Abstracts and Publications

2025
2024
2023
2022
2021

Publications 2024

Digital Pathology & AI Congress: Europe, December 2024 - Poster

Comparative Analysis and Clinical Validation of Vision Transformer and U-Net Models for Automated Kidney Fibrosis Assessment

Nader Aldoj, Kai Standvoss, Mariam Sadeq, et al
Society for Immunotherapy of Cancer, October 2024 - Poster

Artificial intelligence image models optimizing tumor vs immune cell profiling for accurate biomarker analysis in NSCLC precision drug development

Cornelius Boehm, Laura Schlieker, Martin Szyska, et al
New England Journal of Medicine AI, October 2024 - Paper

AI-Based Anomaly Detection for Clinical-Grade Histopathological Diagnostics

Jonas Dippel, Niklas Prenißl, Julius Hense, et al
European Congress of Pathology, September 2024 - Poster

AI-driven Quality Control for Immunohistochemistry: Automated detection and exclusion of artifacts for downstream analysis in digitized pathology slides

Katja Lingelbach, Martin Bauw, Arne Schmidt, et al
European Journal of Cancer, August 2024 - Paper

Dissecting AI-based mutation prediction in lung adenocarcinoma: A comprehensive real-world study

Gabriel Dernbach, Daniel Kazdal, Lukas Ruff, et al
Cancer Research, March 2024 - Poster

Neoadjuvant chemotherapy and radiation shape the local and regional adaptive antitumor immune response in lung squamous cell carcinomas

Rosemarie Krupar, Justin Nieder, Johannes Braegelmann, et al
AACR Cancer Research, march 2024 - Poster

TTF-1 status in early-stage lung adenocarcinoma is an independent predictor of relapse and survival superior to tumor grading

Simon Schallenberg, Gabriel Dernbach, Mihnea P Dragomir, et al
Cancer Research, March 2024 - Poster

AI-driven, mIF-based cell-omics reveals spatially resolved cell signature for outcome prediction in NSCLC patients

Simon Schallenberg, Gabriel Dernbach, Sharon Ruane, et al
Pathologie, February 2024, Article

Explainable artificial intelligence in pathology

Frederick Klauschen, Jonas Dippel, Philipp Keyl, et al
European Journal of Cancer, January 2024 - Paper

TTF-1 status in early-stage lung adenocarcinoma is an independent predictor of relapse and survival superior to tumor grading

Simon Schallenberg, Gabriel Dernbach, Mihnea P Dragomir, et
Annual Review of Pathology: Mechanisms of Disease, January 2024 - Paper

Toward explainable artificial intelligence for precision pathology

Frederick Klauschen, Jonas Dippel, Philipp Keyl, et al
ARXIV, January 2024 - Paper

RudolfV: A Foundation Model by Pathologists for Pathologists

Jonas Dippel, Barbara Feulner, Tobias Winterhoff, et al

Publications 2023

Digital Pathology & AI Congress, december 2023 - poster

Maximize Biomarker Information from Tissue Samples: AI/Machine Learning for Combined Spatial Analysis of Multiplex IF and H&E

Roman Schulte-Sasse, Beatriz Perez, Deepti Agrawal, et al
Journal for ImmunoTherapy of Cancer, november 2023 - poster

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, et al
Journal for ImmunoTherapy of Cancer, november 2023 - poster

A novel, scalable deep learning-based approach to automated quality control of multiplex immunofluorescence images

Annika F Fink, Roman Schulte-Sasse, Martin Bauw, et al
Journal for ImmunoTherapy of Cancer, november 2023 - poster

Leveraging artificial intelligence (AI) models delineating tumor vs immune cell expression for scalable biomarker analysis of clinical trial samples: a digital image analysis approach for NSCLC

Cornelius Böhm, Katja Lingelbach, Blanca Pablos, et al
Toxicologic Pathology, september 2023, poster

AI-based testicular staging in dogs from nonclinical toxicity studies

Leonie Herkommer, Maximilian Gottschalk, Miriam Hägele, et al
Thirty-seventh Conference on Neural Information Processing Systems Datasets and Benchmarks Track, june 2023 - paper

DiffInfinite: Large Mask-Image Synthesis via Parallel Random Patch Diffusion in Histopathology

Marco Aversa, Gabriel Nobis, Miriam Hägele, et al
BIORXIV, may 2023 - paper

High-resolution molecular atlas of a lung tumor in 3D

Tancredi Massimo Pentimalli, Simon Schallenberg, Daniel Leon-Perinan, et al
The American Association for Cancer Research, april 2023 - poster

Cell cycle arrest status predicted from H&E stained images using deep learning

Christina Aigner, Brian Reichholf, Maxime Emschwiller, et al
The American Association for Cancer Research, april 2023 - poster

AI powered quantification of mitotic rate in H&E stained tissue detects significant differences between treatment groups of preclinical pancreas cancer xenografts

Sharon Ruane, Lukas Ruff, Brian Reichholf, et al
ARVIX, february 2023 - paper

Leveraging weak complementary labels to improve semantic segmentation of hepatocellular carcinoma and cholangiocarcinoma in H&E-stained slides

Miriam Hägele, Johannes Eschrich, Lukas Ruff, et al
Journal of Pathology Informatics, january 2023 - paper

Imaging bridges pathology and radiology

Hansmann Martin-Leo, Klauschen Frederick, Samek Wojciech, et al

Publications 2022

Pathologie Heidelb, november 2022 - review paper

The tumor microenvironment-relay station for prognosis and therapy response

Rosemarie Krupar
Transactions on Machine Learning Research, november 2022 - paper

Exposing Outlier Exposure: What Can Be Learned From Few, One, and Zero Outlier Images

Philipp Liznerski, Lukas Ruff, Robert A Vandermeulen, et al
Seminars in cancer biology, september 2022 - paper

Artificial intelligence and pathology: From principles to practice and future applications in histomorphology and molecular profiling

Albrecht Stenzinger, Maximilian Alber, Michael Allgäuer, et al
Annals of Oncology, september 2022 - talkoster

68MO Generalization of a deep learning model for HER2 status predictions on H&E-stained whole slide images derived from 3 neoadjuvant clinical studies

Miriam Hägele, Klaus-Robert Müller, Carsten Denkert, et al
VIRCHOWS ARCHIV, september 2022 - talk

Extensive spatial characterisation of the tumour-microenvironment in a large clinical non-small cell lung cancer cohort and correlation with clinical and pathological parameters

Sharon Ruane, Simon Schallenberg, Cornelius Böhm, et al
Journal of Fungi, august 2022 - paper

Deep learning assisted diagnosis of onychomycosis on whole-slide images

Philipp Jansen, Adelaida Creosteanu, Viktor Matyas, et al
Cancer Research, june 2022 - poster

Immunohistochemistry-informed AI systems for improved characterization of tumor-microenvironment in clinical non-small cell lung cancer H&E samples

Thomas Mrowiec, Sharon Ruane, Simon Schallenberg, et al
GRUR International, april 2022 - paper

Clarifying Assumptions About Artificial Intelligence Before Revolutionising Patent Law

Daria Kim, Maximilian Alber, Man Wai Kwok, et al
The Journal of Pathology, april 2022 - paper

Machine learning models predict the primary sites of head and neck squamous cell carcinoma metastases based on DNA methylation

Maximilian Leitheiser, David Capper, Philipp Seegerer, et al

Unlock the power of biomedical data.

At Aignostics, we're transforming complex biomedical data into actionable insights that drive innovation in healthcare. Stay connected with us and be the first to learn how we’re shaping the future of medicine through data-driven solutions.