Collecting Eye and Patient Care Project in python

Collecting Eye and Patient Care in python

 PROJECT ID: PYTHON36

 PROJECT NAME: Collecting Eye and Patient Care in python

 PROJECT CATEGORY: MCA / BCA / BCCA / MCM / POLY / ENGINEERING

PROJECT ABSTRACT:

Health systems in India are grappling with the effects of existing communicable and noncommunicable means to cater to the needs of the people. Lack of adequate progress on these underlying social determinants of health has been acknowledged as a glaring failure of public health.

Our main motto to take up this problem is to cater to each and every need of the patient as well as monitor his/her health from the time he/she first visits the hospital till he/she totally recovers.

Additional attention and adequate support to ensure faster recovery is not possible as there is no proper communication channel/link between the doctor and the patient after the check-up.

Due to insufficient data obtained in the form of feedback the government is unable to do the necessary improvements required in this field.

According to the statistics, feedback from merely 5-10% of the patients is collected monthly from any of the government aided medical centers.

The course of medication prescribed to patients is not monitored.

The staff is not monitored in terms of their behavior and supportiveness towards the needs of the patients.

Proposed Features:

Maintaining records of the patient for future use

Giving them reminders

Monitoring prescriptions given to the patients

Changing the prescription according to the availability of the medicines in the inventory to provide low-cost health services

Taking feedbacks over certain interval(through the algorithm we came up with) to keep track of patient’s health and report it to doctor

It will not only help us monitor the health services provided to the people but will, in turn, gain the trust of the people visiting these health centers.It will also encourage people to use medical facilities when required.

SOFTWARE REQUIREMENTS:

OS                                : Windows

Python IDE                  : Python 2.7.x and above

Language                             : Python Programming

Database                             : MYSQL

HARDWARE REQUIREMENTS:

 RAM                :  4GB and Higher

Processor          :  Intel i3 and above

Hard Disk         : 500GB Minimum

 

Setting up Software Environment

Python is a high level, interpreted, interactive and object-oriented scripting language.

Python is designed to be highly readable and has fewer syntactical constructions than other languages. Python is used in the development of this model. In this experiment, the following python libraries are used to develop the machine learning models:

• NLTK: It is a python package which works with human language data and provides an easy-to-use interface to different lexical resources like WordNet and text processing libraries. These lexical resources are used for classification, tokenization, stemming, tagging, parsing, and semantic reasoning [23].

• Pandas: It is a python package which acts as a data analysis tool and deals with data structures. Pandas carry out entire data analysis workflow in Python without having to switch to a more domain specific language like R [46].

• Tweepy: It is used in accessing the Twitter API by establishing the connection and to gather tweets from Twitter [24]. This module is used to stream live tweets directly from Twitter in real-time.

• Numpy: NumPy is the fundamental package for computing with Python. It is used to add support to multi-dimensional arrays and matrices, with a large collection of high-level mathematical functions [47].

• scikit-learn: It is a simple and efficient tool for data mining and data analysis [47]. • matplotlib python library which generates plots, histograms, power spectra, bar charts, etc.

In this work matplotlib.pyplot module is used to plot the metrics [47].

• Gensim It is used to automatically extract semantic topics from documents, as efficiently as possible. Gensim is designed to process raw, unstructured text data. The algorithms in Gensim, such as Word2Vec where it automatically discovers the semantic structure of phrase by examining statistical co-occurrence patterns within a corpus of training documents. These algorithms are unsupervised. Once these statistical patterns are found, any plain text documents can be succinctly expressed in the new, semantic representation and queried for topical similarity against other documents [48].

• Keras: Keras is a high-level neural networks API, written in Python and capable of running on top of TensorFlow, CNTK, or Theano. It was developed with a focus on enabling fast experimentation. Being able to go from idea to result with the least possible delay is key to doing good research.

TABLE OF CONTENTS

·        Title Page      

·        Declaration

·        Certification Page

·        Dedication

·        Acknowledgements

·        Table of Contents

·        List of Tables

·        Abstract

CHAPTER SCHEME

CHAPTER ONE: INTRODUCTION

CHAPTER TWO: OBJECTIVES

CHAPTER THREE: PRELIMINARY SYSTEM ANALYSIS

·         Preliminary Investigation

·         Present System in Use

·         Flaws In Present System

·         Need Of New System

·         Feasibility Study

·         Project  Category

CHAPTER FOUR: SOFTWARE ENGINEERING AND PARADIGM APPLIED   

·         Modules

·         System / Module Chart

CHAPTER FIVE: SOFTWARE AND HARDWARE REQUIREMENT

CHAPTER SIX: DETAIL SYSTEM ANALYSIS

·         Data Flow Diagram

·         Number of modules and Process Logic

·         Data Structures  and Tables

·         Entity- Relationship Diagram

·         System Design

·         Form Design 

·         Source Code

·         Input Screen and Output Screen

CHAPTER SEVEN: TESTING AND VALIDATION CHECK

CHAPTER EIGHT: SYSTEM SECURITY MEASURES

CHAPTER NINE: IMPLEMENTATION, EVALUATION & MAINTENANCE

CHAPTER TEN: FUTURE SCOPE OF THE PROJECT

CHAPTER ELEVEN: SUGGESTION AND CONCLUSION

CHAPTER TWELE: BIBLIOGRAPHY& REFERENCES          

Other Information

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PROJECT WITH HARD BINDING	1850/- Only
TOTAL COST (SYNOPSIS, SOFTCOPY, HARDBOOK, and SOFTWARE, PPT)	2500/- Only
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