From pixels to patient care: deep learning-enabled pathomics signature offers precise outcome predictions for immunotherapy in esophageal squamous cell cancer.

"Declarations Ethics approval and consent to participateAll procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (Ethics Committee of Shandong Cancer Hospital) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was waived due to the retrospective study. Consent for publicationAll authors agree to the publication of the article. Competing interestsThe authors declare that they have no conflict of interest. Competing interests The authors declare that they have no conflict of interest."

"Funding This research was supported by National Natural Science Foundation of China (Grant number 82172865 and 82203198), Natural Science Foundation of Shandong Province, (Grant number ZR2022QH023 and ZR2021LZL009), The Key Research, Development Program of Shandong Major Science & Technology Innovation Project (Grant number 2021SFGC0501), Start-up fund of Shandong Cancer Hospital (Grant number 2020-B14), Clinical Research Special Fund of Wu Jieping Medical Foundation (Grant number 320.6750.2021-02-51 and 320.6750.2021-17-13)."