Views provided by UsageCounts
{"references": ["S. Nandhini, Monojith Debnath, Anurag Sharma, Pushkar (2018), \"Heart disease prediction using machine learning\", Int. J. of Recent Eng. Res. and Develop., Volume 3, Issue 10, pp. 39\u201346", "Apurv Patel, Kunjal D. Khatri, Smit Kiri, Kathan Patel (2018), \"A literature review on heart disease prediction based on data mining algorithms\", Internat. J. for Res. Trends and Innov., Volume 3, Issue 6, pp. 100\u2013102", "Kumar G. Dinesh, Kumar D. Santhosh, K. Arumugaraj, V. Mareewari (1\u20133 March, 2018), \"Prediction of cardiovascular disease using machine learning algorithms\", International Conference on Current Trends towards Converging Technologies, Coimbatore, India", "V. V. Ramlingam, Ayantan Dandapath, M. Karthik Raja (2018), \"Heart disease prediction using machine learning techniques: A Survey\", Int. J. of Eng. and Tech., Volume 7, Issue 2.8, pp. 684\u2013687", "Meghana Padmanabhan, Pengyu Yuan, Govind Chada, Hien Van Nguyen (2019), \"Physician-friendly machine learning: A case study with cardiovascular disease risk prediction\", J. of Clin. Med., Volume 8, Issue 7, DOI: 10.3390/jcm8071050"]}
Heart Disease is one of transience reason in the present age as demonstrated by a particular course of action to diminish the amount of passing’ due to coronary disease, for instance cardiovascular breakdown, hypertension, coronary ailment, Arrhythmia needs to foresee suitably through detection systems. In most recent examination AI strategies has been utilized to enable the wellbeing to mind industry and diagnosis of heart related disease. Numerous amounts of patient’s reports are retained and techniques of machine learning such like K-Nearest Neighbor (KNN), Decision tree, Support Vector Machine (SVM), Naive Bayes, Random forest are used.
Data analysis, heart disease, hybrid technique, machine learning, http://matjournals.com/Engineering-Journals.html
Data analysis, heart disease, hybrid technique, machine learning, http://matjournals.com/Engineering-Journals.html
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
| views | 3 |

Views provided by UsageCounts