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Christopher Chung on Muck Rack

Christopher Chung

Verified
Santa Rosa
As seen in: The Press Democrat, Medium, Wiley Online Library, MDPI, JAMA (The Journal of the American Medical Association), American Academy of Ophthalmology, Northeast Mississippi Daily Journal, Florence Morning News, Citrus County Chronicle, Journal of The American Academy of Dermatology (JAAD), UroToday and
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Articles

Comparison of Marketing and Composition Features Between Popular Tinted and Non-Tinted Sunscreens in the United States

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By Jessie Nelson, Judy Hamad, Christopher Chung Verified
| Wiley Online Library Verified
Data Availability Statement The data that support the findings of this study are available from the corresponding author upon reasonable request. References 1, , , , and , “Photoprotection Beyond Ultraviolet Radiation: A Review of Tinted Sunscreens,” Journal of the American Academy of Dermatology 84 (2021): 1393–1397.
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Reply to: Acrylate Copolymers/Crosspolymers in Sunscreens: Minimally Allergenic, Without Evidence of Need for Avoidance by (Meth)acrylate-Sensitized Individuals

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By Emily Levin, Christopher Chung Verified, Katia Hermes
| Wiley Online Library Verified
Opens in a new window Opens an external website Opens an external website in a new window This website utilizes technologies such as cookies to enable essential site functionality, as well as for analytics, personalization, and targeted advertising. To learn more, view the following link: Privacy Policy , , , , and . 2026.
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Deep learning classification of significant prostate cancer on MRI: a systematic review and meta-analysis.

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By Christopher Chung Verified, Julia L. Michalak, Yossef Rubinov
| UroToday Verified
Deep learning (DL) image analysis of prostate MRI can be integrated into the prostate cancer diagnostic pathway to improve biopsy decision making, reduce radiologist interpretation time, and decrease inter-reader variability. In this paper, we systematically review the current literature on DL classification of clinically significant prostate cancer detected on magnetic resonance imaging and perform a meta-analysis of reported external validation performance metrics.
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