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125 papers and 1 presentation; 116 titles.

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Conference × Year × Title × Authors Extras Pages
PHUSE APAC 2026 BioBERT-Powered Event Classification - A Machine Learning Approach in Pyhton Gayathiri Premkumar source
poster source		 7
MWSUG 2024 Developing Artificial and Convolutional Neural Networks with Python's Keras API for TensorFlow Ryan Paul Lafler,
Anna T. K. Wade		 source 18
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 CN 2024 Application of Natural Language Processing with R in clinical trials Feifeng Zhou,
Zhenchao Chen		 source 11
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 Revolutionising Informed Consent Form Analysis with Generative AI: Enhancing Efficiency in Drug Development and Data Re-Use Hangyu (Cedric) Liu source
presentation source		 11
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 Deep Learning to Classify Adverse Events from Patient Narratives Tom Sabo,
Sundaresh Sankaran,
Qais Hatim		 source 11
SGF 2021 Developing a SAS Deep Learning MedDRA encoder (MedDRA-DeepCoder) for Patient Narratives Qais Hatim source 11
PHUSE EU 2020 AI-assisted Medical Coding [presentation] Christian S. Christensen,
Thomas Ellebaek		 source
video		 20
SGF 2020 Exploring Online Drug Reviews using Text Analytics, Sentiment Analysis, and Data Mining Models Thu Dinh,
Goutam Chakraborty		 source 23
SGF 2020 How to Build a Text Analytics Model in SAS Viya with Python Nate Gilmore source 13
SGF 2020 Medical Image Analyses in SAS Viya with Applications in Automatic Tissue Morphometry in the Clinic Courtney Ambrozic source 13
SGF 2020 Using Analytics to Predict Tax Recovery and Prioritize Audits and Investigations in Canada Jason A. Oliver source 19
SGF 2020 Using Python with Model Studio for SAS Visual Data Mining and Machine Learning Jagruti Kanjia source 35
PharmaSUG 2020 Detecting Side Effects and Evaluating the Effectiveness of Drugs from Customers' Online Reviews using Text Analytics, Sentiment Analysis and Machine Learning Models Thu Dinh,
Goutam Chakraborty		 source 22
SESUG 2019 Hybrid Rare Event Sampling Technique Ross Bettinger source 15
SESUG 2019 Improving Employee Satisfaction Through Text Analytics Luis David Martinez source 15
SCSUG 2019 Building a Neural Network Scoring Model with JMP and Microsoft SQL Server to predict Aggregate Motor Vehicle Driver Alcohol Impairment David Whitchurch source 10
MWSUG 2019 Deploying SAS Viya Docker images to the cloud - a step by step guide Alan Zablocki 25
MWSUG 2019 Detecting Side Effects and Evaluating Effectiveness of Drugs from Customers' Online Reviews using Text Analytics and Data Mining Models Thu Dinh 23
MWSUG 2019 Logistic Regression, Basics and Beyond Bruce S. Lund 35
PharmaSUG 2019 Hands-on Training for Machine Learning Programming Kevin Lee source 12
PHUSE US 2019 Quantifying Dynamic Risk with Predictive Analytics Susan Olson,
Connor English		 source
presentation source		 7
SCSUG 2018 Machine Learning in Litigation Prediction - Workers' Compensation Litigation Propensity Predictive Model Mei Najim source 17
PHUSE US 2018 Modeling and Text Analysis to Empower FAERS Adverse Event Mitigation Qais Hatim,
Emily McRae		 source
presentation source		 24
SGF 2018 A Cautionary Tale of Using Machine Learning within Credit Risk in the Utilities Industry Spiros Potamitis,
Paul Malley		 source 8
SGF 2018 Claim Analytics: A Litigation Prediction Case Study Mei Najim source 18
SGF 2018 Claim Risk Scoring Using Survival Analysis Framework and Machine Learning with Random Forest Yuriy Chechulin source 15
SGF 2018 How Good is That Forecast? The Nuances of Prediction Evaluation Across Time Aric LaBarr source 7
