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Your search keyword '"Chen, Po-Hsuan"' showing total 18 results
Start Over Author "Chen, Po-Hsuan" Publisher elsevier bv
18 results on '"Chen, Po-Hsuan"'

1. Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study

Author

Schaekermann, Mike, primary, Spitz, Terry, additional, Pyles, Malcolm, additional, Cole-Lewis, Heather, additional, Wulczyn, Ellery, additional, Pfohl, Stephen R., additional, Martin, Donald, additional, Jaroensri, Ronnachai, additional, Keeling, Geoff, additional, Liu, Yuan, additional, Farquhar, Stephanie, additional, Xue, Qinghan, additional, Lester, Jenna, additional, Hughes, Cían, additional, Strachan, Patricia, additional, Tan, Fraser, additional, Bui, Peggy, additional, Mermel, Craig H., additional, Peng, Lily H., additional, Matias, Yossi, additional, Corrado, Greg S., additional, Webster, Dale R., additional, Virmani, Sunny, additional, Semturs, Christopher, additional, Liu, Yun, additional, Horn, Ivor, additional, and Cameron Chen, Po-Hsuan, additional

Published
2024
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2. An End-to-End Platform for Digital Pathology Using Hyperspectral Autofluorescence Microscopy and Deep Learning-Based Virtual Histology

Author

McNeil, Carson, primary, Wong, Pok Fai, additional, Sridhar, Niranjan, additional, Wang, Yang, additional, Santori, Charles, additional, Wu, Cheng-Hsun, additional, Homyk, Andrew, additional, Gutierrez, Michael, additional, Behrooz, Ali, additional, Tiniakos, Dina, additional, Burt, Alastair D., additional, Pai, Rish K., additional, Tekiela, Kamilla, additional, Cameron Chen, Po-Hsuan, additional, Fischer, Laurent, additional, Martins, Eduardo Bruno, additional, Seyedkazemi, Star, additional, Freedman, Daniel, additional, Kim, Charles C., additional, and Cimermancic, Peter, additional

Published
2024
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4. AI-enabled virtual hematoxylin and eosin and Masson’s trichrome staining for non-alcoholic fatty liver disease activity scoring from single unstained slide

Author

McNeil, Carson, primary, Wong, Pok Fai, additional, Sridhar, Niranjan, additional, Wang, Yang, additional, Santori, Charles, additional, Wu, Cheng Hsun, additional, Homyk, Andrew, additional, Gutierrez, Michael, additional, Behrooz, Ali, additional, Tiniakos, Dina, additional, Burt, Alastair, additional, Pai, Rish, additional, Tekiela, Kamilla, additional, Chen, Po-Hsuan Cameron, additional, Rao, Sudha, additional, Hanks, Debra, additional, Sridharan, Shamira, additional, Martins, Eduardo Bruno, additional, Seyedkazemi, Star, additional, Fischer, Laurent, additional, Kim, Charlie, additional, and Cimermancic, Peter, additional

Published
2023
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7. Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies—Current Status and Next Steps

Author

Kartasalo, Kimmo, primary, Bulten, Wouter, additional, Delahunt, Brett, additional, Chen, Po-Hsuan Cameron, additional, Pinckaers, Hans, additional, Olsson, Henrik, additional, Ji, Xiaoyi, additional, Mulliqi, Nita, additional, Samaratunga, Hemamali, additional, Tsuzuki, Toyonori, additional, Lindberg, Johan, additional, Rantalainen, Mattias, additional, Wählby, Carolina, additional, Litjens, Geert, additional, Ruusuvuori, Pekka, additional, Egevad, Lars, additional, and Eklund, Martin, additional

Published
2021
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8. Artificial Intelligence for Diagnosis and Gleason Grading of Prostate Cancer in Biopsies-Current Status and Next Steps

Author

Kartasalo, Kimmo, Bulten, Wouter, Delahunt, Brett, Chen, Po-Hsuan Cameron, Pinckaers, Hans, Olsson, Henrik, Ji, Xiaoyi, Mulliqi, Nita, Samaratunga, Hemamali, Tsuzuki, Toyonori, Lindberg, Johan, Rantalainen, Mattias, Wählby, Carolina, Litjens, Geert, Ruusuvuori, Pekka, Egevad, Lars, Eklund, Martin, Kartasalo, Kimmo, Bulten, Wouter, Delahunt, Brett, Chen, Po-Hsuan Cameron, Pinckaers, Hans, Olsson, Henrik, Ji, Xiaoyi, Mulliqi, Nita, Samaratunga, Hemamali, Tsuzuki, Toyonori, Lindberg, Johan, Rantalainen, Mattias, Wählby, Carolina, Litjens, Geert, Ruusuvuori, Pekka, Egevad, Lars, and Eklund, Martin

Abstract

Diagnosis and Gleason grading of prostate cancer in biopsies are critical for the clinical management of men with prostate cancer. Despite this, the high grading variability among pathologists leads to the potential for under-and overtreatment. Artificial intelligence (AI) systems have shown promise in assisting pathologists to perform Gleason grading, which could help address this problem. In this mini-review, we highlight studies reporting on the development of AI systems for cancer detection and Gleason grading, and discuss the progress needed for widespread clinical implementation, as well as anticipated future developments. Patient summary: This mini-review summarizes the evidence relating to the validation of artificial intelligence (AI)-assisted cancer detection and Gleason grading of prostate cancer in biopsies, and highlights the remaining steps required prior to its widespread clinical implementation. We found that, although there is strong evidence to show that AI is able to perform Gleason grading on par with experienced uropathologists, more work is needed to ensure the accuracy of results from AI systems in diverse settings across different patient populations, digitization platforms, and pathology laboratories.

Published
2021
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