Making heart diseases detectable. The invention of an algorithm for systematically predictions (eBook)

Daniyal Baig (Autor)

eBook Download: PDF

2020 | 1. Auflage
15 Seiten
GRIN Verlag
978-3-346-29762-4 (ISBN)

Infos

Research Paper (postgraduate) from the year 2020 in the subject Computer Science - Programming, grade: 3, , course: Machine learning, language: English, abstract: In this research paper it will be conducted and experimentally analysed to seek an improved method to predict heart disease in the upcoming years. So efficient steps can be taken in order to predict and treat the avoidable fatal heart problem. This work will be creating an efficient algorithm which will detect the disease on the basis of some parameters and give as much accurate information as possible. By using this method one can systematically predict the risk of suffering from this disease. The main feature utilized in the detection will include age, gender, max heart rate, exercise induced angina etc.

In today’s world the heart disease is increasing. Hence a lot of data related to the heart disease is being collected by using data mining. This important can be evaluated and used to predict and detect the coronary artery disease and heart related problem before the occurrence of the fatal experience. Many different types of life threating diseases are amongst people but heart disease has been studied the most in medical research. Early diagnosis of the disease is a very difficult task. We want to introduce an automated way of prediction of heart disease in individuals. This solution is not one and all solution but it will serve as a complementary diagnosis in the field of medical research. The main task in heart disease is to detect the disease early and treat it efficiently before any fatal experience occurs.

Produkt-Details

• Erscheint lt. Verlag: 17.11.2020
• Verlagsort: München
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge
• Schlagworte: detection • machine learning
• ISBN-10: 3-346-29762-4 / 3346297624
• ISBN-13: 978-3-346-29762-4 / 9783346297624