SGF 2018 Mitigating the Effects of Class Imbalance Using SMOTE and Tomek Link Undersampling in SAS Kyle Biron source 20
SGF 2018 New Ways to Incorporate Continuous Predictors in Generalized Linear Models Anthony Salis,
Angela Wu,
Gordon Johnston		 source 15
SGF 2018 Robust Principal Component Analysis: Two Analyses in One Anthony Salis,
Zohreh Asgharzadeh,
Kyungduck Cha		 source 11
SGF 2018 Shorter Waiting Time, Better Emergency Healthcare: Forecasting Stockholms' Emergency Room Visits Martin Nordberg,
Oskar Eriksson		 source 24
SESUG 2017 Exploring JMP Modeling Functionality Using Consumer Expenditure Data Joshua Klick source 12
SESUG 2017 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 25
MWSUG 2017 Claim Analytics Mei Najim 18
MWSUG 2017 Logistic Model Selection with SAS PROC's LOGISTIC, HPLOGISTIC, HPGENSELECT Bruce S. Lund 18
SGF 2017 Developing a Predictive Model of Physician Attribution of Patient Satisfaction Surveys Ken Ferrell source 5
SGF 2017 Geospatial Analysis: Linear, Nonlinear, or Both? Kelsey Osterloo,
Angela Wu		 source 14
SGF 2017 Predictive Models: Storing, Scoring, and Evaluating Matthew Duchnowski source 10
SGF 2017 Property and Casualty Insurance Predictive Analytics in SAS Mei Najim source 17
SGF 2017 Random Forests with Approximate Bayesian Model Averaging Tiny Du Toit,
Andre De Waal		 source 11
SGF 2017 Real AdaBoost: Boosting for Credit Scorecards and Similarity to WOE Logistic Regression Paul Edwards source 12
SGF 2017 The Three Amigos Factors: Determining Term Deposit Purchases: How a Bank Can Get Other People's Money Gina Colaianni,
Bogdan Gadidov,
Matthew Mitchell		 source 59
SESUG 2016 Know your Interest Rate Anirban Chakraborty,
Goutam Chakraborty		 source 16
MWSUG 2016 Property and Casualty Insurance Predictive Analytics in SAS Mei Najim 17
SGF 2016 A Property and Casualty Insurance Predictive Modeling Process in SAS Mei Najim source 14
SGF 2016 Analysis of IMDb Reviews for Movies and Television Series Using SAS Enterprise Miner and SAS Sentiment Analysis Studio Ameya Jadhavar,
Goutam Chakraborty,
Prithvi Raj Sirolikar		 source 17
SGF 2016 Application of Data Mining Techniques in Improving Breast Cancer Diagnosis Josephine Akosa source
presentation		 10
SGF 2016 Application of Gradient Boosting through SAS Enterprise Miner to Classify Human Activities Minh Pham,
Mary Ruppert-Stroescu,
Mostakim Tanjil		 source
presentation		 8
SGF 2016 Classifying Fatal Automobile Accidents in the US, 2010-2013: Using SAS Enterprise Miner to Understand and Reduce Fatalities Catherine LaChapelle,
Daniel Brannock,
Aric LaBarr,
Craig Shaver		 source 11
SGF 2016 Diagnosing Obstructive Sleep Apnea: Using Predictive Analytics Based on Wavelet Analysis in SAS/IML Software and Spectral Analysis in PROC SPECTRA Woranat Wongdhamma source 12
SGF 2016 Ensemble Modeling: Recent Advances and Applications Wendy Czika,
Ye Liu		 source 20
SGF 2016 Finding and Evaluating Multiple Candidate Models for Logistic Regression Bruce S. Lund source
zip		 17
SGF 2016 Missing Values: They Are NOT Nothing Justin Jia,
Shan Shan Lin		 source 19
SGF 2016 Predicting Forest Fire Occurrence and Incremental Fire Rate Using SAS 9.4 and SAS Enterprise Miner 14.1 Quyen Nguyen source 12
SGF 2016 Predicting Human Activity Sensor Data Using an Auto Neural Model with Stepwise Logistic Regression Inputs Venkata Vennelakanti source
presentation		 10
MWSUG 2015 A Property & Casualty Insurance Predictive Modeling Process in SAS Mei Najim 14
MWSUG 2015 Fitting and Evaluating Logistic Regression Models Bruce S. Lund 26
MWSUG 2015 Get the highest bangs for your marketing bucks using Incremental Response Models in SAS Enterprise Miner Delali Agbenyegah 8
