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Pregled bibliografske jedinice broj: 1083692

Clinical Decision Support Systems in Practice: Current Status and Challenges


Jović, Alan; Stančin, Igor; Friganović, Krešimir; Cifrek, Mario
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

Profili:

Avatar Url Krešimir Friganović (autor)

Avatar Url Alan Jović (autor)

Avatar Url Igor Stančin (autor)

Avatar Url Mario Cifrek (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada

Citiraj ovu publikaciju:

Jović, Alan; Stančin, Igor; Friganović, Krešimir; Cifrek, Mario
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)
Jović, A., Stančin, I., Friganović, K. & Cifrek, M. (2020) Clinical Decision Support Systems in Practice: Current Status and Challenges. U: Skala, K. (ur.)Proceedings 43rd International Convention MIPRO 2020.
@article{article, author = {Jovi\'{c}, Alan and Stan\v{c}in, Igor and Friganovi\'{c}, Kre\v{s}imir and Cifrek, Mario}, editor = {Skala, K.}, year = {2020}, pages = {373-378}, keywords = {decision support system, clinical decision support system, healthcare, artificial intelligence, deep learning}, title = {Clinical Decision Support Systems in Practice: Current Status and Challenges}, keyword = {decision support system, clinical decision support system, healthcare, artificial intelligence, deep learning}, publisher = {Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO}, publisherplace = {Opatija, Hrvatska} }
@article{article, author = {Jovi\'{c}, Alan and Stan\v{c}in, Igor and Friganovi\'{c}, Kre\v{s}imir and Cifrek, Mario}, editor = {Skala, K.}, year = {2020}, pages = {373-378}, keywords = {decision support system, clinical decision support system, healthcare, artificial intelligence, deep learning}, title = {Clinical Decision Support Systems in Practice: Current Status and Challenges}, keyword = {decision support system, clinical decision support system, healthcare, artificial intelligence, deep learning}, publisher = {Hrvatska udruga za informacijsku i komunikacijsku tehnologiju, elektroniku i mikroelektroniku - MIPRO}, publisherplace = {Opatija, Hrvatska} }




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