| WUSS |
2026 |
Enhancing Your SAS Viya Workflows with Python: Integrating Python's Open-Source Libraries with SAS using PROC PYTHON |
Ryan Paul Lafler,
Miguel Bravo Martinez del Valle |
source |
12 |
| PharmaSUG |
2026 |
Enhancing Your SAS Viya Workflows with Python: Integrating Python's Open-Source Libraries with SAS using PROC PYTHON |
Ryan Paul Lafler,
Miguel Bravo Martinez del Valle |
source |
13 |
| PHUSE US |
2026 |
Where are my Agents? Automating Cohort Building with a Dynamic Cohort Builder |
Mary Dolegowski,
Sherrine Eid |
source
presentation source |
12 |
| PHUSE APAC |
2026 |
Real- World Safety Evaluation through Electronic Medical Record: A Transformative Approach to Korean Post-Marketing Surveillance |
Ha-Yeong Gil,
Yeo Rae Moon,
YongHyun Cho,
Seung-Hee Jeong |
source
poster source |
3 |
| PHUSE US |
2025 |
Accelerating Patient Safety with Knowledge Graphs: Lessons from a Successful Implementation |
Partha Bhattacharjee,
Kirti Aggarwal |
source
presentation source |
10 |
| PHUSE US |
2025 |
From Application to Approval: Exploring the FDA's Review Process |
Kiran Bonda |
source
presentation source |
4 |
| PHUSE US |
2025 |
Leveraging Vector Databases to Enhance AI Applications in Pharmaceutical Research |
Angu Sundaresh Krishna Kumar,
Ramanathan Srinivasan |
source
presentation source |
11 |
| MWSUG |
2024 |
Developing Artificial and Convolutional Neural Networks with Python's Keras API for TensorFlow |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
18 |
| PHUSE EU |
2024 |
Revolutionising Statistical Programming Activities - StatProg CoPilot Consortium Leveraging on Open-Source World and Generative AI |
Sébastien Tourlet |
source
presentation source |
4 |
| PHUSE EU |
2024 |
Unlocking the Potential of Unstructured Data in Real-World Evidence: Leveraging Text for Enhanced Patient Classification and Regulatory Validation |
Georgios Panagiotakis,
Maria Puri |
source
poster source |
10 |
| SESUG |
2024 |
Developing Artificial and Convolutional Neural Networks with Python's Keras API for TensorFlow |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
18 |
| WUSS |
2024 |
Developing Artificial and Convolutional Neural Networks with Python's Keras API for TensorFlow |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
18 |
| PharmaSUG |
2024 |
Unraveling the Layers within Neural Networks: Designing Artificial and Convolutional Neural Networks for Classification and Regression Using Python-s Keras & TensorFlow |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
18 |
| PHUSE US |
2024 |
Data Quality Evaluation of EHR FHIR API Real-World Data for FDA and Pharmaceutical Industry Use for Analysis and AI Implementation |
Sarah Ferko,
Abhishek Pandey,
Matthew Deady,
Brian Goodness |
source
presentation source |
10 |
| PHUSE US |
2024 |
Enabling the Breakthroughs of Tomorrow: The Data Lakehouse for Clinical Trials |
Venu Mallarapu |
source
presentation source |
12 |
| PHUSE US |
2024 |
Harness the Data's Potential in a Clinical Trial Process |
Eva Kelty,
Catharina Dahlbo |
source
poster source |
4 |
| PHUSE US |
2024 |
The Role of AI (ML/NLP/Deep Learning) in Handling Sensitive/Confidential Data |
Divya Kanniah,
Swetha Balaji |
source
presentation source |
3 |
| WUSS |
2023 |
Unraveling the Layers within Neural Networks: Designing Artificial and Convolutional Neural Networks for Classification and Regression Tasks using TensorFlow in Python |
Ryan Paul Lafler,
Anna T. K. Wade |
source |
24 |
| PharmaSUG |
2023 |
Bringing it All Together: Applying the Analytics Life Cycle for Natural Language Processing to Life Sciences |
Sundaresh Sankaran,
Tom Sabo |
source |
15 |
| PHUSE US |
2023 |
The Role of AI in Handling Clinical Data and Documents (Structured and Unstructured) |
Farha Feroze |
source
presentation source |
6 |
| PHUSE US |
2022 |
Implementation of Real-world Structured/ Unstructured Clinical Data in Real-world Evidence Trials (RWEs) for Regulatory Submissions [presentation] |
