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Activity Details

132 Mon, 8/9/2021, 1:30 PM - 3:20 PM Virtual
SLDS CSpeed 1 — Contributed Speed
Section on Statistical Learning and Data Science, Text Analysis Interest Group
Chair(s): Jaime Lynn Speiser, Wake Forest School of Medicine
1:35 PM Applications of Machine Learning Methods to Identify Pediatric Patients with De Novo Acute Myeloid Leukemia from a Real-World Data Set
Yimei Li, University of Pennsylvania
1:40 PM Estimation of a Distribution Function with Increasing Failure Rate Average
Ganesh B. Malla, University of Cincinnati-Clermont College
1:45 PM A Semiparametric Complementary Log-Log Model with Applications in Rare Event Mining
Cheng Peng, West Chester University of Pennsylvania; Kai Peng, Ningbo University of Technology
1:50 PM A Deep Convolutional Neural Network Approach for Predicting Cumulative Incidence Based on Pseudo-Observations
Pablo Gonzalez Gonzalez Ginestet, Karolinska Institutet; Philippe Weitz, Karolinska Institutet; Erin Gabriel, Karolinska Institutet; Mattias Rantalainen, Karolinska Institutet
1:55 PM Subgroup Identification of Elderly Bladder Cancer Patients Based on Mental and Physical Scores: A Clustering Approach
Mojgan Golzy, University of Missouri-Columbia; Katie Murray, University of Missouri-Columbia
2:00 PM Impact of Tweets Pre-Processing Techniques on a Dictionary for Environment
Camilla Salvatore, University of Bergamo; Daniele Toninelli, University of Bergamo; Michela Cameletti, University of Bergamo; Stephan Schlosser, Georg-August-Universität Göttingen
2:05 PM Can Machine Learning Improve Correspondence Audit Case Selection? Considerations for Algorithm Selection, Validation, and Experimentation
Lucia Lykke, The MITRE Corporation; Ben Howard, The MITRE Corporation; David Pinski, The MITRE Corporation; Alan Plumley, Internal Revenue Services
2:10 PM Applying Machine Learning Methods for Insight into Textile Recycling Behavior
Brandon King, North Carolina State University; Lori Rothenberg, North Carolina State University; Jeffrey Joines, North Carolina State University
2:15 PM Empirical Comparison of Multiplicative and Tree-Based Interaction Predictive Models
Chinedu Jude Nzekwe, North Carolina A&T State University; Sayed Mostafa, North Carolina A&T State University; Seong-Tae Kim, North Carolina A&T State University
2:20 PM On Kernel-Target Alignment and Relevant Dimensions in Kernel Feature Spaces Ensuing from the Decision and Regression Tree Ensembles
Dai Feng, AbbVie Inc.; Richard Baumgartner, Merck Research Laboratories
2:30 PM Efficient Semi-Supervised Deep Learning and Machine Learning NLP System to Extract Clinical Measurements from Polysomnogram Laboratory Reports
Ioannis Malagaris, University of Texas Medical Branch; David En Shuo Hsu, University of Texas Medical Branch; Yong-fang Kuo, University of Texas Medical Branch
2:35 PM A Novel Regularized Neuro-Fuzzy Model for Chronic Diseases Outcome Prediction in Longitudinal Dietary Studies
Venkata Sukumar Gurugubelli, University of Massachusetts Dartmouth; Hua Fang, University of Massachusetts Dartmouth
2:40 PM Predicting Nursing Graduates Using Machine Learning Models
Xiaoyue Cheng, University of Nebraska at Omaha; Li Hannaford, Creighton University; Mary Kunes-Connell, Creighton University
2:45 PM Classification of Distinct Trajectories in Longitudinal Data with Irregularly Spaced Intervals: A Large Data Application of Post-Hoc Mixture Modeling of BLUPs from Mixed Models
Md Jobayer Hossain, Nemours Children's Health System; Benjamin E Leiby, Thomas Jefferson University
2:50 PM Worldwide Statistics Without Borders and Client to Consultant Bridge Collaboration: Statistical Storytelling in the Time of COVID
Michal Czapski, Statistics Without Borders; Joshua Derenski, Statistics Without Borders; Stephen Godfrey, Statistics Without Borders; Michelle Vanchu-Orosco, Greater Victoria Coalition to End Homelessness; SWB
2:55 PM Multiomics-Based Tensor Decomposition for Breast Cancer Subtyping
Qian Liu, University of Manitoba; Bowen Cheng, University of Toronto; Pingzhao Hu, University of Manitoba
3:00 PM A Prediction Model Method for Optimizing Appointment Overbooking in Health Care Clinics Using Electronic Health Care Record Data
Nathaniel O'Connell, Wake Forest School of Medicine; Joseph Skelton, Wake Forest School of Medicine
3:05 PM What Can Public Data Tell Us About the Quality of Life in Rural Small Towns?
Denise Bradford, University of Nebraska- Lincoln; Susan VanderPlas, University of Nebraska - Lincoln
3:10 PM What Makes You Unique?
Ben Seiler, Stanford University; Art Owen, Stanford University; Masayoshi Mase, Hitachi, Ltd