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Medical System for Diagnosis of Cardio Vascular Diseases

Medical System for Diagnosis of Cardio Vascular Diseases

          
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About the Book

Heart attack is one of the most serious problems of the healthcare industry in India. While it has

been known that Indians are prone to heart attacks a decade earlier than their western

counterparts, experts have expressed concerns over lowering of patient's age. Today's fast paced

lifestyle has brought in a lot of negative impacts on the mind, body and heart. Irregular sleeping

patterns, bad eating habits, skipped meals lead to harmful diseases. Also the prevalence of heart

attacks amongst younger lot is on a steady rise. Data has also revealed that 48 percent of patients

hospitalized for cardiac emergencies in 2018 were less than 50 years of age. The awareness

about the heart failure is very low in our country. Most people do not know the difference

between a heart attack and heart failure. In this experiment, we used Machine Learning

approaches to identify whether a person (Elders and Teenagers) has heart disease or not (and then

compared them). The teenager data is collected through a survey done using Google form and the

data of person whose age is greater than 40 is used from UCI research site for study purpose,

which is refined and cleaned and is then processed using various Soft Computing Techniques .

The results thus produced are then analyzed and a plausible prediction is made regarding the

accuracy in diagnosing and predicting heart disease. Here we are using KNN, tree, SVM,

Random forest, Neural Network, Naïve Bayes, CN2, XGBoost, SMOTE and Adaboost as our

soft computing method, which is combination of fuzzy logic and artificial neural network. It is

called Adaptive because it is a closed loop system. This research study is an attempt to reduce

the efforts and time put in by the doctor by automating the risk prediction with the help of a Soft

Computing technique. The resulting system will contribute more effectiveness and will give

more than 90% accuracy to predict Heart diseases.

The soft computing tools are today's need in health care application, which can perform data

analysis and modeling, and they can assist the physician to make right and prompt clinical

decisions. Extracting patterns from the patient's information that tie predictor's variables in a

health science database is the topic of data mining.


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Product Details
  • ISBN-13: 9788729562436
  • Publisher: Independent Author
  • Publisher Imprint: Independent Author
  • Height: 229 mm
  • No of Pages: 280
  • Spine Width: 15 mm
  • Width: 152 mm
  • ISBN-10: 8729562430
  • Publisher Date: 28 Nov 2022
  • Binding: Paperback
  • Language: English
  • Returnable: Y
  • Weight: 381 gr


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