Primena mašinskog učenja u borbi protiv COVID-19 pandemije
Sažetak
Mašinsko učenje (engl. Machine Learning – ML) ima značajnu ulogu u borbi protiv COVID-19 pandemije (SARS-CoV-2). ML bazirane tehnike omogućavaju brzo otkrivanje uzročno-posledičnih veza i trendova iz velikog uzorka podataka. Zbog toga ove tehnike pružaju efikasne metode za generisanje informacija i sticanje znanja iz struktuiranih i nestruktuiranih podataka. Ovo je posebno značajno u uslovima koji utiču na sve apsekte ljudskih života kao što je slučaj sa pandemijama. U ovakvim slučajevima je neophodno prikupljati veliku količinu podataka koja će omogućiti donošenje odgovarajućih mera za sprečavanje širenja pandemije, ranu dijagnostiku infekcije, pronalazak lekova, smanjenje negativnih posledica, itd. Savremene informacijske i komunikacijske tehnologije (IKT) omogućavaju i nove koncepte primene kao što je Internet stvari (engl. Internet of Things –IoT), a koji omogućava automatizirano i efikasno prikupljanje podataka iz različitih izvora. Ovo otvara mogućnosti za kreiranje efikasnih ML-baziranih mehanizama i prediktivnih modela potrebnih za donošenje odgovarajućih mera i odluka u specifičnim situacijama. Ovaj rad prezentuje najkorištenije primene mašinskog učenja za smanjenje uticaja COVID-19 pandemije. Cilj je da se prikažu potencijali, rešenja i mogućnosti primene različitih tehnika, algoritama i skupova podataka (engl. datasets) u kontekstu borbe protiv navedene pandemije. Također, u radu su predstavljene određene ideje i otvorena pitanja za buduća istraživanja što može koristiti kao polazna tačka za buduća istraživanja.
Reference
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