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Patient data can be used for medical diagnosis

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30 Oct 2019CPOL
Storing and analyzing various patient data can be useful for diagnosis and prediction

This article is part of the Cloud AI Challenge with SAP HANA and Amazon SageMaker. This entry is not meant to be a full article - it's purely just an outline of an idea - and will be removed once the contest has concluded.

Introduction

Patient data can be collected and stored for diagnosis, risk analysis and predictions

Topic

Medical field can be a good place to use machine learning models and algorithms.  We can store the different parameters of a patient such as age, weight, height, sex, smoking, drinking habits, Blood pressure and other different parameters such as blood sugar level etc. Also diseases treated or experienced can be saved for statistics.

Based on these dataset, we can come up with the statistics of which agegroup, sex or people with smoking or drinking habits are susceptible to diseases.  This can also be useful in recommending medicines, predicting re-admissions and identifying high risk patients. 

 

Points of Interest

 

Medical field is ever improving with the increasing technology and treatments being used for patients. Usage of Machine learning techniques can be helpful in diagnosing and treating patient ailments. 

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License

This article, along with any associated source code and files, is licensed under The Code Project Open License (CPOL)

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About the Author

Krishna P Seetharaman
Architect Aspire Systems India(Pvt) Ltd
India India
Technical expertise in working with microsoft technologies such as VC++, C#, ASP.NET, SQL Server, SharePoint, BizTalk. Currently working in middleware tools such as: Informatica Cloud, Mule Soft, Dell Boomi

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Posted 30 Oct 2019

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