Dalia Rodriguez Salas
Dalia Rodríguez Salas, M. Eng.
Pattern Recognition Lab, Friedrich-Alexander-Universität Erlangen-Nürnberg
Martensstr. 3
91058 Erlangen
Germany
- Phone number: +49152102-28519
- Email: dalia.rodriguez@fau.de
Office hours
Daily Mo, Tu, We, Th, Fr,Academic CV
- Since 03/2017:
PhD candidate at Pattern Recognition Lab, Friedrich-Alexander University Erlangen-Nürnberg
Projects
2017
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Development of multi-modal, multi-scale imaging framework for the early diagnosis of breast cancer
(FAU Funds)
Term: March 1, 2017 - June 30, 2020Breast cancer is the leading cause of cancer related deaths in women, the second most common cancer worldwide. The development and progression of breast cancer is a dynamic biological and evolutionary process. It involves a composite organ system, with transcriptome shaped by gene aberrations, epigenetic changes, the cellular biological context, and environmental influences. Breast cancer growth and response to treatment has a number of characteristics that are specific to the individual patient, for example the response of the immune system and the interaction with the neighboring tissue. The overall complexity of breast cancer is the main cause for the current, unsatisfying understanding of its development and the patient’s therapy response. Although recent precision medicine approaches, including genomic characterization and immunotherapies, have shown clear improvements with regard to prognosis, the right treatment of this disease remains a serious challenge. The vision of the BIG-THERA team is to improve individualized breast cancer diagnostics and therapy, with the ultimate goal of extending the life expectancy of breast cancer sufferers. Our primary contribution in this regard is developing a multi-modal, multi-scale framework for the early diagnosis of the molecular sub-types of breast cancer, in a manner that supplements the clinical diagnostic workflow and enables the early identification of patients compatible with specific immunotherapeutic solutions.
Publications
2023
Conference Contributions
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Transferring Quantified Emotion Knowledge for the Detection of Depression in Alzheimer’s Disease Using Forestnets
International Conference on Acoustics, Speech, and Signal Processing (ICASSP) (Rhodes Island, June 4, 2023 - June 10, 2023)
In: ICASSP 2023 2023
DOI: 10.1109/ICASSP49357.2023.10095219
BibTeX: Download
2022
Journal Articles
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Interpreting acoustic features for the assessment of Alzheimer's disease using ForestNet
In: Smart Health 26 (2022), Article No.: 100347
ISSN: 2352-6483
DOI: 10.1016/j.smhl.2022.100347
BibTeX: Download - , , , , , , , :
Interpreting acoustic features for the assessment of Alzheimer's disease using ForestNet
In: Smart Health 26 (2022), Article No.: 100347
ISSN: 2352-6483
DOI: 10.1016/j.smhl.2022.100347
BibTeX: Download
Conference Contributions
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GAN-based Augmentation of Mammograms to Improve Breast Lesion Detection
Bildverarbeitung für die Medizin 2022 (Heidelberg, June 26, 2022 - June 28, 2022)
In: Klaus Maier-Hein, Thomas M. Deserno, Heinz Handels, Andreas Maier, Christoph Palm, Thomas Tolxdorff (ed.): Bildverarbeitung für die Medizin 2022, Wiesbaden: 2022
DOI: 10.1007/978-3-658-36932-3_66
BibTeX: Download - , , , :
GAN-based Augmentation of Mammograms to Improve Breast Lesion Detection
German Workshop on Medical Image Computing, 2022 (Heidelberg, DEU, June 26, 2022 - June 28, 2022)
In: Klaus Maier-Hein, Thomas M. Deserno, Heinz Handels, Andreas Maier, Christoph Palm, Thomas Tolxdorff (ed.): Informatik aktuell 2022
DOI: 10.1007/978-3-658-36932-3_66
BibTeX: Download
2021
Conference Contributions
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Ultrasound Breast Lesion Detection using Extracted Attention Maps from a Weakly Supervised Convolutional Neural Network
Bildverarbeitung für die Medizin 2021 (Regensburg, March 7, 2021 - March 9, 2021)
In: Palm, Christoph; Deserno, Thomas M.; Handels, Heinz;Maier, Andreas; Maier-Hein, Klaus;Tolxdorff, Thomas. (ed.): Bildverarbeitung für die Medizin 2021, Wiesbaden: 2021
DOI: 10.1007/978-3-658-33198-6
BibTeX: Download
2020
Journal Articles
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Mapping Ensembles of Trees to Sparse, Interpretable Multilayer Perceptron Networks
In: SN Computer Science 1 (2020), Article No.: 252
ISSN: 2661-8907
DOI: 10.1007/s42979-020-00268-y
BibTeX: Download
Conference Contributions
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ForestNet – Automatic Design of Sparse Multilayer Perceptron Network Architectures Using Ensembles of Randomized Trees
The 5th Asian Conference on Pattern Recognition (Auckland, New Zealand, November 26, 2019 - November 29, 2019)
In: Pattern Recognition 2020
DOI: 10.1007/978-3-030-41404-7_3
URL: https://link.springer.com/chapter/10.1007/978-3-030-41404-7_3
BibTeX: Download
2017
Conference Contributions
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Fast and robust selection of highly-correlated features in regression problems
International Conference on Machine Vision Applications (Nagoya University, Nagoya, Japan, May 8, 2017 - May 12, 2017)
In: 2017 Fifteenth IAPR International Conference on Machine Vision Applications (MVA) 2017
DOI: 10.23919/MVA.2017.7986905
URL: https://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2017/Dalia17-IARP.pdf
BibTeX: Download
2014
Conference Contributions
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Voting Algorithms Model with a Support Sets System by Class
13th Mexican International Conference on Artificial Intelligence (MICAI) (Tuxtla Gutierrez, Mexico, November 16, 2014 - November 22, 2014)
In: MICAI 2014: Nature-Inspired Computation and Machine Learning 2014
DOI: 10.1007/978-3-319-13650-9_12
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2013
Conference Contributions
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Designing partially-connected, multilayer perceptron neural nets through information gain
The 2013 International Joint Conference on Neural Networks (IJCNN) (Dallas, TX, USA, August 4, 2013 - August 9, 2013)
In: The 2013 International Joint Conference on Neural Networks (IJCNN) 2013
DOI: 10.1109/IJCNN.2013.6706991
URL: http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2013/Dalia13-PcMLP.pdf
BibTeX: Download