Ravi Mokkarala,
Yan Shen |
source |
12 |
| PHUSE US |
2022 |
Practical Challenges in Handling Unstructured Data Using Artificial Intelligence [presentation] |
Farha Feroze |
source
video |
11 |
| PHUSE EU |
2021 |
Incorporating Novel Real-world Evidence Across the Drug Development Continuum: Leveraging the Value of Digital Social Media [presentation] |
Nardin Farid,
Stephen Doogan |
source
video |
24 |
| PHUSE EU |
2021 |
Software Demonstration: Unlocking Value from Structured Clinical Trial Data - Sponsored by Privacy Analytics [presentation] |
Thomasin Element |
source |
18 |
| PHUSE US |
2021 |
Industry Metrics for Extensions of CDISC Terminology [presentation] |
Sergiy Sirichenko |
source
video |
36 |
| PHUSE US |
2021 |
Software Demonstration: SD11: Streamline Your Quantitative Anonymization Process and Deliver Consistent Outputs for Every Disclosure Scenario [presentation] |
Stephen Doogan |
source |
8 |
| SGF |
2020 |
SAS on an Amazon Web Services Data Lake: Enabling Access to Data Lakes on SAS |
Dilip Rajan |
source |
11 |
| SGF |
2020 |
Sound Insights: A Pipeline for Information Extraction from Audio Files |
Biljana Belamaric Wilsey,
Xiaozhuo Cheng |
source |
8 |
| PHUSE US |
2020 |
A Comparison of Machine Learning Algorithms for Binary Classification of Free-text Fields Using SAS, R, and Python |
Michael S Rimler |
source
presentation source |
12 |
| PHUSE US |
2020 |
A Visualization approach for Clinical Trials with Digital Data |
Siddharth Kumar Lokineni |
source
presentation source |
6 |
| PharmaSUG |
2019 |
Artificial Intelligence and Real World Evidence - it takes two to tango |
Charan Kumar Kuyyamudira Janardhana |
source |
9 |
| PHUSE US |
2019 |
R and Python Differences, Techniques and Challenges for SAS Programmers |
Murali Neela |
source
presentation source |
20 |
| PHUSE US |
2018 |
Drug-Induced Liver Injury (DILI) Classification Using FDA-Approved Drug Labeling and FAERS Data - FDA |
Qais Hatim |
source
presentation source |
31 |
| PHUSE US |
2018 |
Modeling and Text Analysis to Empower FAERS Adverse Event Mitigation |
Qais Hatim,
Emily McRae |
source
presentation source |
24 |
| SGF |
2018 |
Harvesting Unstructured Data to Reduce Anti-Money Laundering (AML) Compliance Risk |
Austin Cook,
Beth Herron |
source |
10 |
| SGF |
2018 |
SAS Visual Analytics: Text Analytics Using Word Clouds |
Jenine Milum |
source |
9 |
| SGF |
2018 |
SAS Visual Forecasting: A Cloud-Based Time Series Analysis and Forecasting System |
Jerzy M. Brzezicki,
Joseph H. Katz |
source |
21 |
| PharmaSUG |
2017 |
A Practical Guide to Healthcare Data: Tips, Traps, and Techniques |
Gregory S. Barnes Nelson |
source |
20 |
| SGF |
2017 |
A Practical Guide to Healthcare Data: Tips, Traps, and Techniques |
Gregory S. Barnes Nelson |
source |
20 |
| SGF |
2017 |
Production Forecasting in the Age of Big Data in the Oil and Gas Industry [presentation] |
Vipin Prakash Gupta,
Satyajit Dwivedi |
source |
17 |
| SCSUG |
2016 |
SAS Enterprise Guide for LASR Server |
Piyush K. Singh,
Prasoon Sangwan |
source |
11 |
| SCSUG |
2016 |
Show Me the Money! Text Analytics for Decision-Making in Government Spending |
Tom Sabo |
source |
13 |
| WUSS |
2016 |
SAS integration with NoSQL database |
Kevin Lee |
source |
9 |
| PharmaSUG |
2016 |
SAS integration with NoSQL data |
Kevin Lee |
source |
9 |
| SGF |
2016 |
Lenovo Success Story: Early Detection of Pervasive Quality Issues through the Voice of Customer Analytics |
Murali Krishna Pagolu,
Rob Carscadden |
source |
16 |
| SGF |
2016 |
Pedal-to-the-Metal Analytics with SAS Studio, SAS Visual Analytics, and SAS Visual Statistics |
Manuel Figallo-Monge |
source |
20 |
| SGF |
2015 |
Analyzing Marine Piracy from Structured and Unstructured Data Using SAS Text Miner |
Raghavender Reddy Byreddy,
Nitish Byri,
Goutam Chakraborty,
Tejeshwar Gurram,
Anvesh Reddy Minukuri |
source |
12 |
| SGF |
2015 |
