Learning individualized treatment rules (ITRs) is an important topic in precision medicine. Current literature mainly focuses on deriving ITRs from a single source population. We consider the observational data setting when population differs target of interest. Compared with causal generalization for average effect which scalar quantity, ITR poses new challenges due to need model and generaliz...

This demonstration presents DIPSEIL Environment – its methodology, functionality, workflow model and its interface in an example. We start with the description of developed Learning Objects for Internet-based Performance Support Systems with Educational Elements – IPSS_EE_LOs. Then we present how IPSS_EE_LOs can be created and used in DIPSEIL for the development of “Telecommunication Systems” c...

In this paper, we present a web-based educational setting, referred to as SCALE (Supporting Collaboration and Adaptation in a Learning Environment), which aims to serve leaning and assessment. SCALE enables learners to (i) work on individual and collaborative activities proposed by the environment with respect to learners’ knowledge level, (ii) participate actively in the assessment process in ...

Abstract Lower limb motor impairment affects greatly the autonomy and quality of life those people suffering from it. Recent studies have shown that an appropriate rehabilitation can significantly improve their condition, but, for this purpose, it is essential to know patient’s functional state be able detect any changes occur in as soon possible. Traditionally, standardized clinical scales bee...

In many important applications of precision medicine, the outcome interest is time to an event (e.g., death, relapse disease) and primary goal identify optimal individualized decision rule (IDR) prolong survival time. Existing work in this area have been mostly focused on estimating IDR maximize restricted mean population. We propose a new robust framework for static or dynamic with time-to-eve...