Heart plus
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A disorder or illness called heart failure results in the heart becoming weak or
damaged. In order to avoid heart failure early on, it is crucial to understand the
causes of heart failure. Based on validation, two experimental processing steps
will be applied to the dataset of clinical records related to heart failure. Testing
will be done in the first step utilizing six different classification algorithms,
including K-nearest neighbor, neural network, random forest, decision tree,
Naïve Bayes, and support vector machine (SVM). Cross-validation was
employed to conduct the test. According to the results, the random forest
algorithm performed better than the other five algorithms in tests employing
the algorithm. Subsequent testing uses an algorithm with the best accuracy
value, which will then be tested again using split validation with varying split
ratios and genetic algorithms as a selection feature. The value generated from
testing using the genetic algorithm selection feature is better than the random
forest algorithm alone, which is recorded to produce an accuracy value of
93.36% in predicting the survival of heart failure patients.Heart failure prediction based on random forest algorithm using genetic algo...
Heart failure prediction based on random forest algorithm using genetic algo...International Journal of Reconfigurable and Embedded Systems
Explore our latest blog post uncovering the digital revolution reshaping cardiovascular care! From wearable technology providing real-time heart monitoring to AI-driven diagnostics revolutionizing early detection, we delve into the significant impact technology has on heart health.
Cardiovascular Health in the Digital Age_ How Technology is Impacting Heart C...
Cardiovascular Health in the Digital Age_ How Technology is Impacting Heart C...Cardiology Associates of Morristown
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Similar to Heart plus
A disorder or illness called heart failure results in the heart becoming weak or
damaged. In order to avoid heart failure early on, it is crucial to understand the
causes of heart failure. Based on validation, two experimental processing steps
will be applied to the dataset of clinical records related to heart failure. Testing
will be done in the first step utilizing six different classification algorithms,
including K-nearest neighbor, neural network, random forest, decision tree,
Naïve Bayes, and support vector machine (SVM). Cross-validation was
employed to conduct the test. According to the results, the random forest
algorithm performed better than the other five algorithms in tests employing
the algorithm. Subsequent testing uses an algorithm with the best accuracy
value, which will then be tested again using split validation with varying split
ratios and genetic algorithms as a selection feature. The value generated from
testing using the genetic algorithm selection feature is better than the random
forest algorithm alone, which is recorded to produce an accuracy value of
93.36% in predicting the survival of heart failure patients.Heart failure prediction based on random forest algorithm using genetic algo...
Heart failure prediction based on random forest algorithm using genetic algo...International Journal of Reconfigurable and Embedded Systems
Explore our latest blog post uncovering the digital revolution reshaping cardiovascular care! From wearable technology providing real-time heart monitoring to AI-driven diagnostics revolutionizing early detection, we delve into the significant impact technology has on heart health.
Cardiovascular Health in the Digital Age_ How Technology is Impacting Heart C...
Cardiovascular Health in the Digital Age_ How Technology is Impacting Heart C...Cardiology Associates of Morristown
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Heart plus
- 1. Hyorim Woo, CEO imrimee@gmail.com 1 Smart Health Care AI-Based Heartbeat Monitor System Heart+
- 2. Heart➕ Problem 2 1st Coronary Heart Disease 2nd Heart Stroke The Top 10 causes by Death Worldwide http://www.who.int/mediacentre/factsheets/fs310/en/index2.html The causes by Death in Korea http://kosis.kr/ 12% of Death from Heart Disease
- 4. Heart➕ Product : Heart Monitor System 4 1.Measure 2.Detect 3.Notify
- 5. Heart➕ Market Size 5 7 million - heart disease 12% die unexpectedly7 M The causes by Death in Korea http://kosis.kr/
- 6. Heart➕ Competition 6 Monitoring Heartbeats Heart➕ iBeat iRhythm 24 hours / 7 days √ √ On Wrist √ √ Alert to doctor √ Roll-Around √ √ √
- 7. Heart➕ Team 7 Hyorim Woo, CEO MS of Computer Science Daegu Bank Software support Nexii, Project Manager Dongju Kim, CTO MS of Computer Science Samsung Electronics SW eng. Software Consultant of A.I. Heejin Song, PhD. COO PhD of BioMedical Engineering Massachusetts General Hospital Yangsan Hospital in Korea
- 8. Heart➕ Milestone 8 2 K 2018 2019 2020 $450 K 2021
- 9. Heart➕ Contact Info 9 Hyorim Woo, CEO imrimee@gmail.com +82-01-4476-2101