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Conference Open access

Smart Health Prediction Using Machine Learning

2025 · Proceedings of the 1st International Conference on Interdisciplinary Research in Science, Engineering, and Technology · pp. 383-388 · 0 citations · 14 references

TL;DR

Smart Health Forecasting based on the indicators that users or patients provide to the system, a machine learning and predictive modeling system forecasts their illnesses and improves a number of features of healthcare applications by providing a thorough explanation of medical data.

Abstract

: Currently, one of the most significant domestic issues affecting our country is health care. A healthy start in life depends on access to healthcare. Seeing a doctor, however, can be difficult if you have any health issues. Smart Health Forecasting based on the indicators that users or patients provide to the system, a machine learning and predictive modeling system forecasts their illnesses. The healthcare sector and other industries generate a significant amount of data. Humans cannot handle such vast amounts of data quickly enough to diagnose illnesses and recommend remedies. To reduce this human work and generate dependable results, we have investigated machine learning algorithms and data management strategies. Additionally, it improves a number of features of healthcare applications by providing a thorough explanation of medical data. The latest, most powerful technologies will reduce the physical work that experts have to do. Collecting patient, diagnostic, and other data is its primary objective. Entering, storing, accessing, and changing patient and physician data as needed is the system's primary duty. Information about the patient, including their diagnosis, is input into the system and shown on the screen. The only way to access the health prediction system is with a username and password. It can be accessed by a receptionist or administrator. Processing is fairly fast, and the data is safely stored for personal use.

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