A Recommendation System Based on AI for Storing Block Data in the Electronic Health Repository
  • Metaadatok
Tartalom: http://hdl.handle.net/20.500.12944/17575
Archívum: Közszolgálati Tudásportál
Gyűjtemény: Publikációk
Karokon kívüli egységek
Cím:
A Recommendation System Based on AI for Storing Block Data in the Electronic Health Repository
Létrehozó:
Mani Vinodhini
Kavitha C.
Band Shahab S.
Mosavi Amir
Hollins Paul
Palanisamy Selvashankar
Közreműködő:
Eötvös József Kutatóközpont
Kiadó:
Frontiers Media S.A.
Téma:
artificial intelligence
deep learning
health data
health repository
machine learning
patients
storage
Műszaki tudományok
Műszaki tudományok/Informatikai tudományok
Tartalmi leírás:
The proliferation of wearable sensors that record physiological signals has resulted in an exponential growth of data on digital health. To select the appropriate repository for the increasing amount of collected data, intelligent procedures are becoming increasingly necessary. However, allocating storage space is a nuanced process. Generally, patients have some input in choosing which repository to use, although they are not always responsible for this decision. Patients are likely to have idiosyncratic storage preferences based on their unique circumstances. The purpose of the current study is to develop a new predictive model of health data storage to meet the needs of patients while ensuring rapid storage decisions, even when data is streaming from wearable devices. To create the machine learning classifier, we used a training set synthesized from small samples of experts who exhibited correlations between health data and storage features. The results confirm the validity of the machine learning methodology. Copyright
Típus:
info:eu-repo/semantics/other
Formátum:
application/pdf
Azonosító:
nke:2296-2565
nke:10.3389/fpubh.2021.831404
nke:32607350
nke:Frontiers in Public Health
nke:9
nke:000751455600001
nke:2-s2.0-85124072429
Létrehozó:
info:eu-repo/semantics/openAccess