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2025
Mark Enhancing the Prediction of Lymph Node Metastasis in Early Breast Cancer Using Deep Learning on Routine Full-Breast Mammograms
Zhang, Daqu ^LU ; Dihge, Looket ^LU ; Bendahl, Pär-Ola ^LU ; Arvidsson, Ida ^LU ; Dustler, Magnus ^LU ; Ellbrant, Julia ^LU ; Gulis, Kim ^LU ; Hjärtström, Malin ^LU ; Ohlsson, Mattias ^LU and Rejmer, Cornelia ^LU , et al. (2025) In Breast Cancer Research
- Working paper/Preprint › Preprint in preprint archive
Mark Advancing non-invasive melanoma diagnostics with deep learning and multispectral photoacoustic imaging
Merdasa, Aboma ^LU ; Fracchia, Alice ; Stridh, Magne ^LU ; Hult, Jenny ^LU ; Andersson, Emil ^LU ; Edén, Patrik ^LU ; Olariu, Victor ^LU and Malmsjö, Malin ^LU (2025) In Photoacoustics 45.
- Contribution to journal › Article
Mark Deep learning on routine full-breast mammograms enhances lymph node metastasis prediction in early breast cancer
Zhang, Daqu ^LU ; Dihge, Looket ^LU ; Bendahl, Pär-Ola ^LU ; Arvidsson, Ida ^LU ; Dustler, Magnus ^LU ; Ellbrant, Julia ^LU ; Gulis, Kim ^LU ; Hjärtström, Malin ^LU ; Ohlsson, Mattias ^LU and Rejmer, Cornelia ^LU , et al. (2025) In npj Digital Medicine 8(1).
- Contribution to journal › Article
Mark A spectroscopy-based machine learning framework on photoacoustic imaging data for automatic 3D delineation of melanoma tumors
Merdasa, Aboma ^LU ; Fracchia, Alice ; Stridh, Magne ^LU ; Hult, Jenny ^LU ; Andersson, Emil ^LU ; Edén, Patrik ^LU ; Olariu, Victor ^LU and Malmsjö, Malin ^LU (2025) Photons Plus Ultrasound: Imaging and Sensing 2025 In Progress in Biomedical Optics and Imaging - Proceedings of SPIE 13319.
- Chapter in Book/Report/Conference proceeding › Paper in conference proceeding
2024
Mark Identification of sentinel lymph node macrometastasis in breast cancer by deep learning based on clinicopathological characteristics
Zhang, Daqu ^LU ; Svensson, Miriam ^LU ; Edén, Patrik ^LU and Dihge, Looket ^LU (2024) In Scientific Reports 14.
- Contribution to journal › Article
Mark Facilitating clinically relevant skin tumor diagnostics with spectroscopy-driven machine learning
Andersson, Emil ^LU ; Hult, Jenny ^LU ; Troein, Carl ^LU ; Stridh, Magne ^LU ; Sjögren, Benjamin ^LU ; Pekar-Lukacs, Agnes ^LU ; Hernandez-Palacios, Julio ; Edén, Patrik ^LU ; Persson, Bertil ^LU and Olariu Annell, Victor ^LU , et al. (2024) In iScience 27(5).
- Contribution to journal › Article
2021
Mark A community effort to identify and correct mislabeled samples in proteogenomic studies
Yoo, Seungyeul ; Shi, Zhiao ; Wen, Bo ; Kho, SoonJye ; Pan, Renke ; Feng, Hanying ; Chen, Hong ; Carlsson, Anders ^LU ; Edén, Patrik ^LU and Ma, Weiping , et al. (2021) In Patterns 2(5).
- Contribution to journal › Article
2019
Mark Artificial neural network models to predict nodal status in clinically node-negative breast cancer
Dihge, Looket ^LU ; Ohlsson, Mattias ^LU ; Edén, Patrik ^LU ; Bendahl, Pär Ola ^LU and Rydén, Lisa ^LU (2019) In BMC Cancer 19(1).
- Contribution to journal › Article
Mark Establishing strong imputation performance of a denoising autoencoder in a wide range of missing data problems
Abiri, Najmeh ^LU ; Linse, Björn ^LU ; Edén, Patrik ^LU and Ohlsson, Mattias ^LU (2019) In Neurocomputing 365. p.137-146
- Contribution to journal › Article
2018
Mark Identification and validation of single-sample breast cancer radiosensitivity gene expression predictors
Sjöström, Martin ^LU ; Staaf, Johan ^LU ; Edén, Patrik ^LU ; Wärnberg, Fredrik ; Bergh, Jonas ; Malmström, Per ^LU ; Fernö, Mårten ^LU ; Niméus, Emma ^LU and Fredriksson, Irma (2018) In Breast Cancer Research 20(1).
- Contribution to journal › Article

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