Chatbot for healthcare system using AI

1. Presented by,
Vikash Chandra : 1OX18CS097
Kaushik M : 1OX18CS100
1
Overview of Internship Training
In
Compsoft Technologies
Department of Computer Science & Engineering
The Oxford College of Engineering
Under the guidance,
Mr. Nithin

2. Chatbot for Healthcare System Using AI
• Healthcare is a major issue all around the globe and in some
countries like the U.S.A.
• Healthcare is pretty expensive, so finding the right doctor
according to your symptoms is not only convenient but saves
both the doctor’s and patient’s time and also saves the patient’s
money.
• This project aims to create a healthcare chatbot to help both
doctors and patients have a convenient time while receiving
quality healthcare at the same time.
ABSTRACT

3. INTRODUCTION OF TRAINING
 Company :Compsoft Technologies
 Place : No 363-19th main road 1st block Rajajinagar Bangalore 560010
 Profile : IT service
 Domain :Machine learning with python
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4. INTRODUCTION ABOUT ORGANIZATION
Vision
 We are committed to going the extra mile to bring success to the clients
consistently.
 We are dedicated to delivering the right people, solutions, and services to
the clients that they require to meet their technology challenges and
business goals.
Mission
 Optimizing client satisfaction with quality services.
 Delivering the most efficient and the best solution to our clients to every
client leveraging leading technologies & industry best practices.


5.  We have a proven record of building highly scalable, world-
class consulting processes that offer tremendous business
advantages to our clients in the form of huge cost-benefits,
definitive results and consistent project deliveries across the
globe.
 We prominently strive to improve your business by delivering
the full range of competencies including operational
performance, developing and applying business strategies to
improve financial reports, defining strategic goals and measure
and manage those goals along with measuring and managing
them.
INTRODUCTION ABOUT DEPARTMENT

6. TECHNICAL TOOLS
 We have used multiple tools to implement this project.
 The implementation of code is done at machine learning.
 It is done through a website called www.heathcarepracto.com, data is stored in
csv files. Data set consists of the doctor’s photo, name, his experience, what
symptoms he can treat.
 They can be written in any python interpreter like colab, jupyter notebook or
even IDLE, make sure that your computer runs NumPy, pandas and matplotlib
functions properly to prevent errors. In this project, I will use google colab
because it works best for me.
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7. DURATION
This internship was taken up for 4 weeks Implementation
Start Date: 20th April 2022
End Date: 24th May 2022
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8. PROBLEM STATEMENT
• Healthcare is very important to lead a good life.
• However, it is very difficult to obtain a consultation with a doctor for every
health problem.
• The idea is to create a medical chatbot using Artificial Intelligence that can
diagnose the disease and provide basic details about the disease before consulting
a doctor.
• This will help to reduce healthcare costs and improve accessibility to medical
knowledge through medical chatbots.
• Chatbots are computer programs that use natural language to interact with users.
The chatbot stores the data in the database to identify the sentence keywords and
make a query decision and answer the question.
• Ranking and sentence similarity calculations are performed using n-gram, TFIDF
and cosine similarity.
• The score will be obtained for each sentence from the given input sentence and
more similar sentences will be obtained for the query given.
• The third-party, the expert program, handles the question presented to the bot that
is not understood or is not present in the database.

9. • The chatbots are conversational virtual assistants which automate
interactions with the users.
• Chatbots are powered by artificial intelligence using machine
learning techniques to understand natural language.
• The main motive of the paper is to help the users with minor
health information.
• Initially when the user visits the website first register themselves
and later can ask the bot their queries.
• The system uses an expert system to answer the queries if the
answer is not present in the database.
• Here the domain experts also should register themselves by
giving various details.
• The data of the chatbot is stored in the database in the form of a
pattern template. Here SQL is used for handling the database.
PROPOSED STATEMENT

10. SYSTEM REQUIREMENTS
Functional Requirements:
• Hardware Requirements
 Pentium Processor IV or Higher
 Min 10 GB HDD
 RAM 512 MB or Higher
 2.4 GHz or faster Processor
• Software Requirements
 Windows Vista onwards, Linux, Mac OS
 In the case of building the Project from the source
 Python Compiler
 TensorFlow Machine learning library
 Keras
 SciKit Learn
 Pandas
 NumPy
 Flask

11. • Performance Requirements:
 Should have a training error of as low as possible.
 Software Quality Attributes
 Robustness
 The formats of the scanned copies should be in the
standard format.
 Reliability
 Better learning methods
 Acquiring good accuracy results
Non-Functional Requirements:

12. IMPLEMENTATION / METHODOLOGY
Data Collection:
It is done through a website called www.heathcarepracto.com, data is stored in csv files.
Data set consists of the doctor’s photo, name, his experience, what symptoms he can treat
Programs:
They can be written in any python interpreter like colab, jupyter notebook or even IDLE,
make sure that your computer runs NumPy, pandas and matplotlib functions properly to
prevent errors. In this project, we will use Visual Studio Code because it works best for
me.
Software Testing:
The research in this thesis focuses on predicting the general symptoms of a patient and
suggests a doctor based on the symptoms they say yes to. It uses a csv database to store
data on doctors and retrieve them when needed depending upon the symptoms.

16. RESULT

18. CONCLUSION
 The Healthcare Chat bot is a handy application that suggests a doctor
depending upon what symptoms the patient might have and suggest based
on a yes/no option.
 But this healthcare chatbot could use some improvements in the login
screen and due to programming limitations, it is tedious to cycle through
yes/no questions, and it’d be harder to do so in emergency cases.
 This chatbot could use more websites to refer from to advise more
doctors.

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