| 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 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 population-based healthcare data to investigate the risk of mortality or relapse after radiotherapy for prostate cancer |
Bill Nailon |
University of Edinburgh |
PLCO |
Jun 24, 2024 |
PLCO-1601 |
| 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 Architectures for the Automated Detection of Pulmonary tumor and Tuberculosis in Thoracic Radiographic Imaging |
Mutlu Avci |
Çukurova University |
NLST |
Jan 10, 2025 |
NLST-1380 |
| 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 |
| Utilization of neural networks to identify and predict future cancer growth with images |
Wenzhi Zhang |
Detroit Country Day School |
NLST |
Sep 30, 2024 |
NLST-1329 |
| 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 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 |
| Validate Colon Cancer Model trained on synthetic data against PLCO dataset patient data |
Jeremy Howard |
Lucem Health, Inc. |
PLCO |
May 14, 2024 |
PLCO-1553 |
