Naslov
Genomic data analysis: Conceptual framework for the application of artificial intelligence in personalized treatment of oncology patients
(Genomic data analysis: Conceptual framework for the application of artificial intelligence in personalized treatment of oncology patients)

Autori
Kelemenić-Dražin, Renata ; Luić, Ljerka

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the International Conferences on WWW/Internet 2021 and Applied Computing 2021 / Isaías, Pedro ; Weghorn, Hans - : International Assn for Development of the Information Society (IADIS), 2021, 233-236

ISBN
978-989-8704-34-4

Skup
20th International Conference on WWW/Internet (ICWI 2021) ; 18th International Conference Applied Computing 2021 (AC 2021)

Mjesto i datum
Online, 13.10.2021. - 15.10.2021

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
data analytics ; artificial intelligence ; oncology ; personalized medicine

Sažetak
Oncology is one of the most dynamic branches of medicine. As a result of numerous oncology studies, there has been a significant increase in scientific and clinical data that the human brain cannot store. Advances in artificial intelligence (AI) technology has led to its rapid clinical application. In this paper, we wanted to see the role of the use of artificial intelligence (AI) in oncology. We conducted an unsystematic search of databases (Pub Med, MEDLINE, and Google Scholar) using the keywords: artificial intelligence, deep learning, machine learning, oncology, personalized medicine. From a large number of articles available to us, we singled out review articles and clinical trial results according to their clarity and innovation regarding the use of artificial intelligence in oncology. Of particular importance to us was the ability to apply their results in everyday clinical work. The possibilities of using artificial intelligence in oncology are innumerable. Thus, AI can be used for diagnostic purposes (malignant screening, histopathology, and molecular diagnostics), therapeutic purposes (personalized treatment, prediction of treatment side effects and response to therapy, treatment decisions) as well as for prognostic purposes (risk stratification, 5-year survival, monitoring). The implementation of AI in clinical practice presents new challenges for clinicians. Namely, in the era of evidence-based and patient-centered medicine, they will have to master statistical as well as computer skills in addition to clinical ones. Therefore, it is necessary to start educating future doctors about the importance of AI in medicine as soon as possible.

Izvorni jezik
Engleski

Znanstvena područja
Informacijske i komunikacijske znanosti

POVEZANOST RADA