E-LIB Suche - Ergebnisse für: Weitz, Philippe

1

Development and prognostic validation of a three-level NHG-..:

Sharma, Abhinav ; Weitz, Philippe ; Wang, Yinxi...
Breast Cancer Research. 26 (2024) 1 - p. , 2024

Link: https://doi.org/10.1186/..

2

Deep learning-based risk stratification of preoperative bre..:

Boissin, Constance ; Wang, Yinxi ; Sharma, Abhinav...
Breast Cancer Research. 26 (2024) 1 - p. , 2024

Link: https://doi.org/10.1186/..

3

The ACROBAT 2022 challenge: Automatic registration of breas..:

Weitz, Philippe ; Valkonen, Masi ; Solorzano, Leslie...
Medical Image Analysis. 97 (2024) - p. 103257 , 2024

Link: https://doi.org/10.1016/..

4

A Multi-Stain Breast Cancer Histological Whole-Slide-Image ..:

Weitz, Philippe ; Valkonen, Masi ; Solorzano, Leslie...
Scientific Data. 10 (2023) 1 - p. , 2023

Link: https://doi.org/10.1038/..

5

Transcriptome-wide prediction of prostate cancer gene expre..:

Weitz, Philippe ; Wang, Yinxi ; Kartasalo, Kimmo...
Bioinformatics. 38 (2022) 13 - p. 3462-3469 , 2022

Link: https://doi.org/10.1093/..

6

Using deep learning to detect patients at risk for prostate..:

Liu, Bojing ; Wang, Yinxi ; Weitz, Philippe...
iScience. 25 (2022) 7 - p. 104663 , 2022

Link: https://doi.org/10.1016/..

7

Predicting Molecular Phenotypes from Histopathology Images:..:

Wang, Yinxi ; Kartasalo, Kimmo ; Weitz, Philippe...
Cancer Research. 81 (2021) 19 - p. 5115-5126 , 2021

Link: https://doi.org/10.1158/..

8

Radiomic Feature Stability Analysis Based on Probabilistic ..:

, In: 2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI),

Haarburger, Christoph ; Schock, Justus ; Truhn, Daniel... - p. 1188-1192 , 2020

Link: https://doi.org/10.1109/..

9

Artificial intelligence in histopathology image analysis fo..:

Weitz, Philippe
I. P. Weitz, Y. Wang, K. Kartasalo, L. Egevad, J. Lindberg, H. Grönberg, M. Eklund, M. Rantalainen. "Transcriptome-wide prediction of prostate cancer gene expression from histopathology images using coexpression-based convolutional neural networks". Bioinformatics. vol. 38, no. 13, pp. 3462–3469, Jun. 2022. ::doi::10.1093/bioinformatics/btac343 ::pmid::35595235 ::isi::000808228800001. , 2023

Link: http://hdl.handle.net/10..

10

The ACROBAT 2022 Challenge: Automatic Registration Of Breas..:

Weitz, Philippe ; Valkonen, Masi ; Solorzano, Leslie...
http://arxiv.org/abs/2305.18033. , 2023

Link: http://arxiv.org/abs/230..

11

Increasing the usefulness of already existing annotations t..:

Weitz, Philippe ; Sartor, Viktoria ; Acs, Balazs...
http://arxiv.org/abs/2303.06727. , 2023

Link: http://arxiv.org/abs/230..

12

Transcriptome-wide prediction of prostate cancer gene expre..:

Weitz, Philippe ; Wang, Yinxi ; Kartasalo, Kimmo...
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9237721/. , 2022

Link: http://www.ncbi.nlm.nih...

13

ACROBAT -- a multi-stain breast cancer histological whole-s..:

Weitz, Philippe ; Valkonen, Masi ; Solorzano, Leslie...
http://arxiv.org/abs/2211.13621. , 2022

Link: http://arxiv.org/abs/221..

14

Using deep learning to detect patients at risk for prostate..:

Liu, Bojing ; Wang, Yinxi ; Weitz, Philippe...
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9272383/. , 2022

Link: http://www.ncbi.nlm.nih...

15

Transcriptome-wide prediction of prostate cancer gene expre..:

Weitz, Philippe ; Wang, Yinxi ; Kartasalo, Kimmo...
13. , 2022

Link: https://trepo.tuni.fi/ha..