Hosted by The JC School of Public Health and Primary Care (JCSPHPC) of The Chinese University of Hong Kong (CUHK), the “SPHPC Thematic Research Seminar Series –Find the Culprit in the Crowd: Deep Learning Models for Cancer Subtyping” will take place on 14 March, 2025 (Friday). In this talk, Prof. Xin Wang, Associate Professor of the Department of Surgery, CUHK, will introduce a deep learning framework based on transcriptomic profiles. It is a platform independent, robust to missing data, and can be used for single sample prediction. Light refreshments will be served.
Please refer to the details below:
Date: | 14 March, 2025 (Friday) |
Time: | 12:30pm – 1:30pm |
Venue: | Seminar Room 3, 1/F, School of Public Health Building, Prince of Wales Hospital, Shatin |
Mode: | In-person |
Topic: | Transcriptomic, histopathological and radiological deep learning models for cancer subtype classification |
Speaker: | Prof. Xin Wang Associate Professor, Department of Surgery, Faculty of Medicine, The Chinese University of Hong Kong |
Moderator: | Prof. Maggie Wang Associate Professor, JC School of Public Health and Primary Care, Faculty of Medicine, the Chinese University of Hong Kong |
Presentation Abstract
It is now clear that major human cancers are heterogeneous diseases, which hamper the selection of patients for optimized clinical management and treatment. To dissect the complex cancer heterogeneity, molecular subtyping has been widely adopted as an effective strategy in the last couple of decades. Despite the insights into cancer biology, the conventional cancer subtyping studies were mostly based on conventional machine learning methods applied to transcriptomics data, which lack cross-platform robustness and are not suitable for clinical translation. In this talk, Prof. Wang will first introduce a deep learning framework based on transcriptomic profiles, which is platform independent, robust to missing data, and can be used for single sample prediction. To facilitate clinical implementation, Prof. Wang will next introduce our recent works on deep learning models for cancer subtyping based on histopathological images and radiological scans. These medical imaging resources are widely available in the clinic, hence more suitable for the translation of cancer subtyping into real clinical practice to advance precision oncology.
About the Speaker
Prof. Xin Wang obtained his PhD in 2014 from University of Cambridge Department of Oncology and Cancer Research UK Cambridge Institute. From 2013 to 2015, Prof. Wang did his postdoctoral research at the Department of Biomedical Informatics, Harvard Medical School. He is currently an Associate Professor at the Department of Surgery, The Chinese University of Hong Kong, directing the Division of Biomedical Informatics and MPhil-PhD Programme in Translational Genomics. He is also leading the Laboratory of Translational Bioinformatics at LI Ka Shing Institute of Health Sciences as a Principal Investigator. Prof. Wang’s group has been focusing on mechanistic and translational research in major human cancers by developing novel methods integrating bioinformatics, systems biology, machine learning and artificial intelligence. Prof. Wang published > 90 peer-reviewed papers in leading journals, and his work is currently supported by significant research funds from Hong Kong, Shenzhen City and Guangdong Province in China.
About the Moderator
Dr. Maggie Wang obtained Bachelor degree (honor) in Physics (2005) from the Hong Kong University of Science and Technology (HKUST) and PhD in Statistics (2011) from the ISOM department of HKUST. She was a visiting scholar to the Columbia University (2009) and Stanford University (2016). Joint the JC School of Public Health and Primary Care (SPHPC) of the Chinese University of Hong Kong (CUHK) as a Research Assistant Professor in 2011, Dr. M Wang was appointed as Assistant Professor in 2015, and Associate Professor in 2021 (tenured). She was the elected Representative of Associate Professors in the Faculty of Medicine, CUHK.
Dr. M Wang is the Principle Investigator of projects funded by RGC-GRF, ITC, HMRF and NSFC. She was elected as the one of the six board members of the International Genetic Epidemiology Society (IGES) (2021-2023). Dr. M Wang serves as the Editor-in-Chief of Human Genetics (Springer Nature), and a Council Member of the Chinese Bioinformatics Society (preparatory) since 2019. She is the recipient of the Research Excellence Award 2022-23 and Young Researcher Award 2022 in CUHK. Dr. M Wang is awarded with the highly competitive 2023 NSFC Excellent Young Scientists Fund (HK & Macau).