BOLALARDA EPILEPSIYA TURLARINI TASNIFLASHDA MASHINALI O‘QITISH USULLARINI QO‘LLASH
DOI:
https://doi.org/10.5281/zenodo.23117384Abstract
Bolalarda epileptik xurujlarni aniqlash erta aralashuv va bemorni uzluksiz kuzatib borish uchun muhim klinik vazifa hisoblanadi. Ushbu tadqiqotda ko‘p kanalli bosh terisi EEG signallari asosida epileptik xurujlarni avtomatik aniqlash uchun “boshidan oxirigacha” (end-to-end) ishlaydigan chuqur o‘rganish usuli taqdim etiladi. CHB-MIT bosh terisi EEG ma’lumotlar bazasi asosida 20 608 ta belgilangan EEG segmenti o‘qitish, tekshirish va mustaqil sinov to‘plamlariga ajratildi. Sinov natijalarida CNN–LSTM modeli ROC-AUC = 0,995, F1 = 0,966, accuracy = 0,968, precision = 0,9777 va recall = 0,9646 ko‘rsatkichlariga erishdi. Natijalar ushbu usulning EEG asosida xurujlarni avtomatik aniqlash va klinik qarorlarni qo‘llab-quvvatlovchi aqlli tizimlarga integratsiya qilish salohiyatini ko‘rsatadi.Keywords
EEG, mashinali o‘qitish, epilepsiya, klassifikatorlar, ma’lumotlar to‘plami, SMOTEReferences
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