Pregled bibliografske jedinice broj: 1083692
Clinical Decision Support Systems in Practice: Current Status and Challenges
Clinical Decision Support Systems in Practice: Current Status and Challenges // Proceedings 43rd International Convention MIPRO 2020 / Skala, K. (ur.).
Rijeka: Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2020. str. 373-378 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 1083692 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Clinical Decision Support Systems in Practice:
Current Status and Challenges
Autori
Jović, Alan ; Stančin, Igor ; Friganović, Krešimir ; Cifrek, Mario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings 43rd International Convention MIPRO 2020
/ Skala, K. - Rijeka : Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO, 2020, 373-378
Skup
43nd International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO 2020)
Mjesto i datum
Opatija, Hrvatska, 28.09.2020. - 02.10.2020
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
decision support system, clinical decision support system, healthcare, artificial intelligence, deep learning
Sažetak
Decision support systems (DSS) are computer programs based on artificial intelligence methods that contribute to reaching a correct decision in an often-narrow domain of interest. Clinical decision support systems (CDSS) are such DSSs that may be used by medical professionals in clinics and hospitals. They are used for diagnosis, treatment protocol recommendations, treatment outcome predictions and other tasks. CDSS are constructed based on symbolic and machine learning (including deep learning) approaches to represent and infer medical knowledge. The aim of this work is to provide an overview of past and current methods in designing a successful CDSS. The study considers the systems that were claimed to be implemented in clinical practice. Currently, the development of a CDSS is mostly pursued in two directions: 1) a more traditional approach based on rules, ontologies, probabilistic models, and the use of standards ; 2) machine learning based approach. Both approaches may be used complementary within a healthcare information system. This work seeks to provide an objective view on the advantages and limitations of the approaches as well to discuss future research avenues that could lead to more accurate and trustworthy CDSS and improved healthcare.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Kliničke medicinske znanosti
POVEZANOST RADA
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb