Smart healthcare system for biomedical and healthcare applications

Malika singh

Abstract


A cryptocurrency dubbed Bitcoin was suggested in 2008, and an open-source version of it became accessible in 2009. Blockchain technology served as the basis for the bitcoin implementation. Peer-to-peer networking transactions are made feasible by decentralised blockchain. Attempts have been made by researchers to look at its applications outside of finance. Healthcare is one industry where blockchain technology has a lot of potential. Blockchain technology has the potential to advance the healthcare industry in a number of areas, including health monitoring devices, clinical trial data, the sharing and storage of patient medical records, the storage of information related to insurance, and claim settlement, to name just a few. The proposed solution tries to address issues with ownership, security, and privacy of healthcare data by utilising Blockchain technology.

Keywords


Artificial Intelligence, CNN, Deep Learning, EEG Data, Feature extraction, Machine Learning, Neuroscience

References


N. Jiwani, K. Gupta and P. Whig, "Novel HealthCare Framework for Cardiac Arrest With the Application of AI Using ANN," 2021 5th International Conference on Information Systems and Computer Networks (ISCON), 2021, pp. 1-5, doi: 10.1109/ISCON52037.2021.9702493.

Jupalle, H., Kouser, S., Bhatia, A.B. et al. Automation of human behaviors and its prediction using machine learning. Microsyst Technol (2022). https://doi.org/10.1007/s00542-022-05326-4

K. Gupta, N. Jiwani, N. Afreen and D. D, "Liver Disease Prediction using Machine learning Classification Techniques," 2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), 2022, pp. 221-226, doi: 10.1109/CSNT54456.2022.9787574.

A. Sharma, H. Jupalle, R. R. Naddikatu, A. Velu and P. Whig, "AI Application for the Sustainable Development to Reduce Carbon Footprint," 2021 5th International Conference on Information Systems and Computer Networks (ISCON), 2021, pp. 1-4, doi: 10.1109/ISCON52037.2021.9702511.

K. Gupta, N. Jiwani and N. Afreen, "Blood Pressure Detection Using CNN-LSTM Model," 2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), 2022, pp. 262-366, doi: 10.1109/CSNT54456.2022.9787648.

N. Jiwani, K. Gupta and N. Afreen, "Automated Seizure Detection using Theta Band," 2022 International Conference on Emerging Smart Computing and Informatics (ESCI), 2022, pp. 1-4, doi: 10.1109/ESCI53509.2022.9758331.

Alkali, Y., Routray, I., & Whig, P. (2022). Study of various methods for reliable, efficient and Secured IoT using Artificial Intelligence. Available at SSRN 4020364.

Anand, M., Velu, A., & Whig, P. (2022). Prediction of Loan Behaviour with Machine Learning Models for Secure Banking. Journal of Computer Science and Engineering (JCSE), 3(1), 1–13.

Bhargav, R., & Whig, P. (2021). More Insight on Data Analysis of Titanic Data Set. International Journal of Sustainable Development in Computing Science, 3(4), 1–10.

chouhan, S. (2019). Using an Arduino and a temperature, humidity sensor, Automate the fan speed. International Journal of Sustainable Development in Computing Science, 1(2).

George, N., Muiz, K., Whig, P., & Velu, A. (2021). Framework of Perceptive Artificial Intelligence using Natural Language Processing (PAIN). Artificial & Computational Intelligence/Published Online: July.

Khera, Y., Whig, P., & Velu, A. (2021). efficient effective and secured electronic billing system using AI. Vivekananda Journal of Research, 10, 53–60.

Pawar, V. S. (2021). IOT ARCHITECTURE WITH EMBEDDED AI. International Journal of Sustainable Development in Computing Science, 3(4), 11–20.

Velu, A., & Whig, P. (2021). Protect Personal Privacy And Wasting Time Using Nlp: A Comparative Approach Using Ai. Vivekananda Journal of Research, 10, 42–52.

Whig, P., Nadikattu, R. R., & Velu, A. (2022). COVID-19 pandemic analysis using application of AI. Healthcare Monitoring and Data Analysis Using IoT: Technologies and Applications, 1.

Whig, P., & Rupani, A. (2020). Novel Economical Social Distancing Smart Device for COVID19. International Journal of Electrical Engineering and Technology, 2.

N. Jiwani, K. Gupta and N. Afreen, "A Convolutional Neural Network Approach for Diabetic Retinopathy Classification," 2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), 2022, pp. 357-361, doi: 10.1109/CSNT54456.2022.9787577.


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