PRIMENA NEURONSKIH MREŽA NA PARAMETRE KVALITETA ZDRAVSTVENE ZAŠTITE
Sažetak
Za potrebe praćenja i procene kvaliteta nege i lečenja koji se nude pacijentima i pružanja podrške aktivnostima koje se odnose na zdravstvenu zaštitu koristi se kvantitativni indikator poznat kao „indikator kvaliteta u zdravstvenoj zaštiti”. Ova studija je razmatrala tačnost predviđanja stope smrtnosti slučajeva koristeći šest različitih faktora. Istraživanje odnosa između navedenih faktora (stopa smrtnosti (procenat) u roku od 48 sati od prijema, stopa smrtnosti hirurških slučajeva, prosečna dužina boravka u bolnici, prosečan broj preoperativnih dana, prosečan broj hirurških zahvata (anestezija), prosečan broj medicinskih sestara po zauzetom krevetu na medicinskom odeljenju) i predviđanje stope smrtnosti slučaja bili su primarni cilj. Predviđanja stope smrtnosti slučajeva urađena su uz pomoć mašine za ekstremno učenje (ELM), izgrađene i korišćene u toku istraživanja. Rezultati ELM-a, genetskog programiranja (GP) i veštačke neuronske mreže (ANN) bili su predmet poređenja i diskusije. Tačnost kompjuterskih modela procenjena je upoređivanjem njihovih predviđanja sa empirijskim podacima i korišćenjem niza statističkih mera. Rezultati simulacija pokazuju da se ELM može efikasno koristiti u situacijama kada je potrebno predviđanje stope smrtnosti.
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