Pinned Repositories
-NC-paper-automatic-ecg-diagnosis
Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".
-PhySO-
这是物理学公式拟合工具PhySo（Φ-SO）的demo的中文注释项目，帮助需要快速入门此工具的**科研人员初步熟悉该工具的使用
AMI-database1
Andrew-Ng_ecg
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
ecg-age-prediction
Scripts and modules for training and testing neural network for age prediction from the ECG. Companion code to the paper "Deep neural network-estimated electrocardiographic age as a mortality predictor".
ECG-With-Scatter-Graph
MITAB_ECG_CNN_Classification
Basic Algorithm For Beginners （Python version）
Mousavi2018_ECG-Heartbeat-Classification-seq2seq-model
Inter- and intra- patient ECG heartbeat classification for arrhythmia detection: a sequence to sequence deep learning approach
SOTA_ecg-classification
ECG Arrhythmia classification using CNN
Zero-Shot-ECG
A Personalized Zero-Shot ECG Anomaly Monitoring System: From Sparse Representation Based Domain Adaption to Energy Efficient Suspicious Beat Detection for a Practical ECG Surveillance
WangMengxiao319's Repositories
WangMengxiao319/-NC-paper-automatic-ecg-diagnosis
Scripts and modules for training and testing neural network for ECG automatic classification. Companion code to the paper "Automatic diagnosis of the 12-lead ECG using a deep neural network".
WangMengxiao319/ecg-age-prediction
Scripts and modules for training and testing neural network for age prediction from the ECG. Companion code to the paper "Deep neural network-estimated electrocardiographic age as a mortality predictor".
WangMengxiao319/ECG-With-Scatter-Graph
WangMengxiao319/MITAB_ECG_CNN_Classification
Basic Algorithm For Beginners （Python version）
WangMengxiao319/Mousavi2018_ECG-Heartbeat-Classification-seq2seq-model
Inter- and intra- patient ECG heartbeat classification for arrhythmia detection: a sequence to sequence deep learning approach
WangMengxiao319/SOTA_ecg-classification
ECG Arrhythmia classification using CNN
WangMengxiao319/Zero-Shot-ECG
A Personalized Zero-Shot ECG Anomaly Monitoring System: From Sparse Representation Based Domain Adaption to Energy Efficient Suspicious Beat Detection for a Practical ECG Surveillance
WangMengxiao319/-PhySO-
这是物理学公式拟合工具PhySo（Φ-SO）的demo的中文注释项目，帮助需要快速入门此工具的**科研人员初步熟悉该工具的使用
WangMengxiao319/AMI-database1
WangMengxiao319/Andrew-Ng_ecg
Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network
WangMengxiao319/ARCADE_submit
Submit Page for ARCADE challenge for MICCAI Conference
WangMengxiao319/ArrowCMR
Repository for FPGA and ARM code for Arrow CMR development board
WangMengxiao319/AutoSAM
finetuning SAM with non-promptable decoder on medical images
WangMengxiao319/choice_stu_no_register
选择今日未打卡的人，并粘贴在剪贴板
WangMengxiao319/Coursera-ML-AndrewNg-Notes
吴恩达老师的机器学习课程个人笔记
WangMengxiao319/Deep-Learning-Coursera
吴恩达深度学习课程课后编程作业
WangMengxiao319/deeplearning_ai_books
deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）
WangMengxiao319/deeplearningbook-chinese
Deep Learning Book Chinese Translation
WangMengxiao319/fastbook
The fastai book, published as Jupyter Notebooks
WangMengxiao319/LAVIS
LAVIS - A One-stop Library for Language-Vision Intelligence
WangMengxiao319/Machine-Learning-Notes
白板推导系列课程笔记 初版
WangMengxiao319/MATLAB_DOF4
Analyzing the system with four degrees of freedom, from the homework of <Mechanical System Dynamics>
WangMengxiao319/Oxyford_MI-MultiLabel
WangMengxiao319/PhySO
Physical Symbolic Optimization
WangMengxiao319/RTA-CNN
The code of An End-to-End Atrial Fibrillation Detection by A Novel Residual-Based Temporal Attention Convolutional Neural Network with Exponential Nonlinearity Loss
WangMengxiao319/Shenda-Hong2019_MINA
MINA: Multilevel Knowledge-Guided Attention for Modeling Electrocardiography Signals, IJCAI 2019
WangMengxiao319/Snippet-Policy-Network-V2
The source code of SPN-V2
WangMengxiao319/VGG16-MLP_Anomaly-Detection-in-Time-Series-with-Triadic-Motif-Fields
Anomaly Detection in Time Series with Triadic Motif Fields and Application in Atrial Fibrillation ECG Classification