神经肌肉疾病精准健康研究支持数据集
包含香港神经肌肉疾病患者登记数据和机器学习模型,用于精准健康研究。

基本信息
资源简介
神经肌肉疾病精准健康研究支持数据集
【数据集背景】
本数据集源站标题为《Supporting dataset for Advancement of Precision Health for Neuromuscular Disorders using Effective Patient Registry and Machine Learning》。源站首次发布:2023-11-22。
【数据内容】
源站原始描述:This dataset serves as a supporting dataset for the PhD thesis entitled ''Advancement of Precision Health for Neuromuscular Disorders using Effective Patient Registry and Machine Learning.'' All studies have been endorsed by the Institutional Review Board (IRB). In the first stage of the study, we developed the novel Hong Kong Neuromuscular Disorders Patient Registry (HKNMDPR) and a machine learning algorithm. In the second stage of the study, we studied the (1) facial weakness prediction, (2) gen…
【数据结构与技术规格】
数据集 DOI:10.25442/hku.24597174.v1。
【主题与分类】
源站学科分类:Neurology and neuromuscular diseases。主题标签:Neuromuscular disorders。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://datahub.hku.hk/articles/dataset/Supporting_dataset_for_Advancement_of_Precision_Health_for_Neuromuscular_Disorders_using_Effective_Patient_Registry_and_Machine_Learning/24597174
使用许可:CC BY-NC 4.0(https://creativecommons.org/licenses/by-nc/4.0/)。
规范引用:Yu, Kwan Leung (2023). Supporting dataset for Advancement of Precision Health for Neuromuscular Disorders using Effective Patient Registry and Machine Learning. HKU DataHub. Dataset
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:Supporting dataset for Advancement of Precision Health for Neuromuscular Disorders using Effective Patient Registry and Machine Learning
- DOI:10.25442/hku.24597174.v1
- 发布日期:2023-11-22
- 源站页面:https://datahub.hku.hk/articles/dataset/Supporting_dataset_for_Advancement_of_Precision_Health_for_Neuromuscular_Disorders_using_Effective_Patient_Registry_and_Machine_Learning/24597174
按页面 Download 按钮获取。
数据加载示例(图像类)
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
数据说明
This dataset serves as a supporting dataset for the PhD thesis entitled ‘‘Advancement of Precision Health for Neuromuscular Disorders using Effective Patient Registry and Machine Learning.’’ All studies have been endorsed by the Institutional Review Board (IRB).
In the first stage of the study, we developed the novel Hong Kong Neuromuscular Disorders Patient Registry (HKNMDPR) and a machine learning algorithm. In the second stage of the study, we studied the (1) facial weakness prediction, (2) genotypic-phenotypic correlations, (3) personalized telerehabilitation, (4) treatment evaluation, (5) psychological impact of COVID-19 pandemic and (6) hesitancy, reactogenicity and immunogenicity of COVID-19 vaccines in NMDs.
许可
CC BY-NC 4.0
引用
学术使用请引用 DOI 10.25442/hku.24597174.v1(source: https://datahub.hku.hk/articles/dataset/Supporting_dataset_for_Advancement_of_Precision_Health_for_Neuromuscular_Disorders_using_Effective_Patient_Registry_and_Machine_Learning/24597174)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




