Online Medical Management System

Project Title

Online Medical Management System

Project Area of Specialization Cloud Infrastructure,Project Summary

Online medical systems are commonly available in the hospital now. They are working extremely well in managing all the data inside a hospital like dispatching pay to all the medical staff, record keeping at the administrative end and some other tasks. We can notice here there is no mention of a doctor or a patient among the features of such a system

The three main stakeholders of any medical institution: Doctors, Patients and Pharmacists don’t have access to the system. It is therefore needed to develop a system which empowers these three key stakeholders by giving them access to the system with their own accounts incorporated inside the system.

This system takes care of the above problem by giving the three main stakeholders of the hospital access to the system where everyone has got their own accounts which are accessible from everywhere.

This project is divided into two modules:

Module 1:

Module 1 includes the management system in the form of a website and a mobile app. The website and mobile app can be accessed by anyone. Patients can sign up from anywhere whereas the doctors and pharmacists will have their login credentials added by the administration of the particular hospital using the system.

Following are the actions that the following accounts can take:

1) Patients can view their medical history, statistics of their blood vitals in the form of graphs and reports displayed in their dashboard. They can also view doctor’s information.

2) Doctors will be able to view a patient’s previous medical history with permission of that particular patient. They will be able to enter the prescription of patients which can then later be viewed by that particular patient.

3) Pharmacists have the record of the prescriptions being entered by the doctors which enables them to have the medicines ready for the patients when they get there.

Module 2:

Module 2 is prescription entering through conversion of handwriting into text.

Doctors will be able to either enter the prescriptions by typing in the particular fields using a keyboard or write the prescriptions by hand on a tablet. A deep learning algorithm will then convert the handwritten text into computer text which will then be stored inside a database ready to be retrieved by the patient and pharmacist account at anytime.

Project Objectives

• To facilitate the doctors for prescribing digitally
  • Conversion of handwritten text to machine readable text
• To improve the patient record maintenance
• To allow the patients and doctors to share and view their results when possible
• To bring different stakeholders like doctors, patients and pharmacists on a single platform
• To develop a multi-platform application

Project Implementation Method

Project implementation method is divided into the following four phases:

1. Requirement Phase:

In this phase we gathered all the requirements which were used for the development of our project.

• A local server for hosting the database and all the data of the patients, doctors and pharmacists. This is done by using an Apache server provided by XAMPP. Node.js provides a HTTP server for node.js development.
• Text Editor (Sublime Text, Visual Studio Code) to write all the HTML, CSS, PHP, Javascript etc. Android studio to develop android apps.
• Tensorflow bindings for javascript for handwriting conversion to computer text through deep learning
• Research papers and other material for literature review.

2. Development Phase:

In this phase, we identified different modules and then developed them

The list of modules developed is as follows:

• Website:

This website contains all the information regarding patients with portals of every patient through which they can log in and view their data. Doctors can enter prescriptions and pharmacists can view the prescriptions of all the patients as the doctor enters them. The database used is MYSQL which is a RDMS (Relational Database Management System). This website is deployed along with website on the server. The server environment used is Node.js.

• Mobile app:

The mobile app connects with the MYSQL database deployed with the server. The app is made using android studio the official integrated development environment by Google Android. The language used is Java.

• Conversion of handwriting into text:

The conversion of handwriting into computer text is carried out using TensorFlow which is a deep learning module. Convolutional Neural Networks are used to make a deep learning model which contains some features, labels and layers. The layers comprise of a
stack of Convolutional layer and a Max-pooling layer followed
by a fully connected layer. The inputs to the network are the features while the letter being recognized will be the output.

3. Testing Phase:

The modules are then tested individually through debugging. If any error occurs during debugging then the problem is searched on the internet, in different forums like Stackoverflow and Reddit.

4.Development Phase:

The modules are then integrated with each other and then the system is tested as a whole.
 

Benefits of the Project 1. Patient Record Management:

Patient record can be managed in a very orderly manner. One hasn’t got to carry tons of files for their previous medical record. Patients will be able to go empty handed to a doctor and the doctor will be able to see their medical history through this system.

2. Ease of Access:

This system is fairly easy to use. Almost anyone can use it as long as the person remembers his/her login credentials

3. Prescription Management:

This system will have a major benefit of prescription management at all ends. The doctor will have a nice formatted prescription in front of them. The patients will be able to get their medicines easily from the pharmacists without waiting in long lines. Similarly the pharmacists would be able to avoid long lines of patients in the hospital pharmacy as they will be able to hand out the medicines once the particular prescription gets updated on their account.

4. Conversion into text:

Handwriting is generally not that readable. By converting handwriting into text, the system gives the patients more readable data to comprehend.

Technical Details of Final Deliverable Module 1(Website/App Development): Website:

The website is made using Node.js as a backend.

Node.js is the most used server side technology in the world in comparison to other technologies mainly PHP and is used by companies like Microsoft, Netflix, Paypaletc

Following are the reasons why Node.js was preferred over PHP and other server side technologies:

a) The most important difference between Node.js and PHP is that most functions in PHP block until completion  while Node.js functions are non-blocking (commands execute concurrently or even in parallel). Due to this reason applications which require speed prefer Node.js over PHP.

b) Node.js’s package manager npm is the most used package manager in the world with hundreds and thousands of modules where as PHP’s dependency manager composer is not very popular and not used by that many people.

c) The same language i.e JavaScript can be used for both front end and back end development so we don’t have to learn another language like PHP for back end development which saves time and money.

The front end is basic HTML and CSS with bootstrap used as a front end framework. The templating engine used is Handlebars. The database used is MYSQL. MYSQL is the most popular SQL database and is an open source relational database management system. MYSQL database is deployed in the server from where it can be accessed through the website and app.

App:

The app is made using Android Studio which is the official integrated android app development platform for Google’s android operating system.

Module 2(Handwriting Conversion):

The handwriting is converted to text using Convolutional Neural Networks which is a class of deep learning. TensorFlow is used for deep learning which is a open source software library for deep learning from the Google Brain team.

In tensorflow convolutional neural networks are used

Convolutional Neural Networks are used to make a deep learning model which contains some features, labels and layers. The layers comprise of a
stack of Convolutional layer and a Max-pooling layer followed
by a fully connected layer. The inputs to the network are the features while the letter being recognized will be the output.

Final Deliverable of the Project HW/SW integrated systemType of Industry IT , Medical , Health Technologies Artificial Intelligence(AI), Cloud InfrastructureSustainable Development Goals Good Health and Well-Being for People, Industry, Innovation and InfrastructureRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	78000
Neo N2/M1 Smart Pen	Equipment	1	25000	25000
NeoLab Notebook	Equipment	1	5000	5000
Tablet(For handwriting input))	Equipment	1	20000	20000
Digiroot Universal Stylus or Similar	Equipment	3	6000	18000
Contingency/Exchange Rate Variation	Miscellaneous	1	5000	5000
Shipping Cost	Miscellaneous	1	5000	5000