cloud-based biomedical data ingestion, transformation, and deidentification platform (GenoSpace)
90
Structured Review
GenoSpace
cloud-based biomedical data ingestion, transformation, and deidentification platform
Cloud Based Biomedical Data Ingestion, Transformation, And Deidentification Platform, supplied by GenoSpace, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/cloud-based+biomedical+data+ingestion%2C+transformation%2C+and+deidentification+platform/cloud+based+biomedical+data+ingestion++transformation++and+deidentification+platform/pm37057912-51-18-10
Average 90 stars, based on 1 article reviews
Cloud Based Biomedical Data Ingestion, Transformation, And Deidentification Platform, supplied by GenoSpace, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/cloud-based+biomedical+data+ingestion%2C+transformation%2C+and+deidentification+platform/cloud+based+biomedical+data+ingestion++transformation++and+deidentification+platform/pm37057912-51-18-10
Average 90 stars, based on 1 article reviews
cloud-based biomedical data ingestion, transformation, and deidentification platform - by Bioz Stars,
2026-10
90/100 stars
Images
Related Articles
Transformation Assay:Article Title: Performance of point-of-care severity scores to predict prognosis in patients admitted through the emergency department with COVID-19. Article Snippet: Funding information Agency for Healthcare Research and Quality, Grant/Award Number: R01HS027369; Gordon and Betty Moore Foundation, Grant/Award Number: 8856; National Heart, Lung, and Blood Institute, Grant/Award Number: K24HL141354 Abstract Background: Identifying COVID‐19 patients at the highest risk of poor outcomes is critical in emergency department (ED) presentation.. Sepsis risk stratification scores can be calculated quickly for COVID‐19 patients but have not been evaluated in a large cohort.. Objective: To determine whether well‐known risk scores can predict poor outcomes among hospitalized COVID‐19 patients. |