CODE-15%: a large scale annotated dataset of 12-lead ECGs
Abstract
A dataset of 12-lead ECGs with annotations. The dataset contains 345 779 exams from 233 770 patients. It was obtained through stratified sampling from the CODE dataset ( 15% of the patients). The data was collected by the Telehealth Network of Minas Gerais in the period between 2010 and 2016. This repository contains the files `exams.csv` and the files `exams_part{i}.zip` for i = 0, 1, 2, ... 17. "exams.csv": is a comma-separated values (csv) file containing the columns "exam_id": id used for identifying the exam; "age": patient age in years at the moment of the exam; "is_male": true if the patient is male; "nn_predicted_age": age predicted by a neural network to the patient. As described in the paper "Deep neural network estimated electrocardiographic-age as a mortality predictor" bellow. "1dAVb": Whether or not the patient has 1st degree AV block; "RBBB": Whether or not the patient has right bundle branch block; "LBBB": Whether or not the patient has left bundle branch block; "SB": Whether or not the patient has sinus bradycardia; "AF": Whether or not the patient has atrial fibrillation; "ST": Whether or not the patient has sinus tachycardia; "patient_id": id used for identifying the patient; "normal_ecg": True if automatic annotation system say it is a normal ECG; "death": true if the patient dies in the follow-up time. This data is available only in the first exam of the patient. Other exams will have this as an empty field; "timey": if the patient dies it is the time to…
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