A Systematic Review of Fetal Cardiac Abnormality with Future Directions

Globally, the fetal cardiac abnormality is the primary reason for morality. However, understanding the huge amount of "Electrocardiogram (ECG)" signals generated from the sensors is exhausting. The machine learning approaches can be employed to assist the evaluation of these images and support identifying any dangerous cardiac anomalies in the fetus. But, traditional machine learning techniques still need improvements. Thus, this survey analyzes the existing strategies utilized for fetal cardiac abnormality detection tasks. The multimodal data and performance measures supported for the fetal cardiac abnormality detection tasks are categorized. The research gaps and challenges are provided to improve the new fetal cardiac abnormality detection mechanisms in the future.