Toward a Generic Multi-modal Medical Data Representation Model

K. M. Swaroopa, Nancy Kaur, Girija Chetty

Research output: A Conference proceeding or a Chapter in BookConference contributionpeer-review


This paper presents a generic multi-modal medical data representation model, based on utilizing the knowledge from the abundance of medical data in the publicly available medical imaging databases. Using novel deep learning techniques, this paper proposes an AI model that is technically capable of capturing characteristics of complex health conditions. The findings from this work based on extensive experimental work allows the development of robust and automatic detection of gliomas, an aggressive form of brain tumors. This model can provide significant benefits to the wide medical AI community and stimulate development and benefit universal health care in the long term.

Original languageEnglish
Title of host publicationAdvances in IoT and Security with Computational Intelligence - Proceedings of ICAISA 2023
EditorsAnurag Mishra, Deepak Gupta, Girija Chetty
Place of PublicationNetherlands
Number of pages10
ISBN (Print)9789819950874
Publication statusPublished - 2023
EventInternational Conference on Advances in IoT, Security with AI, ICAISA 2023 - New Delhi, India
Duration: 24 Mar 202325 Mar 2023

Publication series

NameLecture Notes in Networks and Systems
Volume756 LNNS
ISSN (Print)2367-3370
ISSN (Electronic)2367-3389


ConferenceInternational Conference on Advances in IoT, Security with AI, ICAISA 2023
CityNew Delhi


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