PVC_detection Object Detection Dataset and Pre-Trained Model by PVC

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Explore Dataset

Here are a few use cases for this project:

Cardiology Research: Researchers in the field of cardiology can use the PVC_detection model to analyze medical datasets containing electrocardiograms (ECGs) for better understanding and pattern recognition of various cardiac conditions, such as normal sinus rhythms, premature ventricular contractions (PVC), right bundle branch blocks (RBBB), left bundle branch blocks (LBBB), and intraventricular conduction delays (IT).
Automated ECG Analysis: The PVC_detection model can be integrated into clinical software systems for providing real-time automated analysis of patients' ECG data, improving the speed and accuracy of detecting abnormalities, identifying potential cardiac issues, and assisting healthcare professionals in making more informed decisions in patient care.
Remote Monitoring: The model can be used in telehealth and remote monitoring applications, enabling patients to transmit ECG data from home-based or wearable devices directly to healthcare professionals, who can then monitor and assess cardiac health remotely using the PVC_detection model's classifications.
Medical Training and Education: The PVC_detection model can be used as an educational tool for medical students and professionals, enabling them to practice identifying and interpreting various ECG patterns, to improve their diagnostic skills and clinical decision-making abilities.
Fitness and Health Applications: Fitness enthusiasts and athletes could utilize the PVC_detection model to assess their cardiac health in conjunction with wearable devices or mobile applications. This information could help users understand their heart's response to physical activity, track their cardiac fitness progress, and guide them in optimizing their workout regimen based on their individual cardiac health.

Trained Model API

This project has a trained model available that you can try in your browser and use to get predictions via our Hosted Inference API and other deployment methods.

Cite This Project

If you use this dataset in a research paper, please cite it using the following BibTeX:

@misc{
                            pvc_detection_dataset,
                            title = { PVC_detection Dataset },
                            type = { Open Source Dataset },
                            author = { PVC },
                            howpublished = { \url{ https://universe.roboflow.com/pvc-kcao8/pvc_detection } },
                            url = { https://universe.roboflow.com/pvc-kcao8/pvc_detection },
                            journal = { Roboflow Universe },
                            publisher = { Roboflow },
                            year = { 2022 },
                            month = { dec },
                            note = { visited on 2024-06-20 },
                            }