Fujitsu HIKARI, a Healthcare Decision Support System based on Biomedical Knowledge

Author(s):  
Boris Villazon-Terrazas ◽  
Nuria Garcia-Santa ◽  
Beatriz San Miguel ◽  
Angel del Rey-Mejías ◽  
Juan Carlos Muria ◽  
...  

Fujitsu HIKARI is an artificial intelligence solution to assist clinicians in medical decision making, developed in the context of a joint collaboration project between Fujitsu Laboratories of Europe and Hospital Clínico San Carlos. This decision support system leverages on data analytics combined with healthcare semantic information to provide health estimations for patients, improving care quality and personalized treatment. Fujitsu HIKARI stands on the shoulders of biomedical knowledge, which includes (i) theoretical knowledge extracted from scientific literature, domain expert knowledge, and health standards; and (ii) empirical knowledge extracted from real patient electronic health records. The theoretical knowledge combines a theoretical knowledge graph (TKG) and a biomedical document repository (BDR). The empirical knowledge is encoded in an empirical knowledge graph (EKG). One of the main functionalities of Fujitsu HIKARI is the patient mental health risks assessment, which is based on the exploitation of its underlying Biomedical Knowledge.

Author(s):  
Boris Villazon-Terrazas ◽  
Nuria Garcia-Santa ◽  
Beatriz San Miguel ◽  
Angel del Rey-Mejías ◽  
Juan Carlos Muria ◽  
...  

Fujitsu HIKARI is an artificial intelligence solution to assist clinicians in medical decision making, developed in the context of a joint collaboration project between Fujitsu Laboratories of Europe and Hospital Clínico San Carlos. This decision support system leverages on data analytics combined with healthcare semantic information to provide health estimations for patients, improving care quality and personalized treatment. Fujitsu HIKARI stands on the shoulders of biomedical knowledge, which includes (i) theoretical knowledge extracted from scientific literature, domain expert knowledge, and health standards; and (ii) empirical knowledge extracted from real patient electronic health records. The theoretical knowledge combines a theoretical knowledge graph (TKG) and a biomedical document repository (BDR). The empirical knowledge is encoded in an empirical knowledge graph (EKG). One of the main functionalities of Fujitsu HIKARI is the patient mental health risks assessment, which is based on the exploitation of its underlying Biomedical Knowledge.


2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Bjarni V. Halldorsson ◽  
Aron Hjalti Bjornsson ◽  
Haukur Tyr Gudmundsson ◽  
Elvar Orn Birgisson ◽  
Bjorn Runar Ludviksson ◽  
...  

Expanding medical knowledge increases the potential risk of medical errors in clinical practice. We present, OPAD, a clinical decision support system in the field of the medical care of osteoporosis. We utilize clinical information from international guidelines and experts in the field of osteoporosis. Physicians are provided with user interface to insert standard patient data, from which OPAD provides instant diagnostic comments, 10-year risk of fragility fracture, treatment options for the given case, and when to offer a follow-up DXA-evaluation. Thus, the medical decision making is standardized according to the best expert knowledge at any given time. OPAD was evaluated in a set of 308 randomly selected individuals. OPAD’s ten-year fracture risk computation is nearly identical to FRAX (r= 0.988). In 58% of cases OPAD recommended DXA evaluation at the present time. Following a DXA measurement in all individuals, 71% of those that were recommended to have DXA at the present time received recommendation for further investigation or specific treatment by the OPAD. In only 5.9% of individuals in which DXA was not recommended, the result of the BMD measurement changed the recommendations given by OPAD.


Author(s):  
Vytautas Petrauskas ◽  
Gyte Damuleviciene ◽  
Algirdas Dobrovolskis ◽  
Juozas Dovydaitis ◽  
Audrone Janaviciute ◽  
...  

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