Models and tools based on Data Mining and AI techniques for the fall risk evaluation in elderly people, on the basis of statistical, epidemiological, contextual and expert-based knowledge

The research activity aims to analyze data mining and artificial
intelligence techniques for the evaluation of the fall risk, on the
basis of different knowledge types: statistical information,
epidemiological data, and contextual knowledge. These information will be
further integrated with medical knowledge provided by domain experts.
Presumably, the experts' knowledge will be in the form of rules. Hence,
a goal of this research activity will be about integrating different
information and knowledge types, within a single framework. Aims and
goals of the FARSEEING project will contribute in the identification of
research directions. Moreover, it is expected an intense collaboration
activity with academic and industrial partners of FARSEEING.

Research Fields

Computer science - Modelling tools
Engineering - Knowledge engineering

Eligibility criteria

to apply for research grants fill out the form available at the following address: https://www.aric.unibo.it/AssegniRicerca/BandiPubblicati/zz_Bandi_din.aspx

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Programme Description

Eligible destination country/ies for fellows	Italy
Eligibility of fellows: country/ies of residence	All
Eligibility of fellows: nationality/ies	All
Website of Fellowship Programme	https://www.aric.unibo.it/AssegniRicerca/BandiPubblicati/zz_Bandi_din.aspx

Fellowship's Details

Career Stage	Early stage researcher or 0-4 yrs (Post graduate)
Research Profile	Not defined