Integration And Mining of Medical Records for Healthcare Services AWS Cloud

Project Code :TCMAPY739

Objective

In this application, the IoH data produced by patients are often distributed across different departments and contain partial patient privacy. Therefore, it is often a challenging task to effectively integrate or mine the sensitive IoH data without disclosing patient privacy. To tackle this challenge, we develop a novel multi-source medical data integration and mining solution for better healthcare services, named PDFM in Amazon web services.

Abstract

In this application the Internet of health (IOH) provides the medical sources to the doctors. In this initiative, traditional medical or health services are gradually transitioning to the Web or Internet, producing a large amount of medical data about patients, doctors, medicine, medical infrastructure, and so on. Effective integration and analyses of these IoH data will assist scientific disaster diagnosing and medical care services. However, IoH data is frequently distributed among departments and has only partial user privacy. As a result, efficiently integrating or mining critical IoH data while maintaining user privacy is typically a formidable task. To address the above- we developed PDFM, a multi-source medical data integration and analytical tool for revamped healthcare services, in response to the aforementioned challenge (Privacy-free Data Fusion and Mining). In this application four modules are there for serving the health care services, admin is useful for adding the doctors and patients to the hospitals, doctor is responsible for serving the medicines and precaution for the patients and provides appointment for the patients, IOH provides the medical data to the doctor based on their requirements. These all medical data sources and patient details are securely stored in the AWS cloud services (S3 Storage) which will provides the more security to data.

Keywords: IOH, PDFM, Medical Data Integration, Privacy, AWS Security, Healthcare Modules, Admin, Doctor.

NOTE: Without the concern of our team, please don't submit to the college. This Abstract varies based on student requirements.

Block Diagram

Specifications

H/W CONFIGURATION:

Processor - I3/Intel Processor

Hard Disk - 160GB

Key Board - Standard Windows Keyboard

Mouse - Two or Three Button Mouse

Monitor - SVGA

RAM - 8GB


S/W CONFIGURATION:

Operating System :  Windows 7/8/10

Server side Script         :  HTML, CSS, Bootstrap & JS

Programming Language     :  Python

Libraries         :  Flask, Pandas, Mysql.connector, Os, Smtplib, Numpy

IDE/Workbench :  PyCharm

Technology         :  Python 3.6+

Server Deployment         :  Xampp Server


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