Donor Sentiment and Characteristic Analysis Using SAS Enterprise Miner and SAS Sentiment Analysis Studio |
Ramcharan Kakarla,
Goutam Chakraborty |
source |
12 |
| SGF |
2015 |
Show Me the Money! Text Analytics for Decision-Making in Government Spending |
Tom Sabo |
source |
13 |
| SGF |
2015 |
Social Media and Open Data Integration through SAS Visual Analytics and SAS Text Analytics for Public Health Surveillance |
Manuel Figallo-Monge,
Emily McRae |
source |
19 |
| SGF |
2015 |
Unstructured Data Mining to Improve Customer Experience in Interactive Voice Response Systems |
Dmitriy Khots |
source |
11 |
| SGF |
2014 |
Analysis of Unstructured Data: Applications of Text Analytics and Sentiment Mining |
Goutam Chakraborty,
Murali Krishna Pagolu |
source |
14 |
| SGF |
2014 |
Star Wars and the Art of Data Science: An Analytical Approach to Understanding Large Amounts of Unstructured Data |
Adam Maness,
Mary Osborne |
source |
28 |
| SGF |
2014 |
Text Mining Economic Topic Sentiment for Time Series Modeling |
Michael P. Dessauer,
Justin Kauhl |
source |
14 |
| SGF |
2014 |
What Benefits Can a Hospital Achieve by an Automated Structured Search in Medical Records for Mapping of Patient Injuries? |
Tonje Hansen |
source |
4 |
| WUSS |
2013 |
Uncovering Patterns in Textual Data with SAS Visual Analytics and SAS Text Analytics |
Daniel Zaratsian |
source |
11 |
| SCSUG |
2013 |
Uncovering Patterns in Textual Data for SAS Visual Analytics and SAS Text Analytics |
Meera Venkataramani |
source |
11 |
| SESUG |
2013 |
Uncovering Patterns in Textual Data with SAS Visual Analytics and SAS Text Analytics |
Daniel Zaratsian,
Mary Osborne,
Justin Plumley |
source |
11 |
| MWSUG |
2013 |
Uncovering Patterns in Textual Data for SAS Visual Analytics and SAS Text Analytics |
Daniel Zaratsian,
Mary Osborne,
Justin Plumley |
|
11 |
| NESUG |
2013 |
Uncovering Patterns in Textual Data for SAS Visual Analytics and SAS Text Analytics |
Meera Venkataramani |
|
11 |
| SGF |
2013 |
Deciphering Emoticons for Text Analytics: A Macro-Based Approach |
Chad Atkinson |
source |
15 |
| SGF |
2013 |
Replacing Manual Coding of Customer Survey Comments with Text Mining: A Story of Discovery with Textual Data in the Public Sector |
Jared Prins |
source |
19 |
| SGF |
2013 |
Uncovering Patterns in Textual Data with SAS Visual Analytics and SAS Text Analytics |
Daniel Zaratsian,
Justin Plumley,
Mary Osborne |
source |
11 |
| SGF |
2013 |
Unleashing the Power of Unified Text Analytics to Categorize Call Center Data |
Arila Barnes,
Jared Peterson,
Saratendu Sethi |
source |
12 |
| NESUG |
2012 |
Becoming the Smartest Guys in the Room: An Analysis of the Enron Emails Using an Integration of Text Analytics and Case Management |
John York |
|
8 |
| SGF |
2012 |
Becoming the Smartest Guys in the Room: An Analysis of the Enron Emails Using an Integration of Text Analytics and Case Management |
John York,
Doris Wong,
Daniel Zaratsian |
source |
8 |
| SGF |
2012 |
Classification of Customers Textual Responses via Application of Topic Mining |
Anil K. Pantangi,
Goutam Chakraborty |
source |
6 |
| SGF |
2012 |
Correlating the Analysis of Opinionated Texts Using SAS Text Analytics with Application of Sabermetrics to Cricket Statistics |
Praveen Lakkaraju,
Saratendu Sethi |
source |
10 |
| SGF |
2011 |
Creating Word Clouds in SAS: A DSGI Approach |
Murphy Choy |
source |
8 |
| SGF |
2011 |
So, That's What's in There? Customer Service through Unstructured Data |
Bruce Bedford,
Ben Zenick |
source |
11 |
| SGF |
2009 |
Data Integration in a Grid-Enabled Environment |
Cheryl Doninger,
Nancy A. Rausch |
source |
11 |
| SGF |
2008 |
Data Integration in a Grid-Enabled Environment |
Cheryl Doninger,
Gary Mehler,
Nancy A. Rausch |
source |
11 |
| SEUGI |
2003 |
The SAS Academic Intiative Featuring the Student Ambassadors: Building the future for our SAS Customers - Wrap Up [presentation] |
Nina Hanke |
source |
10 |
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