Pregled bibliografske jedinice broj: 1139368
AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity
AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity // Journal of clinical medicine, 10 (2021), 4; 766, 23 doi:10.3390/jcm10040766 (međunarodna recenzija, pregledni rad, znanstveni)
CROSBI ID: 1139368 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
AI and Big Data in Healthcare: Towards a More
Comprehensive Research Framework for
Multimorbidity
Autori
Majnarić, Ljiljana ; Babič, František ; O’Sullivan, Shane ; Holzinger, Andreas
Izvornik
Journal of clinical medicine (2077-0383) 10
(2021), 4;
766, 23
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, pregledni rad, znanstveni
Ključne riječi
artificial intelligence ; chronic diseases ; machine learning ; multimorbidity ; population aging.
Sažetak
Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs. However, in practice it is difficult to meet these needs because the organizational processes of current healthcare systems tend to be tailored to a single disease. To improve clinical decision making and patient care in multimorbidity, a radical change in the problem-solving approach to medical research and treatment is needed. In addition to the traditional reductionist approach, we propose interactive research supported by artificial intelligence (AI) and advanced big data analytics. Such research approach, when applied to data routinely collected in healthcare settings, provides an integrated platform for research tasks related to multimorbidity. This may include, for example, prediction, correlation, and classification problems based on multiple interaction factors. However, to realize the idea of this paradigm shift in multimorbidity research, the optimization, standardization, and most importantly, the integration of electronic health data into a common national and international research infrastructure is needed. Ultimately, there is a need for the integration and implementation of efficient AI approaches, particularly deep learning, into clinical routine directly within the workflows of the medical professionals.
Izvorni jezik
Engleski
Znanstvena područja
Kliničke medicinske znanosti
POVEZANOST RADA
Ustanove:
Medicinski fakultet, Osijek,
Fakultet za dentalnu medicinu i zdravstvo, Osijek
Profili:
Ljiljana Majnarić
(autor)
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI