| Minibatch Gradient Descent Method for Deep Survival Analysis |
James Sharpnack |
University of California-Davis |
NLST |
Nov 7, 2019 |
NLST-597 |
| Integrating AI into workflow |
akio iwase |
NucleusHealth |
PLCO |
Nov 4, 2019 |
PLCOI-542 |
| Exascale Deep Learning for screening based predictive modeling for lung cancer |
Greeshma Agasthya |
Oak Ridge National Laboratory |
PLCO |
Nov 4, 2019 |
PLCOI-544 |
| Incorporating Biomarkers to Improve Lung Cancer Risk Prediction |
Samir Hanash |
University of Texas at MD Anderson |
PLCO |
Nov 4, 2019 |
PLCO-549 |
| Extended Cancer Prediction from Lung CT Images |
Atilla Kiraly |
Google |
NLST |
Nov 1, 2019 |
NLST-594 |
| Individual lung cancer survival estimation based on radiomics analysis |
Yujiao Wu |
University of Technology Sydney |
NLST |
Oct 31, 2019 |
NLST-596 |
| use active learning to do the tumor segmentation. |
Sijie Wang |
the university of Tokyo |
NLST |
Oct 31, 2019 |
NLST-595 |
| Colorectal cancer risk factors, risk prediction and blood-based biomarker by tumor consensus molecular subtype |
Jennifer Davis |
University of Kansas Medical Center |
PLCO |
Oct 29, 2019 |
2018-0009 |
| Interpretable Graph Convolutional Networks with CPC features for Whole Slide Histology Classification |
Faisal Mahmood |
Brigham and Women's Hospital |
NLST |
Oct 29, 2019 |
NLST-592 |
| Dietary Inflammatory Index and risk of differentiated thyroid cancer in the Prostate, Lung, Colorectal and Ovarian (PLCO) Cancer Screening Trial |
Li Chen |
Department of the Endocrine and Breast Surgery, The First Affiliated hospital of Chongqing Medical university |
PLCO |
Oct 24, 2019 |
PLCO-543 |
| Machine Learning to select patients benefiting from prostate cancer screening |
Jean-Emmanuel Bibault |
Laboratory of Artificial Intelligence in Medicine and Biomedical Physics, Stanford University |
PLCO |
Oct 24, 2019 |
PLCO-541 |
| Predicting Cancer diagnosis based on preliminary screenings |
Jonathan Mendoza |
Independent |
PLCO |
Oct 24, 2019 |
PLCO-532 |
| Exascale Deep Learning for Predictive Modeling of Lung Cancer |
Greeshma Agasthya |
Oak Ridge National Laboratory |
NLST |
Oct 18, 2019 |
NLST-586 |
| Lung cancer imaging biomarker development on computed tomography using artificial intelligence |
Shazia Akbar |
Altis Labs |
NLST |
Oct 15, 2019 |
NLST-588 |
| Application and evaluation of Deep Learning to Predict tumors in medical images annotated using crowdsourcing |
Aakanksha Sanctis |
Maastricht University,Intitute of Data Science |
NLST |
Oct 15, 2019 |
NLST-587 |
| Bias-correction of relative risks by robustly incorporating validation studies that include multiple methods of physical activity assessment and related biomarkers |
Xin Zhou |
Yale University |
IDATA |
Oct 15, 2019 |
IDATA-32 |
| Quantitative analysis of tissue morphology and biomarkers with convolutional neural networks for improve prognostics of prostate cancer |
Geert Litjens |
Radboud University Medical Center |
PLCO |
Oct 11, 2019 |
PLCOI-540 |
| Intelligent personable treatment recommendation |
Xiaoshui Huang |
The University of Sydney |
NLST |
Oct 10, 2019 |
NLST-584 |
| Evaluation of Patients Data using AI techniques and It's Application in Pancreatic Cancer Differential Diagnosis |
Wanessa Sena |
Federal Institute of Pernambuco |
PLCO |
Oct 10, 2019 |
PLCO-539 |
| Link-based survival additive models with mixed types of censoring. |
Giampiero Marra |
University College London |
PLCO |
Oct 8, 2019 |
PLCO-538 |
