| PharmaSUG |
2025 |
Addressing Challenges in Real-World Evidence Generation: The AI-SAS for Real-World Evidence Approach |
Takuji Komeda, Yuki Yoshida, Yohei Komatsu |
source |
7 |
| SAS Innovate |
2025 |
Overcoming Challenges in RWE Generation: The AI-SAS for RWE Approach [video] |
Yuki Yoshida, Takuji Komeda |
source video |
|
| PharmaSUG |
2021 |
Why Data Scientists need leadership skills? Story of Cross-Value Chain Data Utilization Project |
Yura Suzuki, Yuichi Koretaka, Ryo Kiguchi |
source |
8 |
| SGF |
2021 |
The Potential of Simulation Technologies: Multi-Agent Simulation and Reinforcement Learning |
Satoki Fujita, Shogo Miyazawa, Ryo Kiguchi, Yuki Yoshida, Katsunari Hirano |
source presentation |
14 |
| PharmaSUG |
2020 |
Challenges and solutions for e-data submission to PMDA even after submission to FDA |
Akari Kamitani, HyeonJeong An, Yura Suzuki, Malla Reddy Boda |
source |
14 |
| PharmaSUG |
2019 |
Process optimization for efficient and smooth e-data submissions to both FDA and PMDA |
Eri Sakai, Malla Reddy Boda, Akari Kamitani |
source |
13 |
| PharmaSUG |
2019 |
SHIONOGI Global SAS System Renewal Project - How to Improve Statistical Programming Platform |
Yura Suzuki, Yoshimi Ishida, Malla Reddy Boda |
source |
10 |
| SGF |
2019 |
Make SAS Viya Realize Strategic Data Science - Data Governance, AI Platform and AI SAS Programmer |
Ryo Kiguchi, Katsunari Hirano |
source |
8 |
| SGF |
2017 |
N-Stage Machine Learning Analysis with the LUA Procedure Helps Solve Big Data Analysis Problems |
Ryo Kiguchi, Eri Sakai, Akio Tsuji |
source |
8 |
| SGF |
2016 |
PROC IMSTAT Boosts Knowledge Discovery in Big-Database (KDBD) in a Pharmaceutical Company |
Ryo Kiguchi, Akio Tsuji, Hideaki Watanabe |
source |
7 |
| PharmaSUG |
2014 |
Automatic Access Control via SAS: More Efficient and Smart |
Yuichi Koretaka, Masakazu Fujiwara, Yuki Yoshida |
source |
10 |