Stegmaier, Johannes

Third-generation in situ hybridization chain reaction: multiplexed, quantitative, sensitive, versatile, robust

Choi, H. M. T., Schwarzkopf, M., Fornace, M. E., Acharya, A., Artavanis, G., Stegmaier, J., Cunha, A., & Pierce, N. A. (2018) · Development

Molecular Biology Techniques and ApplicationsAdvanced biosensing and bioanalysis techniques

Cited by 1,495

Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers

Khader, F., Müller-Franzes, G., Wang, T., Han, T., Tayebi Arasteh, S., Haarburger, C., Stegmaier, J., Bressem, K., Kuhl, C., Nebelung, S., et al. (2023) · Radiology

Multimodal Machine Learning ApplicationsMachine Learning in Healthcare

Cited by 107

Medical transformer for multimodal survival prediction in intensive care: integration of imaging and non-imaging data

Khader, F., Kather, J. N., Müller-Franzes, G., Wang, T., Han, T., Tayebi Arasteh, S., Hamesch, K., Bressem, K., Haarburger, C., Stegmaier, J., et al. (2023) · Scientific Reports

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 57

Robust optimal design of experiments for model discrimination using an interactive software tool

Stegmaier, J., Skanda, D., & Lebiedz, D. (2013) · PLoS ONE

Optimal Experimental Design MethodsControl Systems and Identification

Cited by 15

A Deep Learning-based in silico Framework for Optimization on Retinal Prosthetic Stimulation

Wu, Y., Karetić, I., Stegmaier, J., Walter, P., & Merhof, D. (2023) · 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)

Neuroscience and Neural EngineeringTactile and Sensory Interactions

Cited by 6