Health Recommender research project

Dealing with recommendations that assist health behavior the research project Health Recommender aims to develop new methods for supporting health-related information retrieval and decision-making. This multidisciplinary research project aims to create new solutions that promote open knowledge and open data in the fields of personalized medicine and health informatics.
The research project is initiated and coordinated by Lauri Lahti, Dr. Sc. (Tech.), at Department of Computer Science at Aalto University School of Science, Finland (access to the personal web site).

Terveyskäyttäytymistä avustavaa suosittelua koskeva tutkimushanke Health Recommender pyrkii kehittämään uusia menetelmiä tukemaan terveyteen liittyvän tiedon hakemista ja päätöksentekoa. Tämä monitieteinen tutkimushanke pyrkii luomaan uusia ratkaisuja, jotka edistävät avointa tietoa ja avointa dataa yksilöllistetyn lääketieteen ja terveystiedon tietojenkäsittelyn aihepiirissä.
Tutkimushankkeen on käynnistänyt ja sitä koordinoi tekniikan tohtori Lauri Lahti Aalto-yliopiston perustieteiden korkeakoulun tietotekniikan laitoksella (pääsy henkilökohtaiselle verkkosivulle).

Blog archive:

January 2016

Supporting health by digitalization

Author: Lauri Lahti. A blog article published on 31 January 2016 at

Digitalization of various medical analysis methods and storing the gathered measurements into data bases has opened new possibilities for carrying out efficient analysis of correlations and dependencies in the data. Developing and exploiting the new analysis methods for medical diagnostic and treatment work requires expertise that covers various multidisciplinary fields of research. To effectively combine expertise and resources representing complementing perspectives into a medical problem (for example multiple medical personel, laboratory techniques, inspection instruments, data representation formats, time series analysis etc.) there is a need for fluent shared understanding, communication and division of tasks.

Since giving a diagnosis and a treatment have heavy time constraints there is a need for develping such collaborative integrated processes that can facilite identifying the most essential information, fluent communication and maintaining accurracy. Also for each individual medical professional there is a need for developing supportive methods that help to maintain attention and making logical actions effectively (for example for a medic, a trauma specialist, an imaging specialist and a rehabiliation nurse).

Recently happened adoption and usage of smart phones and mobile online activity among ordinary people has opened new possibilities for using health-related online services for everyone. There have been initiatives and requests to provide increasingly more open access to personal health data for everyone (for example personal medical records about previous diagnoses and medications). There is a need to develop individually customized medical services called as personalized medicine. Easy-to-use and relatively low-priced mobile health technology devices and software in smart phones have been introduced to consumers and partly adopted also to support clinical health services.

Ordinary people have become relatively familiar with interactive information retrieval of up-to-date knowledge and communication possibilities with computer devices and realtime online activity that can be applied also in personal medical challenges, for example in self-care and prevention. For elderly and impaired people new computerized assistive technology has offered new ways to manage indenpendently and safely. People have gained a locationally independent possibility to form and join social groups and interaction with social networking that can enable new forms of peer-to-peer support also in respect to patient groups sharing the same medical diagnosis.

To cite this blog article please refer to: Lahti, Lauri (2016). Supporting health by digitalization. A blog article published on 31 January 2016 on the web site of Health Recommender research project. Available online at

Copyright: Health Recommender research project,, 2017.