14.3k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Columbia UniversityUS16 papers
- Harvard UniversityUS13 papers
- Stanford UniversityUS12 papers
- Cornell UniversityUS11 papers
- National Institutes of HealthUS7 papers
- New York UniversityUS7 papers
- University of California, San FranciscoUS7 papers
- Emory UniversityUS6 papers
- Georgia Institute of TechnologyUS6 papers
- Hebrew University of JerusalemIL6 papers
- Imperial College LondonGB6 papers
- Mayo ClinicUS6 papers
9 papers · 1 filter
End-to-end Training for Whole Image Breast Cancer Diagnosis using An All Convolutional Design
Li Shen
We develop an end-to-end training algorithm for whole-image breast cancer diagnosis based on mammograms. It requires lesion annotations only at the first stage of training. After t…
Combination interventions for Hepatitis C and Cirrhosis reduction among people who inject drugs: An agent-based, networked population simulation experiment
Bilal Khan, Ian Duncan, Mohamad Saad +7
Hepatitis C virus (HCV) infection is endemic in people who inject drugs (PWID), with prevalence estimates above 60 percent for PWID in the United States. Previous modeling studies…
full-FORCE: A Target-Based Method for Training Recurrent Networks
Brian DePasquale, Christopher J. Cueva, Kanaka Rajan +2
Trained recurrent networks are powerful tools for modeling dynamic neural computations. We present a target-based method for modifying the full connectivity matrix of a recurrent n…
The Grism Lens-Amplified Survey from Space (GLASS). XII. Spatially Resolved Galaxy Star Formation Histories and True Evolutionary Paths at z > 1
L. E. Abramson, A. B. Newman, T. Treu +12
Modern data empower observers to describe galaxies as the spatially and biographically complex objects they are. We illustrate this through case studies of four, systems…
Emerging whole-cell modeling principles and methods
Arthur P. Goldberg, Balázs Szigeti, Yin Hoon Chew +3
Whole-cell computational models aim to predict cellular phenotypes from genotype by representing the entire genome, the structure and concentration of each molecular species, each…
Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks
Yading Yuan, Yeh-Chi Lo
Automatic skin lesion segmentation on dermoscopic images is an essential step in computer-aided diagnosis of melanoma. However, this task is challenging due to significant variatio…
Deep Learning to Improve Breast Cancer Early Detection on Screening Mammography
Li Shen, Laurie R. Margolies, Joseph H. Rothstein +3
The rapid development of deep learning, a family of machine learning techniques, has spurred much interest in its application to medical imaging problems. Here, we develop a deep l…
Sustainable computational science: the ReScience initiative
Nicolas P. Rougier, Konrad Hinsen, Frédéric Alexandre +42
Computer science offers a large set of tools for prototyping, writing, running, testing, validating, sharing and reproducing results, however computational science lags behind. In…
Automatic skin lesion segmentation with fully convolutional-deconvolutional networks
Yading Yuan
This paper summarizes our method and validation results for the ISBI Challenge 2017 - Skin Lesion Analysis Towards Melanoma Detection - Part I: Lesion Segmentation