Abstract
Personalized medicine (PM) aims to establish a new approach in clinical decision-making, based upon a patient's individual profile in order to tailor treatment to each patient's characteristics. Although this has become a focus of the discussion also in the psychiatric field, with evidence of its high potential coming from several proof-of-concept studies, nearly no tools have been developed by now that are ready to be applied in clinical practice. In this paper, we discuss recent technological advances that can make a shift toward a clinical application of the PM paradigm. We focus specifically on those technologies that allow both the collection of massive as much as real-time data, i.e., electronic medical records and smart wearable devices, and to achieve relevant predictions using these data, i.e. the application of machine learning techniques.
Original language | English (US) |
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Pages (from-to) | 1-9 |
Number of pages | 9 |
Journal | Psychological Medicine |
DOIs | |
State | Accepted/In press - Oct 2 2017 |
Keywords
- Big data
- electronic medical records
- machine learning
- personalized medicine
- precision medicine
- wearable devices
ASJC Scopus subject areas
- Applied Psychology
- Psychiatry and Mental health