[AISWorld] 10 more days to go - UMUAI Special Issue on Patient-centered Personalized eHealth

[Tsvika Kuflik]

Call for papers:

Special Issue on Patient-centered Personalized eHealth

User Modeling and User-Adapted Interaction: The Journal of Personalization
Research (UMUAI)

Extended abstract submission deadline: February 15, 2016

Paper submission deadline (for accepted abstracts): April 15, 2016

Special Issue Web site:
<http://mis.hevra.haifa.ac.il/%7Emorpeleg/umuai_personalized_eHealth.html>
http://mis.hevra.haifa.ac.il/~morpeleg/umuai_personalized_eHealth.html

UMUAI Web site: http://www.umuai.org/

 

Scope of the Special Issue 

In recent years, patients want to be more involved in their health care.
Clinicians acknowledge that involved and empowered patients take more
responsibility for their health, which leads to better outcomes. With the
advance of ICT, telemonitoring and decision support systems are now being
targeted not only at care providers but also at patients.

While patients want to be more involved, they do not have the required
medical knowledge. On the other hand, physicians have the knowledge, but not
the time to adapt that knowledge to all their patients. Traditional clinical
decision-support systems (DSS) are aimed at supporting healthcare
professionals treat patients by matching clinical knowledge to data of
concrete patients, in order to provide patient-specific recommendations to
the health care professionals. The clinical knowledge of these traditional
systems addresses the clinical condition of the patient but is rarely
personalized to the non-clinical considerations of patients (e.g., level of
family support, patient autonomy, level of education of the patient).
Recently, patient-centered clinical decision support systems have emerged,
which envision an alternative scenario in which patients can become users of
these systems in addition to care professional. The advice delivered to
patients is different from the advice targeted toward physicians. While
physicians need to receive support for choosing among treatment
alternatives, patients need to receive reminders for performing measurements
(e.g., of blood pressure), exercising, and taking medications in accordance
to the medical requirements. These recommendations need to be personalized
to patients' preferences, such as their normal meal schedule, their level of
education, etc. This user-patient duality implies that patient-centered DSSs
have to deal with user (patient) modeling in order to personalize the care
needs of the concrete patient-users. These systems relate to the patient's
clinical parameters but also to patient preferences, psycho-social
considerations, functioning and disabilities, or co-morbidities that are
particular to each specific patient in order to provide a complete and
personalized treatment.

In this special issue we will be focusing on Patient-centered clinical
decision support systems and ubiquitous technologies that define user models
supporting patient personalization.

 

Topics

 Topics could include but are not limited to the following topics:

.       Personalized knowledge-based eHealth

.       Health behavior theories and personalization

.       Personalized training, coaching and education eHealth applications

.       Personalized health communication between patients and care
providers

.       Patient model/ patient modeling

.       Using data analysis technologies (machine learning, data mining, big
data, semantic data, data science, etc.) to build personalized
patient-centric models and predictive systems

.       Ubiquitous and personalized eHealth Information Systems

.       Patient-tailored decision-support

.       Patient-centered systems (e.g., self-management)

.       Managing continuity of care for patients spanning different
organizations or care teams within an organization

Papers for this special issue should not target personalized medicine in
terms of genetics/genomics. While telemonitoring could be an important
aspect of personalized eHealth systems, papers need to have a focus on
modeling patients/treatments using either knowledge-engineering or data
analysis technologies.

Paper submission and reviewing process 

The prospective authors must first submit an extended abstract of no more
than 4 single-spaced pages, formatted with 12-pt font and 1-inch margins,
through easychair:

https://easychair.org/conferences/?conf=umuai-ehealth-16

 

 

 

Tsvika

 

Tsvi Kuflik, PhD.

  Associate Professor

  The University of Haifa

  Email: tsvikak at is.haifa.ac.il

  Home page: http://sites.hevra.haifa.ac.il/tsvikak/

  Tel: +972 4 8288511

  Fax: +972 4 8288283

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