Implementation of Deep Learning Method for Prediction of Cardiovascular Disease Test phase, srs, design phase and source code final deliverable
Project Domain/ Category
Artificial Intelligence Deep learning
Abstract/ Preface
Cardiovascular complaint (CVD) is a general term for conditions affecting the heart or blood vessels, world Health Organization (WHO
. https//www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds).
The program will be enforced to prognosticate the Cardiovascular Disease by using deep literacy styles. In this system, it’ll be considered conditions that use UCI machine literacy depository dataset for trial ( particular Cardiovascular Disease dataset) as given below links handed.
Functional Conditions
1. There are seven major tasks you’ll generally perform when developing a system. Tasks (2-7) should be enforced internally while developing the system.
i. Task 1 Define the problem and elect the dataset as any type of
Cardiovascular Disease ii. Task 2 Data Analysis and Preprocessing
iii. Task 3 Point Birth iv. Task 4 Vaticination
v. Task 5 Figure system
vi. Task 6 Test System
vii. Task 7 Tune System
2. The program should have a knowledge- grounded system according to select data (Structured or Unshaped data).
3. The program should have the deep literacy algorithm to execute model vaticination.
4. The program should estimate the performance and update knowledge grounded on the demand.
Note Skype sessions must be attended to communicate with the administrator about deep literacy styles else project won’t be accepted.
Tools/ language Python language
DataSeT https//archive.ics.uci.edu/ml/datasets/heart complaint https//www.kaggle.com/ronitf/heart-disease-uci https//ieee-dataport.org/documents/cardiovascular-disease-dataset
Prerequisite Deep Literacy Generalities, scholars will cover a short course applicable to the mentioned generalities besides SRS and design original attestation.
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