The CirCor DigiScope Dataset: From Murmur Detection to Murmur Classification.

Jorge Oliveira,Andoni Elola,Gari D Clifford,Miguel T Coimbra,Marcelo Nogueira,Cristina Oliveira,Reza Sameni,Carlos Ferreira,Sandra Mattos,Thamine Hatem,Alipio Jorge,Paulo Dias Costa,Thiago Tavares,Ali Bahrami Rad,Francesco Renna

doi:10.1109/jbhi.2021.3137048

Abstract

Cardiac auscultation is one of the most cost-effective techniques used to detect and identify many heart conditions. Computer-assisted decision systems based on auscultation can support physicians in their decisions. Unfortunately, the application of such systems in clinical trials is still minimal since most of them only aim to detect the presence of extra or abnormal waves in the phonocardiogram signal, i.e., only a binary ground truth variable (normal vs abnormal) is provided. This is mainly due to the lack of large publicly available datasets, where a more detailed description of such abnormal waves (e.g., cardiac murmurs) exists. To pave the way to more effective research on healthcare recommendation systems based on auscultation, our team has prepared the currently largest pediatric heart sound dataset. A total of 5282 recordings have been collected from the four main auscultation locations of 1568 patients, in the process, 215780 heart sounds have been manually annotated. Furthermore, and for the first time, each cardiac murmur has been manually annotated by an expert annotator according to its timing, shape, pitch, grading, and quality. In addition, the auscultation locations where the murmur is present were identified as well as the auscultation location where the murmur is detected more intensively. Such detailed description for a relatively large number of heart sounds may pave the way for new machine learning algorithms with a real-world application for the detection and analysis of murmur waves for diagnostic purposes.

Highlights

Cardiovascular disease (CVD) is an umbrella term used to define a heterogeneous group of disorders of the heart and vessels, such as coronary artery disease (CAD), valvular heart disease (VHD), or congenital heart disease (CHD) [1]
Due to the challenges associated with the care of individuals with complex CHD, exceptionally, a few young adults that voluntarily asked to participate in the screening campaigns were examined
The CirCor DigiScope dataset represents a unique cohort from a pediatric population, and a pregnant population, with significant congenital and acquired cardiac diseases

Summary

Introduction

Cardiovascular disease (CVD) is an umbrella term used to define a heterogeneous group of disorders of the heart and vessels, such as coronary artery disease (CAD), valvular heart disease (VHD), or congenital heart disease (CHD) [1].Manuscript received June XX, 2021; revised November YY, 2021. According to [4], CVD contribute to impoverishment due to health-related expenses and high outof-pocket expenditure. This imposes an additional burden on the economies of low-to-middle-income countries. RHD is the single largest cause of hospital admissions for children and young adults, with observations showing a high prevalence of the disease in young adults [8]. Blood flowing through these structures creates audible sounds, which are more significant when the flow is more turbulent [1].

Methods

Findings

Discussion

Conclusion