Musa Nehemiah
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Research Subjects
Musa Nehemiah has a total of 13 co-authors. Here are the top co-authors by number of shared publications:
- Abdulkareem Ayopo Oloyede
Department of Telecommunication Science, University of Ilorin, Ilorin 240003, Nigeria
1 shared publication - Abdulsalam Ya’u Gital
Department of Mathematical Sciences, Abubakar Tafawa Balewa University, Bauchi, Nigeria
1 shared publication - Abubakar Abdulkarim
Department of Electrical Engineering, Ahmadu Bello University, Zaria 810107, Nigeria
1 shared publication - Hammed Adeleye Mojeed
Gdansk University of Technology, Poland
1 shared publication - Haruna Chiroma
College of Computer Science and Engineering, University of Hafr Batin, Hafr Batin, Saudi Arabia
1 shared publication - Ifada Emmanuel
Department of Electrical and Computer Engineering, McGill University, Montreal, QC H3A 0E9, Canada
1 shared publication
Latest Publications
- Open Access
- 2 December 2022
- Published by MDPI AG in Applied Sciences
- Vol. 12 (23) , 12342
Expert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions
Electrocardiography (ECG) is one of the most widely used recordings in clinical medicine. ECG deals with the recording of electrical activity that is generated by the heart through the surface of the body. The electrical activity generated by the heart is measured using electrodes that are attached to the body surface. The use of ECG in the diagnosis and management of cardiovascular disease (CVD) has been in existence for over a decade, and research in this domain has recently attracted large attention. Along this line, an expert system (ES) and decision support system (DSS) have been developed for ECG interpretation and diagnosis. However, despite the availability of a lot of literature, access to recent and more comprehensive review papers on this subject is still a challenge. This paper presents a comprehensive review of the application of ES and DSS for ECG interpretation and diagnosis. Researchers have proposed a number of features and methods for ES and DSS development that can be used to monitor a patient’s health condition through ECG recordings. In this paper, a taxonomy of the features and methods for ECG interpretation and diagnosis were presented. The significance of the features and methods, as well as their limitations, were analyzed. This review further presents interesting theoretical concepts in this domain, as well as identifies challenges and open research issues on ES and DSS development for ECG interpretation and diagnosis that require substantial research effort. In conclusion, this paper identifies important future research areas with the purpose of advancing the development of ES and DSS for ECG interpretation and diagnosis.
- 2 December 2022
- Published by MDPI AG in Applied Sciences
- Vol. 12 (23) , 12342
Open AccessExpert System and Decision Support System for Electrocardiogram Interpretation and Diagnosis: Review, Challenges and Research Directions
Electrocardiography (ECG) is one of the most widely used recordings in clinical medicine. ECG deals with the recording of electrical activity that is generated by the heart through the surface of the body. The electrical activity generated by the heart is measured using electrodes that are attached to the body surface. The use of ECG in the diagnosis and management of cardiovascular disease (CVD) has been in existence for over a decade, and research in this domain has recently attracted large attention. Along this line, an expert system (ES) and decision support system (DSS) have been developed for ECG interpretation and diagnosis. However, despite the availability of a lot of literature, access to recent and more comprehensive review papers on this subject is still a challenge. This paper presents a comprehensive review of the application of ES and DSS for ECG interpretation and diagnosis. Researchers have proposed a number of features and methods for ES and DSS development that can be used to monitor a patient’s health condition through ECG recordings. In this paper, a taxonomy of the features and methods for ECG interpretation and diagnosis were presented. The significance of the features and methods, as well as their limitations, were analyzed. This review further presents interesting theoretical concepts in this domain, as well as identifies challenges and open research issues on ES and DSS development for ECG interpretation and diagnosis that require substantial research effort. In conclusion, this paper identifies important future research areas with the purpose of advancing the development of ES and DSS for ECG interpretation and diagnosis.