SGF 2015 Analyzing Direct Marketing Campaign Performance Using Weight of Evidence Coding and Information Value through SAS Enterprise Miner Incremental Response Sravan Vadigepalli source
zip		 9
SGF 2015 SAS Analytics plus Warren Buffett's Wisdom Beats Berkshire Hathaway! Huh? Bruce Bedford source 20
SGF 2015 When Two Are Better Than One: Fitting Two-Part Models Using SAS Laura Kapitula source 9
MWSUG 2014 Analyzing Collection Effectiveness using Incremental Response Modeling Ryan Burton 7
WUSS 2014 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 8
SGF 2014 An Overview of Machine Learning with SAS Enterprise Miner Patrick Hall,
Jared Dean,
Ilknur Kaynar Kabul,
Jorge Silva		 source
zip		 24
SGF 2014 Building Gamer Segmentation in the Credit Card Industry Using SAS Enterprise Guide Yang Ge source 10
WUSS 2013 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 8
SESUG 2013 Evaluating the Accuracy Assessment Methods of a Thematic Raster through SAS Resampling Techniques and GTL Visualizations Robert Seffrin source 7
SESUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SESUG 2013 What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs Satish Garla source 15
MWSUG 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey 16
NESUG 2013 An Animated Guide: An Introduction to Neural Nets: Russell M. Lavery 12
SGF 2013 Finding the Gold in Your Data: An Overview of Data Mining David A. Dickey source 16
SGF 2013 Predictive Modeling in Sports Leagues: An Application in the Indian Premier League Goutam Chakraborty,
Pankush Kalgotra,
Ramesh Sharda		 source 10
SGF 2013 What Do Your Consumer Habits Say About Your Health? Using Third-Party Data to Predict Individual Health Risk and Costs Albert Hopping,
Rick Monaco,
Sarah Rittman,
Satish Garla		 source 15
NESUG 2012 An Animated Guide: Regression Trees in JMP and Enterprise Miner Russell M. Lavery 32
SESUG 2012 An Introduction to the Clinical Standards Toolkit Mike Molter source 13
PharmaSUG 2012 An Introduction to the Clinical Standards Toolkit and Clinical Data Compliance Checking Mike Molter source 14
SGF 2012 An Experimental Comparison of Classification Techniques for Imbalanced Credit Scoring Data Sets Using SAS Enterprise Miner Iain L. Brown source 14
SGF 2012 Classification of Customers Textual Responses via Application of Topic Mining Anil K. Pantangi,
Goutam Chakraborty		 source 6
SGF 2012 Its About Time: Discrete Time Survival Analysis using SAS Enterprise Miner Sascha Schubert,
Susan Haller,
Taiyeong Lee		 source 15
SCSUG 2011 Prediction on Diabetes Using Data Mining Approach Pardha Repalli source 10
MWSUG 2011 Automated or Manual Validation: Which One is for You? Richann J. Watson,
Patty Johnson		 5
MWSUG 2011 Using SAS to Find the Best K for K-Nearest-Neighbor Classification Charlie Huang 14
PharmaSUG 2011 Automated or Manual Validation: Which One is for You? Richann J. Watson,
Patty Johnson		 source 5
SGF 2011 Improving Customer Loyalty Program through Text Mining of Customers Comments Maheshwar R. Nareddy,
Goutam Chakraborty		 source 8
WUSS 2010 Decision Trees as a Predictive Modeling Method Gerry Hobbs source 7
SESUG 2010 Analysis and Visual Review of Error Matrices in SAS Stat Studio Robert Seffrin source 10
PharmaSUG 2010 Validate it Again?! Get SAS to do it! Carol Matthews,
Ginger Lewis,
Olga Belotserkovsky		 13
SGF 2010 Rapid Predictive Modeling for Customer Intelligence Wayne Thompson,
David R. Duling		 source 12
SGF 2010 The Power of the Group Processing Facility in SAS Enterprise Miner Sascha Schubert source 13
SGF 2010 Using the SAS System and SAS Enterprise Miner for Data Mining: A Study of Cancer Survival at the Mayo Clinic Leonard Gordon source 6
