Chen, Po-Hsuan Cameron

Development and validation of a deep learning algorithm for improving Gleason scoring of prostate cancer

Nagpal, K., Foote, D., Liu, Y., Chen, P.-H. C., Wulczyn, E., Tan, F., Olson, N., Smith, J. L., Mohtashamian, A., Wren, J. H., et al. (2019) · npj Digital Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis

Chen, P.-H. C., Gadepalli, K., MacDonald, R., Liu, Y., Kadowaki, S., Nagpal, K., Kohlberger, T., Dean, J., Corrado, G. S., Hipp, J. D., et al. (2019) · Nature Medicine

AI in cancer detectionAugmented Reality Applications

Cited by 342

How to develop machine learning models for healthcare

Chen, P.-H. C., Liu, Y., & Peng, L. (2019) · Nature Materials

Machine Learning in HealthcareArtificial Intelligence in Healthcare and Education

Cited by 274

Deep learning-based survival prediction for multiple cancer types using histopathology images

Wulczyn, E., Steiner, D. F., Xu, Z., Sadhwani, A., Wang, H., Flament-Auvigne, I., Mermel, C. H., Chen, P.-H. C., Liu, Y., & Stumpe, M. C. (2020) · PLOS ONE

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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Robust and data-efficient generalization of self-supervised machine learning for diagnostic imaging

Azizi, S., Culp, L., Freyberg, J., Mustafa, B., Baur, S., Kornblith, S., Chen, T., Tomasev, N., Mitrović, J., Strachan, P., et al. (2023) · Nature Biomedical Engineering

Domain Adaptation and Few-Shot LearningArtificial Intelligence in Healthcare and Education

Cited by 250

Interpretable survival prediction for colorectal cancer using deep learning

Wulczyn, E., Steiner, D. F., Moran, M., Plass, M., Reihs, R., Tan, F., Flament-Auvigne, I., Brown, T., Regitnig, P., Chen, P.-H. C., et al. (2021) · npj Digital Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 231

Artificial intelligence in digital breast pathology: Techniques and applications

Ibrahim, A., Gamble, P., Jaroensri, R., Abdelsamea, M. M., Mermel, C. H., Chen, P.-H. C., & Rakha, E. A. (2020) · The Breast

AI in cancer detectionArtificial Intelligence in Healthcare and Education

Cited by 202

Determining breast cancer biomarker status and associated morphological features using deep learning

Gamble, P., Jaroensri, R., Wang, H., Tan, F., Moran, M., Brown, T., Flament-Auvigne, I., Rakha, E. A., Toss, M., Dabbs, D. J., et al. (2021) · Communications Medicine

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

Cited by 154

Evaluation of artificial intelligence on a reference standard based on subjective interpretation

Chen, P.-H. C., Mermel, C. H., & Liu, Y. (2021) · The Lancet Digital Health

Artificial Intelligence in Healthcare and EducationArtificial Intelligence in Healthcare

Cited by 63

Pathologist validation of a machine learning–derived feature for colon cancer risk stratification

L’Imperio, V., Wulczyn, E., Plass, M., Müller, H., Tamini, N., Gianotti, L., Zucchini, N., Reihs, R., Corrado, G. S., Webster, D. R., et al. (2023) · JAMA Network Open

AI in cancer detectionRadiomics and Machine Learning in Medical Imaging

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