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Pregled bibliografske jedinice broj: 644007

Big data approach to assessment of soldier stress resilience


Ćosić, Krešimir; Popović, Siniša; Kovač, Bernard
Big data approach to assessment of soldier stress resilience // 1st International Congress of the International College of Person-Centered Medicine (2013) (znanstveni, prihvaćen)


CROSBI ID: 644007 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Big data approach to assessment of soldier stress resilience

Autori
Ćosić, Krešimir ; Popović, Siniša ; Kovač, Bernard

Vrsta, podvrsta
Radovi u časopisima, znanstveni

Izvornik
1st International Congress of the International College of Person-Centered Medicine (2013)

Status rada
Prihvaćen

Ključne riječi
big data; stress resilience; soldier

Sažetak
The concept of new multidimensional and multimodal metrics for assessment of soldier stress resilience is presented, which is based on comprehensive analysis of a few hundred physiological, acoustic, facial and EEG features computed during soldier elicitation with specific multimodal stimulation using mission-relevant affective databases. Augmentation of this dynamic data streams with resilience-relevant biomarkers, like: COMT Val158Met polymorphism, catabolic regulation of synaptic dopamine, immune/inflammatory endocrine and autonomic response, as well as with fMRI/DTI images of key brain circuitry and their connectomics, including a variety of questionnaires like subjective self-reports, personality traits, phenotypes etc. makes the problem of soldier resilience assessment much more complex. Aggregation and cross-correlation longitudinal analysis of these unstructured multidimensional and multimodal datasets along soldier life cycle, including development of soldiers personalized predictive models, leads to real big data problem. Crunching, learning and reasoning on such huge biological, neural, behavioral and environmental personalized big datasets require multidisciplinary and interdisciplinary expert teams. In order to understand complex, nonlinear, and stochastic interactions among soldier’s environment, behavior and biology, we must move from group-based analysis toward individuals personalized big data analysis based on sophisticated machine learning mathematical methods and techniques which can extract valuable scientific and applicable results and knowledge.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika, Računarstvo, Psihologija



POVEZANOST RADA


Projekti:
036-0000000-2029 - Adaptivno upravljanje scenarijima u VR terapiji PTSP-a (Ćosić, Krešimir, MZOS ) ( POIROT)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Siniša Popović (autor)

Avatar Url Krešimir Ćosić (autor)


Citiraj ovu publikaciju:

Ćosić, Krešimir; Popović, Siniša; Kovač, Bernard
Big data approach to assessment of soldier stress resilience // 1st International Congress of the International College of Person-Centered Medicine (2013) (znanstveni, prihvaćen)
Ćosić, K., Popović, S. & Kovač, B. (2013) Big data approach to assessment of soldier stress resilience. Prihvaćen za objavljivanje u 1st International Congress of the International College of Person-Centered Medicine. [Preprint].
@unknown{unknown, year = {2013}, keywords = {big data, stress resilience, soldier}, journal = {1st International Congress of the International College of Person-Centered Medicine}, title = {Big data approach to assessment of soldier stress resilience}, keyword = {big data, stress resilience, soldier} }
@unknown{unknown, year = {2013}, keywords = {big data, stress resilience, soldier}, journal = {1st International Congress of the International College of Person-Centered Medicine}, title = {Big data approach to assessment of soldier stress resilience}, keyword = {big data, stress resilience, soldier} }




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