Istraživači Odsjeka za računarstvo kanadskog Sveučilišta u Alberti na dobrom su putu omogućiti ranu dijagnozu Alzheimerove bolesti i drugih vrsta demencije svima koji imaju pametni telefon pri ruci. Kvaka je u primijenjenom modelu strojnog učenja iz kojeg bi se mogao izraditi jednostavan alat za provjeru. Ovo nije prvi takav pothvat računalnih stručnjaka iz Alberte koji su dosad već izradili slične modele umjetne inteligencije i alate za otkrivanje psihijatrijskih poremećaja kao što su PTSP, shizofrenija, depresija i bipolarni poremećaj.
Nagrađen model
Njihov model, nagrađen na netom završenoj Međunarodnoj konferenciji o akustici, obradi govora i signala ICASSP 2023. na grčkom otoku Rodosu, trenutno raspoznaje pacijente s Alzheimerovom bolešću s točnošću od 70 do 75 posto, što obećava brojka za stotine milijuna ljudi kod kojih će se prije ili kasnije razviti neki oblik demencije. Alzheimerovu bolest dosad je bilo teško otkriti u ranim fazama jer simptomi često počinju prilično suptilno i mogu se zamijeniti s problemima povezanim s pamćenjem, tipičnim za stariju dob.
Da biste otkrili promjene na mozgu, potrebne su razna medicinska snimanja i analiza laboratorijskih pretraga, a to zahtijeva vrijeme, skupo je i najčešće se radi kad je bolest već uznapredovala. Rano otkrivanje pokazatelja demencije pomoću pametnih telefona ubrzalo bi proces i liječenje počelo puno ranije, ističu istraživači. Njihov alat za probir ne bi zamijenio zdravstvene djelatnike, ali bi pokrenuo razvoj telezdravstva i ukinuo brojne zemljopisne ili jezične prepreke u pristupu medicinskim uslugama jer bi se trijaža mogla temeljiti samo na govoru.
Značajke govora
Istraživači su u sklopu projekta ispitivali jezično-agnostičke akustičke i lingvističke značajke govora, a ne specifične riječi. Istraživali su karakteristike govora, uobičajene kod pacijenata oboljelih od Alzheimera. Ti pacijenti govore sporije, s više pauze ili prekida u govoru, obično koriste kraće riječi i često ih je teže razumjeti. Istraživači su pronašli način da te karakteristike prevedu u govorne značajke koje bi mogli provjeriti model strojnog učenja.
Iako je sam model prilično složen, konačno korisničko iskustvo ne može biti jednostavnije. Osoba razgovara s alatom koji analizira i predviđa bolest, a te se informacije zatim mogu prenijeti liječnicima koji će odrediti daljnje postupke.
Više o temiIzvor:Bug.hr
Hi there.
aktual.hr, Thanks for keeping a thoughtful corner of the internet alive.
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