CsAuthors.net database
Most of the data is coming from the
DBLP Computer Science Bibliography
and the rest is coming from CsAuthors.net own database.
We are working hard to keep everything up-to-date. However, we know that there are many papers not yet included in our dataset.
If something is wrong or missing, feel free to write me at
We are working hard to keep everything up-to-date. However, we know that there are many papers not yet included in our dataset.
If something is wrong or missing, feel free to write me at
my email address
.
The "Dijkstra number"
The Dijkstra number describes the collaborative distance between an author and
Edsger W. Dijkstra.
In our dataset 90.3% of authors are connected to Edsger W. Dijkstra and the average Dijkstra number among them is 5.07.
These kind of number/metrics are quite famous and already well defined in other fields.
In our dataset 90.3% of authors are connected to Edsger W. Dijkstra and the average Dijkstra number among them is 5.07.
These kind of number/metrics are quite famous and already well defined in other fields.
- The "Erdős number" expresses the collaborative distance with Paul Erdős, the famous Hungarian mathematician.
- The "Bacon number" expresses the co-acting distance with Kevin Bacon.
The "Erdős number"
The Erdős number describes the collaborative distance between an author and
Paul Erdős.
In our dataset 90.3% of authors are connected to Paul Erdős and the average Erdős number among them is 4.68.
Find more on Wikipedia with an article on the"Erdős number".
In our dataset 90.3% of authors are connected to Paul Erdős and the average Erdős number among them is 4.68.
Find more on Wikipedia with an article on the"Erdős number".
Pamela LaMontagne
Orcid: 0000-0002-6752-8518Affiliations:
- Washington University in St Louis School of Medicine, MO, USA
According to our database1,
Pamela LaMontagne
authored at least 16 papers
between 2003 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
On csauthors.net:
Bibliography
2025
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, September, 2025
2024
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, September, 2024
2023
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
Dataset, November, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Brain MR Image Synthesis for Tumor Segmentation (BraSyn).
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
CoRR, 2023
The Brain Tumor Segmentation (BraTS) Challenge 2023: Local Synthesis of Healthy Brain Tissue via Inpainting.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
CoRR, 2023
Gene-SGAN: a method for discovering disease subtypes with imaging and genetic signatures via multi-view weakly-supervised deep clustering.
, , , , , , , , , , , , , , , , , , , , , , , , , , ,
CoRR, 2023
Non-invasive classification of IDH mutation status of gliomas from multi-modal MRI using a 3D convolutional neural network.
Proceedings of the Medical Imaging 2023: Computer-Aided Diagnosis, San Diego, 2023
2022
β-amyloid PET harmonisation across longitudinal studies: Application to AIBL, ADNI and OASIS3.
, , , , , , , , , , , , , ,
NeuroImage, 2022
MRI-based classification of IDH mutation and 1p/19q codeletion status of gliomas using a 2.5D hybrid multi-task convolutional neural network.
CoRR, 2022
Integrative Imaging Informatics for Cancer Research: Workflow Automation for Neuro-oncology (I3CR-WANO).
, , , , , , , , , , , , , ,
CoRR, 2022
2021
BrainTumorNet: multi-task learning for joint segmentation of high-grade glioma and brain metastases from MR images.
, , , , , ,
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
2020
Brain extraction on MRI scans in presence of diffuse glioma: Multi-institutional performance evaluation of deep learning methods and robust modality-agnostic training.
, , , , , , , , , , , , , , , , , ,
NeuroImage, 2020
Automatic detection of contrast enhancement in T1-weighted brain MRI of human adults.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2018
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge.
, , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ,
et al.
CoRR, 2018
2016
Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research.
, , , , , ,
Neuroinformatics, 2016
2003
, , , , , , ,
NeuroImage, 2003