Cascella, Marco (2023) Implementing Multiple AI‑Based Strategies Toward Automatic Pain Assessment in Cancer Patients. The Pascale Investigation. [Tesi di dottorato]

Anteprima

Testo Cascella_Marco_36.pdf Download (3MB) | Anteprima

Abstract

This document describes the preliminary results of the research activities carried out within the Ph.D. in Information and Communication Technology for Health (ICTH) on the topic of automatic pain assessment (APA) in cancer patients at the Department of Electrical Engineering and Information Technologies (DIETI) of the University of Naples “Federico II”. This research line is dedicated to advancing innovative strategies grounded in artificial intelligence (AI) methodologies with a central focus on objectively probing pain features within the context of oncological patients. The overarching goal is to collect and comprehensively analyze multimodal and multidimensional data. Clinical assessment and data collection is performed through conventional in-person evaluations as well as synchronous and asynchronous telemedicine modalities. In pursuit of these objectives, the research endeavors to leverage several state-of-the-art AI approaches for developing methodologies that transcend traditional subjective pain assessment methods. Behavioral-based APA investigations, including facial expressions of pain and multiple speech analyses, and biosignal studies are performed. Multimodal parameters are integrated to study different cancer pain phenomena that are less understood and difficult to investigate. The aspiration is to pave the way for more effective and personalized pain management strategies by unravelling the intricate layers of pain experiences in cancer patients.

Downloads

Actions (login required)

Modifica documento