An Optimized Model For Estimation Of Coronary Artery Calcium Score Using Intelligent System

@article{1701177,
      author = {Ajinkya Sanjay Jambhale, Samidha Subhash Gawade, Sandesh Sanjay Jadhav},
      title = {An Optimized Model For Estimation Of Coronary Artery Calcium Score Using Intelligent System},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {2},
      number = {10},
      pages = {201-203},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1701177.pdf},
      abstract = {In past decades, cardiovascular diseases are the one that causes most deaths in the world. The more Coronary Artery Calcium Score (CACS) is, the higher the risk of a heart attack. Therefore, CACS is important for the determination of the risk of heart attack. We will make use of Intelligent System to determine the CACS. For this purpose, we collect different parameters like BP, BMI, Calcium Score etc. from UCI Machine learning repository which will be used for learning purpose to predict CACS. From the predicted CACS, we will apply fuzzy logic which will help to define the ranges in more detail. These ranges will define the risk of heart attack.},
      keywords = {Artificial Neural Network (ANN); Coronary Artery Calcium Score (CACS); Fuzzy Logic},
      month = {April},
  }