Grabsch, Heike I.

Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer

Kather, J. N., Pearson, A. T., Halama, N., Jäger, D., Krause, J., Loosen, S. H., Marx, A., Boor, P., Tacke, F., Neumann, U. P., et al. (2019) · Nature Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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A comprehensive survey of genomic alterations in gastric cancer reveals systematic patterns of molecular exclusivity and co-occurrence among distinct therapeutic targets

Deng, N., Goh, L. K., Wang, H., Das, K., Tao, J., Tan, I. B., Zhang, S., Lee, M., Wu, J., Lim, K. H., et al. (2012) · Gut

Gastric Cancer Management and OutcomesCancer Genomics and Diagnostics

Cited by 645

Clinical-Grade Detection of Microsatellite Instability in Colorectal Tumors by Deep Learning

Echle, A., Grabsch, H. I., Quirke, P., van den Brandt, P. A., West, N. P., Hutchins, G. G. A., Heij, L. R., Tan, X., Richman, S. D., Krause, J., et al. (2020) · Gastroenterology

Genetic factors in colorectal cancerAI in cancer detection

Cited by 376

Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study

Wagner, S. J., Reisenbüchler, D., West, N. P., Niehues, J. M., Zhu, J., Foersch, S., Veldhuizen, G. P., Quirke, P., Grabsch, H. I., van den Brandt, P. A., et al. (2023) · Cancer Cell

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 275

Swarm learning for decentralized artificial intelligence in cancer histopathology

Saldanha, O. L., Quirke, P., West, N. P., James, J. A., Loughrey, M. B., Grabsch, H. I., Salto-Tellez, M., Alwers, E., Cifci, D., Ghaffari Laleh, N., et al. (2022) · Nature Medicine

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 227

Development and validation of deep learning classifiers to detect Epstein-Barr virus and microsatellite instability status in gastric cancer: a retrospective multicentre cohort study

Muti, H. S., Heij, L. R., Keller, G., Kohlruss, M., Langer, R., Dislich, B., Cheong, J.-H., Kim, Y.-W., Kim, H., Kook, M.-C., et al. (2021) · The Lancet Digital Health

AI in cancer detectionGastric Cancer Management and Outcomes

Cited by 126

Artificial intelligence for detection of microsatellite instability in colorectal cancer—a multicentric analysis of a pre-screening tool for clinical application

Echle, A., Ghaffari Laleh, N., Quirke, P., Grabsch, H. I., Muti, H. S., Saldanha, O. L., Brockmoeller, S. F., van den Brandt, P. A., Hutchins, G. G. A., Richman, S. D., et al. (2022) · ESMO Open

AI in cancer detectionGenetic factors in colorectal cancer

Cited by 111

End-to-end prognostication in colorectal cancer by deep learning: a retrospective, multicentre study

Jiang, X., Hoffmeister, M., Brenner, H., Muti, H. S., Yuan, T., Foersch, S., West, N. P., Brobeil, A., Jonnagaddala, J., Hawkins, N., et al. (2024) · The Lancet Digital Health

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 108

Optimizing chemotherapy for frail and elderly patients (pts) with advanced gastroesophageal cancer (aGOAC): the GO2 phase III trial

Hall, P. S., Swinson, D., Waters, J. S., Wadsley, J., Falk, S., Roy, R., Tillett, T., Nicoll, J., Cummings, S., Grumett, S. A., et al. (2019) · Journal of Clinical Oncology

Frailty in Older AdultsGastric Cancer Management and Outcomes

Cited by 59

Benchmarking artificial intelligence methods for end-to-end computational pathology

Laleh, N. G., Muti, H. S., Lavinia Loeffler, C. M., Echle, A., Saldanha, O. L., Mahmood, F., Lu, M. Y., Trautwein, C., Langer, R., Dislich, B., et al. (2021) · bioRxiv (Cold Spring Harbor Laboratory)

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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