MINOCA表型：患者特异性管理的挑战
三个MINOCA病例研究，分析不同病因下的临床表现与治疗，支持患者特异性管理。
基本信息
资源简介
MINOCA表型：患者特异性管理的挑战
【一句话概览】
本数据集是 figshare 公开的文本数据集，收录 18 个文件、合计 22.62 MB，主题涵盖 Phenotype、MINOCA、Diagnosis Diferential、Dilatation Pathologic、Coronary Artery，可用于医学自然语言处理（实体识别、信息抽取等），CC BY 4.0 许可开放获取。
【数据集背景】
本数据集源站标题为《MINOCA Phenotypes – A Challenge for Patient-Specific Management》。源站首次发布：2023-06-20。
【数据内容】
源站原始描述：Abstract Myocardial infarction with non-obstructive coronary arteries (MINOCA) is a puzzling clinical phenomenon with an unclear prognosis, characterized by evidence of myocardial infarction (MI) with normal or near-normal coronary arteries on angiography1. Currently, there are no guidelines for management, and many patients are discharged without a determined etiology, often meaning that optimal treatment gets postponed.We report three MINOCA case studies with main pathophysiological cardiac ca…
【数据结构与技术规格】
文件数 18 个，合计 22.62 MB。数据集 DOI：10.6084/m9.figshare.23544410.v1。
【主题与分类】
源站学科分类：Cardiology。主题标签：Phenotype、MINOCA、Diagnosis Diferential、Dilatation Pathologic、Coronary Artery、Microvascular Spasm。
【适用方向】
文本类数据可用于医学自然语言处理，如命名实体识别、信息抽取与文本分类。
【获取与许可】
源站页面：https://scielo.figshare.com/articles/dataset/MINOCA_Phenotypes_A_Challenge_for_Patient-Specific_Management/23544410
使用许可：CC BY 4.0（https://creativecommons.org/licenses/by/4.0/）。
规范引用：Lypovetska, Sofiya (2023). MINOCA Phenotypes – A Challenge for Patient-Specific Management. SciELO journals. 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：MINOCA Phenotypes – A Challenge for Patient-Specific Management
- DOI：10.6084/m9.figshare.23544410.v1
- 发布日期：2023-06-20
- 文件数：18 个
- 文件总体积：22.62 MB
- 源站页面：https://scielo.figshare.com/articles/dataset/MINOCA_Phenotypes_A_Challenge_for_Patient-Specific_Management/23544410
命令行下载
curl -L -o "3914b0b26d46248be4c8342f4f8a358457bd795e.tif" "https://ndownloader.figshare.com/files/41300477"
curl -L -o "24226c4bb938252203ac8019f254d2068471067e.png" "https://ndownloader.figshare.com/files/41300480"
curl -L -o "e1967a59c9e1fafdaf200526c644892df5042fbc.jpg" "https://ndownloader.figshare.com/files/41300483"
curl -L -o "a118c345b346df7c6daf68005dd05dabe5222bfd.tif" "https://ndownloader.figshare.com/files/41300486"
curl -L -o "ebfb76583b8443c688079407ae29ccaaf389ab54.png" "https://ndownloader.figshare.com/files/41300489"
curl -L -o "b2d25ba73d2b0360f9bbfef650da2eb351cd4dcd.jpg" "https://ndownloader.figshare.com/files/41300492"
curl -L -o "30c49c70f94b323e3a3b613848279899fcf549ab.tif" "https://ndownloader.figshare.com/files/41300495"
curl -L -o "2dd26e4408d1f30d8fa8648e5c890f0f7ae48d5c.png" "https://ndownloader.figshare.com/files/41300498"
文件清单
3914b0b26d46248be4c8342f4f8a358457bd795e.tif（3.11 MB）24226c4bb938252203ac8019f254d2068471067e.png（733.79 KB）e1967a59c9e1fafdaf200526c644892df5042fbc.jpg（6.80 KB）a118c345b346df7c6daf68005dd05dabe5222bfd.tif（2.83 MB）ebfb76583b8443c688079407ae29ccaaf389ab54.png（1.20 MB）b2d25ba73d2b0360f9bbfef650da2eb351cd4dcd.jpg（6.39 KB）30c49c70f94b323e3a3b613848279899fcf549ab.tif（2.62 MB）2dd26e4408d1f30d8fa8648e5c890f0f7ae48d5c.png（793.52 KB）2192903b584bcdd58774aaf24eb8c1579f142d35.jpg（5.32 KB）7e5d11f9937d7bb2405ef48f43a2c8a49e55f7e4.tif（3.11 MB）24226c4bb938252203ac8019f254d2068471067e.png（733.79 KB）e1967a59c9e1fafdaf200526c644892df5042fbc.jpg（6.80 KB）7e8391c932b6d7e63449c5859c88a758644cda84.tif（2.83 MB）ebfb76583b8443c688079407ae29ccaaf389ab54.png（1.20 MB）b2d25ba73d2b0360f9bbfef650da2eb351cd4dcd.jpg（6.39 KB）a867b9805be52e06ad2211865e78c6a2290ac3cb.tif（2.62 MB）77ace735b2337b77bff6dce349c2b4f740badcad.png（794.13 KB）07aef7db47143f69edae7a7b126f633f1d439aa7.jpg（5.33 KB）
文件总体积 22.62 MB（源站 API 实测）。
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
Abstract Myocardial infarction with non-obstructive coronary arteries (MINOCA) is a puzzling clinical phenomenon with an unclear prognosis, characterized by evidence of myocardial infarction (MI) with normal or near-normal coronary arteries on angiography1. Currently, there are no guidelines for management, and many patients are discharged without a determined etiology, often meaning that optimal treatment gets postponed.We report three MINOCA case studies with main pathophysiological cardiac causes, particularly epicardial, microvascular, and non-ischemic, prompting differential management. The patients presented with acute chest pain, troponin raise, and no angiographically significant coronary disease.In this study, we analyzed the etiology, clinical diagnosis, and treatment of MINOCA concerning the relevant literature.MINOCA is considered to be a dynamic working diagnosis, including coronary, myocardial, and non-coronary disorders. Prospective studies and registries are needed to improve patient care and outcome.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.23544410.v1（source: https://scielo.figshare.com/articles/dataset/MINOCA_Phenotypes_A_Challenge_for_Patient-Specific_Management/23544410）。
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。
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