Total heartbeats in training dataset classes before and after SMOTE.

Figshare2023-04-25 更新2026-04-28 收录

数据链接：

https://figshare.com/articles/dataset/Total_heartbeats_in_training_dataset_classes_before_and_after_SMOTE_/22694052 数据链接链接失效反馈

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资源简介：

Total heartbeats in training dataset classes before and after SMOTE.

创建时间：

2023-04-25

Artificial and Real dataset with different concept drift type and imbalance ratio

概念漂移检测

类别不平衡

The zip file contains both real and artificial datasets having different concept drift type and imbalance ratio. The real datasets are usually used as a benchmark for concept drift problems and they a

NIAID Data Ecosystem120

TF-C Pretrain ECG

心电图分类

心律失常预测

- Paper: Self-Supervised Contrastive Pre-Training For Time Series via Time-Frequency Consistency - Paper link: - Github repo: https://github.com/mims-harvard/TFC-pretraining - Project website: <s

Figshare2022-05-31 更新30

Classification model parameter settings.

心电图分类

心律失常检测

With over a century of development, electrocardiogram (ECG) diagnostics has become the preferred tool for healthcare professionals in cardiovascular disease diagnosis and monitoring. As wearable devic

Figshare2025-08-22 更新10

AF_Classification_from_a_Short_etc

心电图分类

心律失常检测

2017 年 PhysioNet/CinC 挑战赛旨在鼓励开发算法来分类，从单个短 ECG 导联记录（长度在 30 秒到 60 秒之间），记录是否显示正常窦性心律、心房颤动 (AF)、替代节奏，或者太吵而无法分类。有多种类型的心律失常可按以下分类：起源：房性心律失常、交界性心律失常或室性心律失常。频率：心动过速（成人 > 100 次每分钟 (bpm)）或心动过缓（成人 < 60 bpm）。

OpenXLab90

Three groups with class-imbalance ( π 1 = 0.4, π 2 = 0.2, π 3 = 0.4), dense block diagonal structure ( ρ = 0.9) and small mean difference ( γ = 0.1).

类别不平衡

分类器性能评估

Three groups with class-imbalance (π1 = 0.4, π2 = 0.2, π3 = 0.4), dense block diagonal structure (ρ = 0.9) and small mean difference (γ = 0.1).

NIAID Data Ecosystem20