Graduate project

A health diagnostic tool for tracking and predicting diseases from blood examination report

The health-care industry is coming up with new techniques every day to improve the quality of service and treatment methodology. Prominent application of Artificial intelligence is done to serve these purposes. The enormous data generated by the health-care industry is used by the IT industry, who analyze it, and try to develop solutions for everyday problems that arise in the field of medicine. This research paper is based on a diagnostic tool built to help with the assessment of bloodwork reports and interpret it to know of any occurrence of diseases. The tool has value because it helps the examinee to get cost effectively an explanation of what the blood examination report holds and assist in any further diagnosis and treatment at any stage. The aim of the research is also to make a cost-effective tool so as to reduce the high cost-incurring clinic appointments and other expenses around it, while giving the examinee all the information they need to understand the report. The tool currently predicts the occurrence of Diabetes, Breast Cancer, Cardiovascular Diseases and Obesity, and the results show that the model is promising and effective in its prediction. It helps with suggestions if critical help is needed right away or self-measures can be taken to reduce the existing condition, like lifestyle changes, dietary changes, exercises etc. To overcome this challenge, we have used Machine Learning techniques and Algorithms and open source datasets from Kaggle. The model is deployed for everyone to use at shunaizz.pythonanywhere.com/ as a Cloud-based Application.

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