A Review Article on the Prediction of Diseases at an Early Stage
DOI:
https://doi.org/10.55524/ijircst.2023.11.2.8Keywords:
Disease Prediction, Machine Learning, Healthcare, Random ForestAbstract
Individuals today suffer from a wide range of diseases as a result of their lifestyle choices and the environment in which they live. The objective of forecasting disease at an earlier stage becomes an increasingly vital condition as the identification and prediction of such diseases at their earlier phases become highly significant. Most individuals are too lazy to go to the hospital or see a doctor for a small problem. Our approach focuses on accuracy to detect additional symptoms for illness prediction in healthcare. In this section, I've employed a variety of machine learning algorithms carefully and focused in this few, which achieved the highest accuracy with that specific condition in order to build a strong model that produces the most exact forecasts. This work introduces the topics of illness prediction, disease therapy, and local medical consultation with effective machine learning programming. There are several diseases in the world that are brought on by the conditions of people's living habits or their surroundings. Thus, this study offers a summary of machine learning based illness prediction.
Downloads
References
Kumar, R., Thakur, P., & Chauhan, S. (2022). Special Disease Prediction System Using Machine Learning. 2022 International Conference on Machine Learning, Big Data, Cloud and Parallel Computing, COM-IT-CON 2022, 42–45. https://doi.org/10.1109/COM-IT
CON54601.2022.9850843.
Pandey, A. K., Tripathi, A., & Ranjan, R. (2022). Disease Prediction Using Machine Learning (Health Buddy). 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, 1003–1006.
https://doi.org/10.1109/ICACITE53722.2022.9823602. [3] Gada, D. (2022). Disease Prediction System using Machine Learning. 2022 6th International Conference on Computing, Communication, Control and Automation, ICCUBEA 2022. https://doi.org/10.1109/ICCUBEA54992.2022.10011002. [4] Barun, A., Nanda, M., Jarwal, M. K., & Sipal, D. (2022). Various Disease Predictions Using Machine Learning. 2022 IEEE Region 10 Symposium, TENSYMP 2022. https://doi.org/10.1109/TENSYMP54529.2022.9864521. [5] Gomathi, R. M., Deepa Jothi, K., Ajitha, P., Sivasangari, A., Anandhi, T., & Rani, V. N. (2022). Flawless Multi Perspective Vision for Prediction of Disease using Machine Learning Approach. 2022 6th International Conference on Trends in Electronics and Informatics, ICOEI 2022 - Proceedings, 1190–1194.
https://doi.org/10.1109/ICOEI53556.2022.9776787. [6] Basak, A., Rahman, M. S., & Rahman, M. (2022). Prediction of Heart Disease Using an Approach Based on Machine Learning. 2022 13th International Conference on Computing Communication and Networking Technologies, ICCCNT 2022.
https://doi.org/10.1109/ICCCNT54827.2022.9984555. [7] Trisal, A., Sagar, V., & Jameel, R. (2022). Cardiac Disease Prediction using Machine Learning Algorithms.
Proceedings of International Conference on Computational Intelligence and Sustainable Engineering Solution, CISES 2022, 583–589.
https://doi.org/10.1109/CISES54857.2022.9844370. [8] Sharma, A., Pathak, J., & Rajakumar, P. (2022). Disease Prediction using machine learning algorithms. 2022 2nd International Conference on Advance Computing and Innovative Technologies in Engineering, ICACITE 2022, 995–999.
https://doi.org/10.1109/ICACITE53722.2022.9823744. [9] Gulhane, M., & Sajana, T. (2021). A Machine Learning based Model for Disease Prediction. 2021 International Conference on Computing, Communication and Green Engineering, CCGE 2021.
https://doi.org/10.1109/CCGE50943.2021.9776374. [10] Farooqui, Md. E., & Ahmad, Dr. J. (2020). A DETAILED REVIEW ON DISEASE PREDICTION MODELS THAT USES MACHINE LEARNING. International Journal of Innovative Research in Computer Science & Technology, 8(4). https://doi.org/10.21276/ijircst.2020.8.4.14. [11] Usman, A., & Rajpurohit, B. S. (2021). Modeling and classification of stator inter-turn fault and demagnetization effects in bldc motor using rotor back-emf and radial magnetic flux analysis. International Journal of Power and Energy Systems, 41(2).
https://doi.org/10.1109/ACCESS.2017.
Jain College of Engineering, Institute of Electrical and Electronics Engineers. Bangalore Section., & Institute of Electrical and Electronics Engineers. (n.d.). 2020 International Conference for Emerging Technology (INCET) : Belgaum, India. Jun 5-7, 2020.
Pingale, K., Surwase, S., Kulkarni, V., Sarage, S., & Karve, A. (2019). Disease Prediction using Machine Learning. International Research Journal of Engineering and Technology. www.irjet.net.
Jamgade, A. C. (2019). Disease Prediction Using Big Data from Healthcare Communities. International Journal of Advanced Research in Computer and Communication Engineering, 8
https://doi.org/10.17148/IJARCCE.2019.8328.
Jadhav, S., Kasar, R., Lade, N., Patil, M., & Kolte, S. (2019). Disease Prediction by Machine Learning from Healthcare Communities. International Journal of Scientific Research in Science and Technology, 29–35.
https://doi.org/10.32628/ijsrst19633.
Surya Engineering College, & Institute of Electrical and Electronics Engineers. (n.d.). Proceedings of the 3rd International Conference on Computing Methodologies and Communication (ICCMC 2019) : 27-29, March 2019.
Vasumathi, M. T., & Kamarasan, M. (2019). Fruit disease prediction using machine learning over big data. International Journal of Recent Technology and Engineering, 7(6), 556–559.
https://doi.org/10.5121/cseij.2018.8101.
Christensen, T., Frandsen, A., Glazier, S., Humpherys, J., & Kartchner, D. (2018). Machine learning methods for disease prediction with claims data. Proceedings - 2018 IEEE International Conference on Healthcare Informatics, ICHI 2018, 467–471. https://doi.org/10.1109/ICHI.2018.00108.
Subhash Shirsath, S., & Patil, S. (2018). Engineering and Technology (A High Impact Factor. International Journal of Innovative Research in Science, 7.
https://doi.org/10.15680/IJIRSET.2018.0706059. [20] Chen, M., Hao, Y., Hwang, K., Wang, L., & Wang, L. (2017). Disease Prediction by Machine Learning over Big Data from Healthcare Communities. IEEE Access, 5, 8869– 8879. https://doi.org/10.1109/ACCESS.2017.2694446.