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Artificial intelligence-based incident analysis and learning system to enhance patient safety and improve treatment quality – npj Digital Medicine

Data availability

Requests for raw and analyzed data will undergo internal review by MSKCC to assess whether they are subject to intellectual property rights or confidentiality restrictions. Any data deemed shareable will be provided under a material transfer agreement for non-commercial research purposes.Requests for programming code, fine-tuned models, and related materials will undergo internal review by MSKCC to assess whether they are subject to intellectual property rights or confidentiality restrictions. Any materials deemed shareable will be provided under a material transfer agreement for non-commercial research purposes.

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Acknowledgements

This work was funded in part by the MSKCC Support Grant P30 CA008748. We acknowledge the support of the High-Performance Computing Group in the Department of Digital Informatics & Technology Solutions at MSKCC for providing the computing infrastructure and resources necessary for this project. We also extend our gratitude to Esther Rulnick from the Division of Quality and Safety at MSKCC for their assistance in extracting incidents from the RISQ database.

Author information

Authors and Affiliations

  1. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Abbas J. Jinia, Katherine Chapman, Shi Liu, Cesar Della Biancia, Elizabeth Hipp, Eric Lin, Anyi Li & Jean M. Moran

  2. Division of Quality and Safety, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Robin Moulder

  3. Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    Dhwani Parikh, Jason Cordero, Caralaina Pistone & Mary Gil

  4. Department of Nursing, Memorial Sloan Kettering Cancer Center, New York, NY, USA

    John Ford

Authors

  1. Abbas J. Jinia
  2. Katherine Chapman
  3. Shi Liu
  4. Cesar Della Biancia
  5. Elizabeth Hipp
  6. Eric Lin
  7. Robin Moulder
  8. Dhwani Parikh
  9. Jason Cordero
  10. Caralaina Pistone
  11. Mary Gil
  12. John Ford
  13. Anyi Li
  14. Jean M. Moran

Contributions

A.J.J., K.C., A.L., and J.M.M. conceptualized the study, directly accessed, and verified the data, conducted the formal analysis and methodology, administered the project, created the software, visualized the data, wrote the original draft of the manuscript, and reviewed and edited the manuscript. S.L., C.D.B., E.H., E.L., R.M., D.P., J.C., C.P., M.G., and J.F. contributed to data curation, methodology, and review and editing of the manuscript. All authors had full access to all data in the study and had final responsibility for the decision to submit for publication.

Corresponding authors

Correspondence to Abbas J. Jinia, Anyi Li or Jean M. Moran.

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Competing interests

The authors declare no competing interests related to this work. EH declares the following disclosures: Volunteering position on the executive board of the Knickerbocker Chapter NSDAR. J.M.M. declares the following disclosures: Grants from Varian received during my time at the University of Michigan. Honoraria paid by the Connecticut Area Medical Physics Society. Patient issued for Combined radiation acoustics and ultrasound for radiotherapy guidance and cancer targeting. Co-founder and board member at Prexient, Inc. Chair of Work Group on Science Council EDI at the American Association of Physicists in Medicine. Chair of Work Group on Report Writing at the American Association of Physicists in Medicine. Vice Chair of Research Committee at the Radiation Oncology Institute. Co-Chair at the Radiation Oncology Institute Radiation Oncology Safety Stakeholders Initiative. FuseOncology (Copyright), which has been licensed by my previous institution (University of Michigan) for which I made a contribution. Consultant (unfunded) to the Michigan Radiation Oncology Quality Consortium.

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Jinia, A.J., Chapman, K., Liu, S. et al. Artificial intelligence-based incident analysis and learning system to enhance patient safety and improve treatment quality. npj Digit. Med. (2026). https://doi.org/10.1038/s41746-026-02390-2

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  • DOI: https://doi.org/10.1038/s41746-026-02390-2

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