相关数据集
Table_4_Machine learning algorithms assisted identification of post-stroke depression associated biological features.XLSX
ObjectivesPost-stroke depression (PSD) is a common and serious psychiatric complication which hinders functional recovery and social participation of stroke patients. Stroke is characterized by dynami
NIAID Data Ecosystem70
Supplementary Material for: Machine learning to improve accuracy of transcutaneous bilirubinometry
Introduction: This study aimed to develop models for predicting total serum bilirubin by correcting errors of transcutaneous bilirubin using machine learning based on neonatal biomarkers that could af
Figshare2024-04-10 更新30
This is the clinical validation dataset.
BackgroundCoronary Heart Disease (CHD) is one of the major burdens of cardiovascular diseases worldwide. Traditional diagnostic methods, such as coronary angiography and electrocardiogram, face challe
Figshare2025-09-12 更新10
Table_1_Assessment of fractional flow reserve in intermediate coronary stenosis using optical coherence tomography-based machine learning.DOCX
ObjectivesThis study aimed to evaluate and compare the diagnostic accuracy of machine learning (ML)- fractional flow reserve (FFR) based on optical coherence tomography (OCT) with wire-based FFR irres
NIAID Data Ecosystem50
DataSheet_1_Machine learning-featured Secretogranin V is a circulating diagnostic biomarker for pancreatic adenocarcinomas associated with adipopenia.docx
BackgroundPancreatic cancer is one of the most fatal malignancies of the gastrointestinal cancer, with a challenging early diagnosis due to lack of distinctive symptoms and specific biomarkers. The ex
NIAID Data Ecosystem20
