PHUSE SDE2024presentation·SDE·Single Day Event
An Initiative for Using R at Takeda Japan TOKYO07 APAC · Tokyo
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PHUSE SDE2024presentation·SDE·Single Day Event
Sharing the Survey Results of eData Submission for Real-World Data, and the Reduction of CSR Listings from the PHUSE Japan eData Submission Working Group TOKYO08 APAC · Tokyo
PHUSE SDE2024presentation·SDE·Single Day Event
Sharing Experiences of eData Submission to the PMDA Using Registry Data TOKYO09 APAC · Tokyo
PHUSE SDE2024presentation·SDE·Single Day Event
Synthetic Data Generation for Clinical Trial Control Groups and Target Trial Emulation TOKYO10 APAC · Tokyo
PHUSE SDE2024presentation·SDE·Single Day Event
The FDA’s Perspective on Buzzwords such as AI and ML in Drug Development UTRECHT01 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
Extracting Public Health Benefits from AI in the Medicine’s Lifecycle UTRECHT02 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
The Current State of Interpretable Machine Learning and its Usage in Clinical Research UTRECHT03 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
Clinical Trial-Specific LLM to Auto-Generate Protocols and SAPs UTRECHT04 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
Powering Medical Industry with AI: Automated Consistency Checks for Regulatory Documents with ML UTRECHT05 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
Appropriate Use of Blood Cultures in the Emergency Department Through Machine Learning: a Randomised Controlled Trial UTRECHT06 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
How Breakthroughs in AI Disrupt the Disrupters UTRECHT07 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
Limitations of Using ChatGPT in Writing Statistical Programs in SAS for Clinical Trials UTRECHT08 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
Traceability and AI for Improved Understanding, Communication and Quality Control of Clinical Trials UTRECHT09 EU · Utrecht
PHUSE SDE2024presentation·SDE·Single Day Event
Appropriate Use of Blood Cultures in the Emergency Department Through Machine Learning: a Randomised Controlled Trial UTRECHT10 EU · Utrecht
PharmaSUG2024paper·US·Advanced Programming
Macro Variable Arrays Made Easy with macroArray SAS package AP-108
PharmaSUG2024paper·US·Advanced Programming
LAST CALL to Get Tipsy with SAS®: Tips for Using CALL Subroutines AP-135
PharmaSUG2024paper·US·Advanced Programming
An Introduction to the SAS Transpose Procedure and its Options AP-138
PharmaSUG2024paper·US·Advanced Programming
SAS® Super Duo: The Program Data Vector and Data Step Debugger AP-144