Page 147 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD)
Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies
Available Online: www.ijtsrd.com e-ISSN: 2456 – 6470

Advancement in Chronic Disease Management:
Innovative Approaches and Emerging Technologies

3
Subodh Tembhare , Sejal Shirbhaiyye , Prof. Anupam Chaube
2
1
1,2,3 Department of Science and Technology,
1,2,3 G H Raisoni College of Engineering and Management, Nagpur, Maharashtra, India

ABSTRACT allow for remote consultations and care, or the use of
Chronic diseases, including diabetes, hypertension, artificial intelligence and machine learning to predict the
cardiovascular diseases, and respiratory illnesses, have progression of chronic diseases or assist doctors in
become significant public health challenges worldwide, diagnosing and prescribing treatments. These technologies
impacting millions of individuals across diverse not only aim to enhance the quality of life for patients but also
demographics. The management of these conditions to make the management of chronic conditions more efficient
typically requires long-term care, monitoring, and lifestyle and accessible, particularly in underserved areas.
adjustments. Recent advancements in medical technologies, II. REALTED WORK
data analytics, and personalized healthcare have the 1. Ali and his colleagues aim at predicting heart disease
potential to revolutionize chronic disease management. early and accurately. Relying on ML through digital
This research paper explores innovative approaches and patient record assessment, they apply various
emerging technologies that are shaping the future of supervised choices and their feature importance. The
chronic disease management. The paper examines random forest (RF) algorithm gathers excellent results,
technological innovations like wearable devices, including perfect accuracy, holding great promise as a
telemedicine, artificial intelligence, and personalized diagnostic tool that helps to increase diagnostic accuracy
medicine that are transforming patient care. Furthermore, and efficiency in limited-resource healthcare settings. To
it outlines the impact of these technologies on outcomes, predict which heart disease patients require emergency
challenges in their integration, and the future of chronic care, the authors of.
disease management.

2. Proposed a novel stacking ensemble learner model that
KEYWORDS: Chronic diseases, healthcare technology, leverages a unique approach with behavior-based
telemedicine, wearable devices, artificial intelligence, features and a private MIT dataset, out- performing
personalized medicine, health outcomes, disease management, existing methods with 88% accuracy in predicting
patient monitoring, emerging technologies emergency readmission. This holds promise for early
inter- vention and improved clinical outcomes. One of
I. INTRODUCTION the recent research models that applied ML for heart
"Advancement in Chronic Disease Management: attack prediction is presented by El-Hasnony et al.
Innovative Approaches and Emerging Technologies” 3. Explore using AI on data collected through IoT sensors.
refers to a research study that investigates the evolving They aim to address issues like data bias and low
methods and technologies used to manage chronic diseases, accuracy, ultimately seeking a more accurate and
with an emphasis on the latest innovations aimed at effective AI-powered prediction system for this critical
improving patient outcomes. Chronic diseases such as medical chal- lenge. Furthermore, Singh et al.
diabetes, cardiovascular diseases, asthma, and arthritis are
long-term conditions that require continuous monitoring and 4. Examined prediction systems for heart disease
management, often involving complex treatment plans, employing a greater number of input attributes. These
lifestyle changes, and regular doctor visits. systems use medical terminology like gender, blood
pressure, and cholesterol, like 13 attributes. They
The project would explore how recent advancements, both in
suggested an effective genetic algorithm using the
medical practices and technology, are being applied to
backpropagation method to predict cardiac disease.
improve the management of these diseases. This could
Abbas et al.
include examining the development of new healthcare
models that focus on personalized care, where treatments are Our research paper has explored various aspects of chronic
tailored to individual patients based on their specific health disease management, including:-
data and needs. The project may also look into novel
 Telehealth and Remote Monitoring: Studies have
approaches in prevention, early detection, and remote investigated the effectiveness of telehealth platforms,
monitoring, helping to catch complications before they wearable devices, and remote patient monitoring
worsen and potentially reducing the need for frequent in- systems in improving adherence to treatment plans,
person medical visits. detecting early complications, and enhancing patient-
Emerging technologies would be a significant aspect of this provider communication.
research. The project could cover innovations such as
 Artificial Intelligence (AI) and Machine Learning (ML):
wearable health devices that monitor vital signs (e.g., heart
Research has focused on AI/ML applications for
rate, glucose levels) in real time, telemedicine platforms that

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