Predicting the Heart Disease Using Machine Learning Techniques
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-5224-1_21
Reference21 articles.
1. World Health Organization (WHO) (2017) Cardiovascular diseases (CVDs)—Key Facts
2. http://www.who.int/news-room/fact-sheets/detail/cardiovascular-diseases-(cvds). Accessed 22 Mar 2022
3. Goyal S (2023) Software measurements with machine learning techniques-a review. Recent Adv Comput Sci Commun 16:1–17. https://dx.doi.org/10.2174/2666255815666220407101922
4. Safdar S, Zafar S, Zafar N et al (2018) Machine learning based decision support systems (DSS) for heart disease diagnosis: a review. Artif Intell Rev 50:597–623. https://doi.org/10.1007/s10462-017-9552-8
5. Goyal S (2022) FOFS: firefly optimization for feature selection to predict fault-prone software modules. In: Nanda P, Verma VK, Srivastava S, Gupta RK, Mazumdar AP (eds) Data engineering for smart systems. Lecture Notes in Networks and Systems, vol 238. Springer, Singapore. https://doi.org/10.1007/978-981-16-2641-8_46
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