Tingting Zhu

Jul 29, 2024 | nature.com | Tingting Zhu

AbstractThe decision to accept a deceased donor organ offer for transplant, or wait for something potentially better in the future, can be challenging. Clinical decision support tools predicting transplant outcomes are lacking. This project uses interpretable methods to predict both graft failure and patient death using data from previously accepted kidney transplant offers.

Jul 12, 2024 | journals.ametsoc.org | Tingting Zhu |Jin-Yi Yu

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Apr 11, 2024 | journals.ametsoc.org | Tingting Zhu |Jin-Yi Yu

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Jan 1, 2024 | jitc.bmj.com | Yao Wang |Tingting Zhu |Qi Shi |Guanghui Zhu

Challenges of LN removal and retentionParadoxically, TDLNs serve as an immune barrier and a common site for tumor metastasis. LNs are the primary sites of antitumor immunity and play an important role in the immunotherapy response. Overly aggressive removal of LNs may impair the antitumor immune function. Hence, it should be determined whether to remove them before assessing their clinical value.

Oct 18, 2023 | nature.com | Tingting Zhu

Clinical prediction models follow a standard development pipeline: model development and internal validation; external validation; and clinical impact studies. External validation studies should be followed by real-world studies evaluating the deployed models’ usefulness1. However, the latter are rarely performed. Instead, external validation ends up being the de facto test for evaluating machine learning (ML) models before deployment.