PHUSE EU 2009 Validate it Again?! Get SAS to do it! Carol Matthews,
Ginger Lewis		 source 14
WUSS 2009 Discriminant Analysis, a Powerful Classification Technique in Predictive Modeling George C. J. Fernandez source 20
SGF 2009 Generalizations of Generalized Additive Model (GAM): A Case of Credit Risk Modeling Wensui Liu,
Jimmy Cela,
Chuck Vu		 source 14
MWSUG 2008 Classification of Breast Cancer Cells Using JMP Marie Gaudard 34
MWSUG 2008 Global Clinical Data Classification: A Discriminate Analysis Amurthur Ramamurthy,
Gordon Kapke,
Jodi Yoder		 16
SGF 2008 Employing SAS Text Miner Methodology to Become a Customer Genius in Customer Churn Prediction and Complaint E-mail Management Kristof Coussement source 12
SGF 2008 In Search for a Golden Algorithm Tamara S. Slipchenko,
Candice Bowman,
Catherine Sugar,
Allen L. Gifford		 source 9
SGF 2008 Understanding Your Customer: Segmentation Techniques for Gaining Customer Insight and Predicting Risk in the Telecom Industry Glendon Cross,
Wayne Thompson		 source 14
NESUG 2007 Using PROC PLS (Partial Least Squares) to Build a Gene Prognosis Profile Chenwei Liu 5
MWSUG 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga 20
WUSS 2007 Case Study: Development of an HIV casefinding algorithm with SAS Enterprise Miner Tamara Slipchenko,
Candice Bowman,
Yuexin (Cindy) Chen,
Catherine Sugar,
Allen L. Gifford		 source 9
WUSS 2007 Data Mining Using SAS Enterprise Miner Randall Matignon source 10
SGF 2007 Identifying and Overcoming Common Data Mining Mistakes Doug Wielenga source 20
SUGI 2006 Investigating Open Source Project Success - A Data Mining Approach to Model Formulation, Testing and Validation Uzma Raja,
Marietta J. Tretter		 source 7
WUSS 2005 A Comparison of Missing Data Handling Methods Catherine Truxillo source 20
SUGI 2005 A Proportional Hazards Approach to Campaign List Selection Charles Manahan source 7
SUGI 2005 Decision Tree Validation: A Comprehensive Approach Sylvain Tremblay source 8
SUGI 2005 Maximum Likelihood Parameter Estimation with Incomplete Data Catherine Truxillo source 19
SUGI 2003 Modeling Customer Lifetime Value Using Survival Analysis - An Application in the Telecommunications Industry Junxiang Lu source 6
WUSS 2002 Multiple Linear Regression Analysis of Total Mercury Levels in Blood and Urine Samples Miki Yamauchi,
George C. J. Fernandez,
Stanley Omaye		 source 6
SUGI 2002 Discriminant Analysis, A Powerful Classification Technique in Data Mining George C. J. Fernandez source 9
SUGI 2002 Predicting Customer Churn in the Telecommunications Industry - An Application of Survival Analysis Modeling Using SAS Junxiang Lu source 6
SUGI 2002 Using SAS Enterprise Miner for Data Quality Monitoring in the Veterans Health Administration's External Peer Review Program James H. Forsythe source 5
WUSS 2001 Discriminant Analysis, A Powerful Classification Technique in Data Mining George C. J. Fernandez source 9
PharmaSUG 2001 VALIDATION: Let SAS do the comparisons for you Lara E.H. Guttadauro 6
SUGI 1998 Finding the Solution to Data Mining: A Map of the Features and Components of SAS Enterprise Miner Software Table of Contents John C. Brocklebank,
Mark Brown		 source 24
SUGI 1998 Mining the Data Mart: A Case Study with Stock Market Data James A. Cox,
Tonya L. Etchison		 source 11
PharmaSUG 1997 Integrating SAS Programs with a Multi-Functional Computer Assisted NDA (Canda) Kathryn B. Eisen 4
SUGI 1996 New Age Marketing: Past Life Regression vs. LogisticRegression C. Olivia Parr Rud source 5
SESUG 1995 New Age Marketing: Past Life Regression versus Logistic Regression C. Olivia Parr Rud 9
SUGI 1995 Double Data Entry for Novice Users Terry Shaffer,
N. Paige Groninger		 source 6

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