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Here you can browse the complete list of projects on CDAS whose requests for data/biospecimens were approved.

Name Principal Investigator Institution Study Date Approved Project ID
Using machine learning and big data for optimizing medication prescriptions for lung cancer Jason Chang National Yunlin University of Science and Technology PLCO Nov 22, 2021 PLCO-859
Using Machine Learning for the Early Diagnosis of Pancreatic Cancer Carol Hersh Great Neck South High School PLCO Jul 21, 2020 PLCO-651
Using Machine learning to find gender differences in the bone morphology of the first rib Andreas Prescher MOCA, Institute of Molecular and Cellular Anatomy, RWTH Aachen University NLST Aug 22, 2019 NLST-554
Using machine learning to predict risk from clinical factors and medical image Qiang CAO Independent PLCO Aug 9, 2018 PLCO-390
Using machine learning to understand demographic differences when predicting ovarian cancer Devanshi Kothari Independent PLCO Jul 15, 2021 PLCO-806
Using markers of endemic fungal infection to predict malignancy in lung nodules identified on screening CT Laszlo Vaszar Mayo Clinic Arizona NLST Apr 13, 2016 NLST-205
Using NLST Data to find the Relationships between Nicotine Dependence Variables and CT Screening Efficacy as well as Survival Outcomes Junjia Zhu Penn State Hershey Medical Center NLST Jan 16, 2015 NLST-113
Using PLCO Chest X-Ray data to train medical imaging models on Google Cloud Platform Mikhail Fomitchev Google, LLC PLCO May 12, 2020 PLCOI-619
Using PRS for CRC screening Ulrike Peters Fred Hutchinson Cancer Research Center PLCO Dec 8, 2021 PLCO-872
Using Region based Convolutional Neural Networks (RCNNs) and its variants to detect, classify, segment and predict lung cancer signatures from NLST data Pratik Shah Massachusetts Institute of Technology NLST Nov 13, 2019 NLST-599
Using Self-reported Baseline Questionnaire Data from the PLCO Trial to Create a Three-Outcome Absolute Risk Model for Breast, Ovarian and Endometrial Cancer Aimee Kreimer NCI, DCP, EDRG PLCO Jul 1, 2006 2006-0011
Using the NLST database to develop a lung cancer malignancy prediction tool from CT and WSI data Thomas Langø SINTEF NLST Aug 22, 2019 NLST-553
Using the SF-36 to Track Health Status Outcomes Among Participants in the PLCO Lance Yokochi PHREI PLCO Jul 1, 2006 2006-0270
Using time-series data to predict nodule evolution Joseph Jacob University College London NLST Jun 18, 2019 NLST-526
Utilization of deep learning methodology for automated lung nodule detection Elliot English MetaMind NLST May 28, 2015 NLST-140
Utilization of machine learning to create a predictive model for ovarian cancer based on pelvic ultrasound, CA-125, and clinical characteristics Graham Chapman Case Western Reserve University PLCO Oct 18, 2022 PLCO-1074
Utilizing high-dimensional data with genome-wide scan data to identify novel genetic susceptibility variants for colorectal cancer Ulrike Peters Fred Hutchinson Cancer Research Center PLCO Mar 28, 2013 PLCO-23
Utilizing Machine Learning for Causal Inference using Observational Data. Rafiullah . Central South University, Changsha, Hunan, China PLCO Dec 4, 2023 PLCO-1402
Utilizing PLCO Prostate Survival Data to predict mortality in chemoprevention studies Paul Pinsky NCI, DCP, EDRG PLCO Aug 26, 2010 2010-0141
Utilizing sequence and imputed genotype data to identify novel genetic susceptibility variants for colorectal cancer Ulrike Peters Fred Hutchinson Cancer Center PLCO Mar 6, 2014 PLCO-68