Medical Assistance and Prediction for Chronic Diseases

Q: How many days will it take for my paper to be published?

The review time for papers is not fixed. However, if the paper is accepted and the author completes the processing charges formalities, the paper will be published within a few working days.

Q: I would like to receive a hard copy of the journal materials. Are there any additional charges?

You can log in to the author portal and pay 500 INR to receive the hard copy materials.

Palusa Deepika; Kasoju Shravya; Gurajala Sai Aravind Reddy; Macharla Vivekananda; Mohammed Farooq; Dr. M. Ramesh

Medical Assistance and Prediction for Chronic Diseases

Authors: Palusa Deepika, Kasoju Shravya, Gurajala Sai Aravind Reddy, Macharla Vivekananda, Mohammed Farooq, Dr. M. Ramesh

Unique Paper ID: 178117
Volume: 11
Issue: 12
PageNo: 2833-2838

Keywords: Artificial intelligence chronic disease prediction healthcare analytics machine learning personalized recommendations

Abstract:
Chronic diseases such as diabetes, cardiovascular disorders, and cancer are among the leading causes of death and long-term disability worldwide. These conditions often progress silently, making early detection and intervention essential for effective treatment and improved quality of life. However, traditional diagnostic methods are often time-consuming, reliant on expert interpretation, and reactive in nature. This project proposes a machine learning-based approach to predict the likelihood of chronic diseases by analyzing comprehensive patient data, including demographics, clinical history, lifestyle factors, and genetic indicators. Various supervised learning algorithms, including Decision Trees, Random Forests, Support Vector Machines (SVM), and Neural Networks, are employed to train models capable of making accurate and early predictions. In addition to risk prediction, the system also generates personalized recommendations for lifestyle changes and follow-up actions, aiming to support both healthcare professionals and patients in proactive disease management. Experimental evaluations demonstrate the effectiveness of the proposed model, highlighting its potential to enhance diagnostic accuracy, enable early intervention, and reduce healthcare costs.

Download article

email to a friend

Cite This Article

ISSN: 2349-6002
Volume: 11
Issue: 12
PageNo: 2833-2838

Medical Assistance and Prediction for Chronic Diseases

Available:https://ijirt.org/article?manuscript=178117

Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

Join Our IPN

IJIRT Partner Network

Submit your research paper and those of your network (friends, colleagues, or peers) through your IPN account, and receive 800 INR for each paper that gets published.

Join Now