Prediction of Cardiovascular Diseases by Integrating Electrocardiogram (ECG) and Phonocardiogram (PCG) Multi-Modal Features using Hidden Semi Morkov Model

نویسندگان

چکیده

Because the health care field generates a large amount of data, we must employ modern ways to handle this data in order give effective outcomes and make successful decisions based on data. Heart diseases are major cause mortality worldwide, accounting for 1/3th all fatalities. Cardiovascular disease detection can be accomplished by disturbance cardiac signals, one which is known as phonocardiography. The aim project using machine learning categorize illness electrocardiogram (ECG) phonocardiogram (PCG) readings. investigation began with signal preprocessing, included cutting normalizing signal, was accompanied continuous wavelet transformation utilizing mother analytic morlet. results decomposition shown scalogram, predicted Hidden semi morkov model (HSMM). In first phase, submit dataset file choose an algorithm run chosen dataset. accuracy each selected method then predicted, along graph, modal built max frequency training it. following step, input parameter provided, sick stage heart created. We take measures patient's condition. When compared current approaches, suggested HSMM has 0.952 sensitivity, 0.92 specificity, 0.94 F-score, 0.91 ACC, 0.96 AUC.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Prediction of Cardiovascular Diseases Using an Optimized Artificial Neural Network

Introduction:  It is of utmost importance to predict cardiovascular diseases correctly. Therefore, it is necessary to utilize those models with a minimum error rate and maximum reliability. This study aimed to combine an artificial neural network with the genetic algorithm to assess patients with myocardial infarction and congestive heart failure.   Materials & Methods: This study utilized a m...

متن کامل

Classification of Cardiovascular Disease from ECG using Artificial Neural Network and Hidden Markov Model

this paper deals with the classification of cardiovascular disease for its future analysis. If future progression of the disease can be predicted earlier with proper change in medication patients treatment can be improved. Artificial neural network (ANN) is used as classifier with wavelet transform as the feature extraction for reducing data set of ECG. Hidden markov model (HMM) is used as pred...

متن کامل

Software Cost Regressing Testing Based Hidden Morkov Model

Maintenance of software system accounts for much of the total cost associated with developing software. The nature of the modifying the software is a highly error-prone task which is the main reason for the cost. Correcting fault by changing software or add new functionality can cause existing functionality to regress, introducing new faults. To avoid such defects, one can retest software after...

متن کامل

an investigation into translation of cultural concepts by beginner and advance student using think – aloud protocols

this research aims at answering the questions about translation problems and strategies applied by translators when translating cultural concepts. in order to address this issue, qualitative and quantitative study were conducted on two groups of subjects at imam reza international university of mashhad. these two groups were assigned as beginner and advanced translation students (10 students). ...

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: International Journal on Recent and Innovation Trends in Computing and Communication

سال: 2022

ISSN: ['2321-8169']

DOI: https://doi.org/10.17762/ijritcc.v10i10.5732