Most Probable Explanation for MetaProbLog and Its Application in Heart Sound Segmentation

نویسندگان

  • Theofrastos Mantadelis
  • Jorge Oliveira
  • Miguel Tavares Coimbra
چکیده

This paper, presents ongoing work that extends MetaProbLog with Most Probable Explanation (MPE) inference method. The MPE inference method is widely used in Hidden Markov Models in order to derive the most likely states of a model. Recently, we started developing an application that uses MetaProbLog to models phonocardiograms. We target to use this application in order to diagnose heart diseases by using phonocardiogram classification. Motivated by the importance of phonocardiogram classification, we started the implementation of the MPE inference method and an improvement of representation for annotated disjunctions.

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Design of Persian Karbandi: The Problem of Dividing the Base from a Mathematical Viewpoint

Karbandi is the structure of a kind of roofing in Persian architecture. One of the main issues related to the design of karbandi is that, due to its geometrical structure, it is not possible to design any desired karbandi on a given base. Therefore, it is necessary for the designer to be able to discern the proper karbandi for a given base. The most critical stage in designing a karbandi is whe...

متن کامل

Using Probabilistic Logic Programming to Find Patterns

This short paper, briefly presents the probabilistic logic programming language ProbLog and the system MetaProbLog. We present an example Hidden Markov Model to illustrate the three main tasks of the system. Furthermore, we mention some of the existing ProbLog applications which are used to find connections/patterns in relational databases. Finally, we present an application that uses MetaProbL...

متن کامل

A New Method to Improve Automated Classification of Heart Sound Signals: Filter Bank Learning in Convolutional Neural Networks

Introduction: Recent studies have acknowledged the potential of convolutional neural networks (CNNs) in distinguishing healthy and morbid samples by using heart sound analyses. Unfortunately the performance of CNNs is highly dependent on the filtering procedure which is applied to signal in their convolutional layer. The present study aimed to address this problem by a...

متن کامل

Accessing heart dynamics to estimate durations of heart sounds.

Segmentation of the phonocardiogram into its major sound components is the first step in the automated diagnosis of cardiac abnormalities. Almost all of the existing phonocardiogram segmentation algorithms utilize absolute amplitude or frequency characteristics of heart sounds, which vary from one cardiac cycle to the other and across different patients. The objective of this work is to provide...

متن کامل

شناسایی جریان‌های زیردریایی توسط امواج صوتی

Acoustic wave propagates properly in water, whilst most forms of electromagnetic waves, particularly in salty and dense sea water, are attenuated after a few tens or hundreds of meters so that it will be impossible to trace and detect them. This paper presents a special method for recognizing probable underwater currents, and reconstruction of their intensities, widths, and directions by usin...

متن کامل

ذخیره در منابع من


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

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

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015