Maximilian Alber
Technische Universität Berlin
H-index: 12
Europe-Germany
Top articles of Maximilian Alber
Title | Journal | Author(s) | Publication Date |
|---|---|---|---|
Toward explainable artificial intelligence for precision pathology | Frederick Klauschen Jonas Dippel Philipp Keyl Philipp Jurmeister Michael Bockmayr | 2024/1/24 | |
RudolfV: A Foundation Model by Pathologists for Pathologists | arXiv preprint arXiv:2401.04079 | Jonas Dippel Barbara Feulner Tobias Winterhoff Simon Schallenberg Gabriel Dernbach | 2024/1/8 |
AI-driven, mIF-based cell-omics reveals spatially resolved cell signature for outcome prediction in NSCLC patients | Cancer Research | Simon Schallenberg Gabriel Dernbach Sharon Ruane Cornelius Böhm Lukas Ruff | 2024/3/22 |
Explainable artificial intelligence in pathology | Frederick Klauschen Jonas Dippel Philipp Keyl Philipp Jurmeister Michael Bockmayr | 2024/2/5 | |
Erklärbare Künstliche Intelligenz in der Pathologie | Frederick Klauschen Jonas Dippel Philipp Keyl Philipp Jurmeister Michael Bockmayr | 2024/2/5 | |
AI powered quantification of mitotic rate in H&E stained tissue detects significant differences between treatment groups of preclinical pancreas cancer xenografts | Cancer Research | Sharon Ruane Lukas Ruff Brian Reichholf Christina Aigner Emil Barbuta | 2023/4/4 |
Cell cycle arrest status predicted from H&E stained images using deep learning | Cancer Research | Christina Aigner Brian Reichholf Maxime Emschwiller Marija Pezer Tobias Winterhoff | 2023/4/4 |
970 Multiplex-immunofluorescence-based spatial characterization of the tumor-microenvironment of a large bicentric clinical non-small cell lung cancer cohort | Simon Schallenberg Gabriel Dernbach Sharon Ruane Cornelius Böhm Lukas Ruff | 2023/11/1 | |
Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides | arXiv preprint arXiv:2302.01813 | Miriam Hägele Johannes Eschrich Lukas Ruff Maximilian Alber Simon Schallenberg | 2023/2/3 |
Analysing cerebrospinal fluid with explainable deep learning: From diagnostics to insights | Neuropathology and Applied Neurobiology | Leonille Schweizer Philipp Seegerer Hee‐yeong Kim René Saitenmacher Amos Muench | 2023/2 |
1283 A novel, scalable deep learning-based approach to automated quality control of multiplex immunofluorescence images | Annika F Fink Roman Schulte-Sasse Martin Bauw Deepti Agrawal Beatriz Perez | 2023/11/1 | |
1276 Leveraging artificial intelligence (AI) models delineating tumor vs immune cell expression for scalable biomarker analysis of clinical trial samples: a digital image … | Cornelius Böhm Katja Lingelbach Blanca Pablos Simon Heinke Simon Schallenberg | 2023/11/1 | |
Artificial intelligence and pathology: from principles to practice and future applications in histomorphology and molecular profiling | Albrecht Stenzinger Maximilian Alber Michael Allgäuer Philipp Jurmeister Michael Bockmayr | 2022/9/1 | |
Deep learning assisted diagnosis of onychomycosis on whole-slide images | Journal of Fungi | Philipp Jansen Adelaida Creosteanu Viktor Matyas Amrei Dilling Ana Pina | 2022/8/28 |
Immunohistochemistry-informed AI systems for improved characterization of tumor-microenvironment in clinical non-small cell lung cancer H&E samples | Cancer Research | Thomas Mrowiec Sharon Ruane Simon Schallenberg Gabriel Dernbach Rumyana Todorova | 2022/6/15 |
Clarifying Assumptions About Artificial Intelligence Before Revolutionising Patent Law | GRUR International | Daria Kim Maximilian Alber Man Wai Kwok Jelena MitroviĆ Cristian Ramirez-Atencia | 2022/4/1 |
68MO Generalization of a deep learning model for HER2 status predictions on H&E-stained whole slide images derived from 3 neoadjuvant clinical studies | Annals of Oncology | M Hägele KR Müller C Denkert A Schneeweiss BV Sinn | 2022/9/1 |
Ten Assumptions About Artificial Intelligence That Can Mislead Patent Law Analysis | Max Planck Institute for Innovation & Competition Research Paper | Daria Kim Maximilian Alber Man Wai Kwok Jelena Mitrovic Cristian Ramirez-Atencia | 2021/8/1 |
Balancing the composition of word embeddings across heterogenous data sets | arXiv preprint arXiv:2001.04693 | Stephanie Brandl David Lassner Maximilian Alber | 2020/1/14 |
Interpretable deep neural network to predict estrogen receptor status from haematoxylin-eosin images | Artificial Intelligence and Machine Learning for Digital Pathology: State-of-the-Art and Future Challenges | Philipp Seegerer Alexander Binder René Saitenmacher Michael Bockmayr Maximilian Alber | 2020 |
