Data Based Framework for Sleep Medicine

Jun 25, 2024·
Kristina Zovko
,
Petar Šolić
Toni Perković
Toni Perković
,
Ivana Pavlinac Dodig
,
Linda Lušić Kalcina
,
Renata Pecotić
,
Zoran Đogaš
DOI

Abstract

Obstructive Sleep Apnea (OSA) is a common breathing disorder that affects between 2 % and 26 % of adults and remains significantly underdiagnosed, leading to disturbed sleep and reduced oxygen levels due to repeated collapse of the upper airway during sleep. In order to effectively diagnose and treat OSA, it is essential to use a machine learning (ML) model to predict future trends based on past data. This paper explores the integration of machine learning techniques into the field of sleep medicine, specifically for the diagnosis and management of OSA. The proposed digital platform offers a promising solution that improves diagnostic accuracy, supports personalized medicine, and improves the efficiency of healthcare delivery.

Type

Publication

International Conference on Smart and Sustainable Technologies (SpliTech), 01–06

Status

Peer-reviewed
publications
Toni Perković
Authors
Toni Perković
Full Professor
I am a Full Professor in the Department of Electronics and Computing at the Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB), University of Split, Croatia, where I teach wireless network security, wireless communication networks, data science and reinforcement learning. My research spans information security, applied cryptography and the Internet of Things. Before returning to FESB in 2020, I was an assistant and then associate professor at the University Department of Forensic Sciences in Split. I co-founded the SpliTech international conference and serve on the editorial board of the Journal of Communications Software and Systems.