Key result
AI deep learning model uses bidirectional long-term memory to predict CVD from mobile health data.
Why the study?
The study aimed to accurately predict cardiovascular disease from patient m-health data using an AI-based deep learning model to improve prediction performance.
An AI-based deep learning model using GTOA and Bi-LSTM was developed to predict cardiovascular disease from mobile health data.
Hypothesis-generating for m-health AI in CVD prediction; prospective validation required before clinical adoption.
In recent decades, mobile health (m-health) applications have gained significant attention in the healthcare sector due to their increased support during critical cases like cardiac disease, spinal cord problems, and brain injuries. Also, m-health services are considered more valuable, mainly where facilities are deficient. In addition, it supports wired and advanced wireless technologies for data transmission and communication. In this work, an AI-based deep learning model is implemented to predict healthcare data, where the data handling is performed to improve the prediction performance. It includes the working modules of data collection, normalization, AI-based classification, and decision-making. Here, the m-health data are obtained from the smart devices through the service providers, which comprises the health information related to blood pressure, heart rate, glucose level, etc. The main contribution of this paper is to accurately predict Cardio Vascular Disease (CVD) from the patient dataset using the AI-based m-health system. After obtaining the data, preprocessing can be performed for noise reduction and normalization because prediction performance highly depends on data quality. Consequently, We use the Gorilla Troop Optimization Algorithm (GTOA) to select the most relevant functions for classifier training and testing. Classify his CVD type according to a selected set of features using bidirectional long-term memory (Bi-LSTM). Moreover, the proposed AI-based prediction model’s performance is validated and compared using different measures.
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Ramesh et al. (2023) studied Cardiovascular Disease (CVD). AI-based prediction model (Bi-LSTM and GTOA) was evaluated on Prediction of Cardiovascular Disease (CVD). An AI-based deep learning model using bidirectional long-term memory and the Gorilla Troop Optimization Algorithm was developed to predict cardiovascular disease from mobile health data.
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