal, Digital Object
Identifier DOI 10.1109/ACCESS.2020.3028051 |
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2020-08-09 |
Paper: Wouter van Haaften, Alex Sangers, Tom van
Engers, Somayeh Djafari, "Coping with the general
data protection regulation: Anonymization through
multi-party computation technology.", IRIS/SCIS
Conference, 9-12 August 2020, Sundsvall, Sweden,
<https://www.irisscis2020.com> |
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2020-06-29 |
Rosanne J. Turner, "Safe Statistics for Means and
Proportions", video presentation at the
Machine Learning Summer School 2020 by the Max
Planck Institute for Intelligent Systems, Tübingen,
Germany. Link to the video: https://youtu.be/H5RMtnydAQI |
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2020-04-22 |
Presentation at the EPI-PHD online quarterly
meeting: Freek Dijkstra, "Data Exchange Demo: Share
data while retaining control and confidentiality of
your data." |
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2020-04-22 |
Presentation at the EPI-PHD online quarterly
meeting: Guido van 't Noordende, "Push authorization
- the Whitebox model." |
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2020-03-17 |
Poster and short
paper at ICT.OPEN
2020 (cancelled): Rosanne J. Turner, Alexander Ly,
Judith ter Schure, Peter D. Grünwald , "Safe
Testing: online, anytime valid hypothesis
tests. " |
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2020-03-17 |
Poster and short
paper at ICT.OPEN
2020 (cancelled): Jamila Alsayed Kassem, "EPI
infrastructure: A dynamic infrastructure to secure
data sharing in healthcare applications." |
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2020-03-17 |
Poster and short
paper at ICT.OPEN
2020 (cancelled): Milen G. Kebede, Giovanni Sileno,
Tom Van Engers, "Automated regulatory constraints
and data governance for healthcare," |
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2019-10-31 |
Poster at NWO COMMIT2DATA PI meeting, Utrecht:
"Enabling Personalized Interventions (EPI)." |
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2019-10-11 |
Presentation by Cees de Laat: Department of
Computer Science, AGH University of Science and
Technology Krakow: "ICT to support the
transformation of Science in the Roaring
Twenties." |
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2019-10-02 |
Poster by Corrine Allaart (VU) at Big Data Health
and Data2Person event, Amersfoort: " Distributed
Deep Learning voor Cerebrovascular Accident." |
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2019-10-02 |
Presentation Pitch by Corinne Allaart (VU) at Big
Data Health and Data2Person event, Amersfoort: "
Distributed Deep Learning voor Cerebrovascular
Accident."
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2019-09-25 |
Presentation by Cees de Laat: eScience
conference Visionary track, San Diego: "ICT
to support the transformation of Science in the
Roaring Twenties." |
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2019-08-22 |
Presentation by Cees de Laat: CIENA executive
briefing invited science presentation, Ottawa: "ICT
to support the transformation of Science in the
Roaring Twenties." |
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2019-09-18 |
Presentation by Cees de Laat: Global Research
Platform (GRP) workshop,
San
Diego: "Globally
Distributed Secure Data Exchange Fabrics."
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2019-04-25 |
Presentation by Cees de Laat, Sander Klous, Josine
Janus at kick off meeting: "Enabling personalized
Intervetions". |
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2018-12-18 |
SURFSARA Superdag 2018 talk: "Digital Data
Markets: Trusted Data Processing in Untrusted
Environments". |
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2018-05-09 |
Session organized by Cees de Laat (chair) at
Internet2 Summit, Washington, May 9, 2018; "Digital
Marketplaces Using Novel Infrastructure Models." |
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2017-02-24 |
Report from NWO/STW Workshop "ICT with Industry
2016" Lorenz Centre Leiden, Nov. 7-11th 2016; Prof.
dr. Tom M. van Engers (UvA), Prof. dr. Robert Meijer
(UvA, TNO), Dr. ing. Leon Gommans (Air France KLM
Group ICT Technology Office R&D, UvA), Dr. Kees
Nieuwenhuis (Thales Nederland B.V., CTO Office),
"Trusted Big Data Sharing for Aircraft MRO using a
Secure Digital Market Place mechanism." |
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