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Advancement in Chronic Disease Management: Unveiling New Frontiers in Diagnosis, Treatment & Prevention

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Advancement in Chronic Disease Management: Unveiling New Frontiers in Diagnosis, Treatment & Prevention


Vedant Golait | Titu Tiwari | Prof. Anupam Chaube



Vedant Golait | Titu Tiwari | Prof. Anupam Chaube "Advancement in Chronic Disease Management: Unveiling New Frontiers in Diagnosis, Treatment & Prevention" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Emerging Trends and Innovations in Web-Based Applications and Technologies, January 2025, pp.147-153, URL: https://www.ijtsrd.com/papers/ijtsrd74930.pdf

The rapid advancement in medical technologies has revolutionized the field of predictive healthcare, enabling the development of sophisticated systems that integrate diverse data types to enhance diagnostic accuracy. This paper presents a novel hybrid medical prediction system that synergistically combines deep learning-based image analysis and traditional medical data processing techniques to deliver accurate multi-modal diagnostic predictions.The proposed system leverages the strengths of Convolutional Neural Networks (CNNs) and Natural Language Processing (NLP) techniques to synthesize insights from medical images, structured data, and textual information. Specifically, ResNet-18 is employed for feature extraction from medical images, while term frequency-inverse document frequency (TF-IDF) vectorization is utilized for processing structured and textual data.By integrating CNNs with NLP techniques, the system forms a robust architecture capable of identifying complex relationships between diverse data modalities. This multi-modal approach not only enhances diagnostic accuracy but also streamlines clinical workflows, offering significant potential in predictive healthcare systems.The proposed hybrid medical prediction system has far-reaching implications for the field of healthcare, enabling clinicians to make more informed decisions, improving patient outcomes, and reducing healthcare costs. Future research directions include exploring the application of this system to various medical specialties and investigating the use of other deep learning architectures to further enhance diagnostic accuracy.

Natural Language Processing (NLP), CNN, Image classification, Text Vectorization


IJTSRD74930
Special Issue | Emerging Trends and Innovations in Web-Based Applications and Technologies, January 2025
147-153
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

International Journal of Trend in Scientific Research and Development - IJTSRD having online ISSN 2456-6470. IJTSRD is a leading Open Access, Peer-Reviewed International Journal which provides rapid publication of your research articles and aims to promote the theory and practice along with knowledge sharing between researchers, developers, engineers, students, and practitioners working in and around the world in many areas like Sciences, Technology, Innovation, Engineering, Agriculture, Management and many more and it is recommended by all Universities, review articles and short communications in all subjects. IJTSRD running an International Journal who are proving quality publication of peer reviewed and refereed international journals from diverse fields that emphasizes new research, development and their applications. IJTSRD provides an online access to exchange your research work, technical notes & surveying results among professionals throughout the world in e-journals. IJTSRD is a fastest growing and dynamic professional organization. The aim of this organization is to provide access not only to world class research resources, but through its professionals aim to bring in a significant transformation in the real of open access journals and online publishing.

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