An Advanced Conceptual Diagnostic Healthcare Framework for Diabetes and Cardiovascular Disorders
M. Sharma, G. Singh, R. Singh

TL;DR
This paper proposes an advanced healthcare framework combining data mining, IoT, chatbots, and semantic analysis to improve diagnosis and treatment for diabetes and cardiovascular patients, aiming for an effective and economical solution.
Contribution
It introduces a hybrid framework integrating multiple emerging technologies to enhance healthcare for diabetic and cardiac patients, with a focus on practicality and cost-effectiveness.
Findings
The system uses bio-sensors for real-time patient monitoring.
Hybridization of technologies offers a more effective healthcare solution.
Implementation is challenging but potentially more economical.
Abstract
The data mining along with emerging computing techniques have astonishingly influenced the healthcare industry. Researchers have used different Data Mining and Internet of Things (IoT) for enrooting a programmed solution for diabetes and heart patients. However, still, more advanced and united solution is needed that can offer a therapeutic opinion to individual diabetic and cardio patients. Therefore, here, a smart data mining and IoT (SMDIoT) based advanced healthcare system for proficient diabetes and cardiovascular diseases have been proposed. The hybridization of data mining and IoT with other emerging computing techniques is supposed to give an effective and economical solution to diabetes and cardio patients. SMDIoT hybridized the ideas of data mining, Internet of Things, chatbots, contextual entity search (CES), bio-sensors, semantic analysis and granular computing (GC). The…
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