Our Publications

  1. Nouman, H., & Alfandari, R. (2020). Identifying children suspected for maltreatment: The assessment process taken by healthcare professionals working in community healthcare services. Children and Youth Services Review, 113, 104964. https://doi.org/10.1016/j.childyouth.2020.104964

  2. Nouman, H., Alfandari, R., Enosh, G., Dolev, L., & Daskal-Weichhendler, H. (2020). Mandatory reporting between legal requirements and personal interpretations: Community healthcare professionals’ reporting of child maltreatment. Child Abuse & Neglect, 101, 104261. https://doi.org/10.1016/j.chiabu.2019.104261

  3. Enosh, G., Alfandari, R., Nouman, H., Dolev, L., & Daskal-Weichhendler, H. (2021). Assessing, consulting, reporting: Heuristics in professional decision-making regarding suspected child maltreatment in community healthcare services. Child Maltreatment, 26(3), 291–301. https://doi.org/10.1177/10775595211006243

  4. Alfandari, R., & Taylor, B. J. (2023). Processes of multi-professional child protection decision making in hospital settings: Systematic narrative review. Trauma, Violence, & Abuse, 24(1), 295–312. https://doi.org/10.1177/15248380211060271

  5. Cowley, E. L., Nurmatov, U. B., Taylor, B. J., & Gilbert, R. E. (2025). Defining child maltreatment for research and surveillance: An international, multi-sectoral, Delphi consensus study in 34 countries. The Lancet Regional Health – Europe, 50, 101196. https://doi.org/10.1016/j.lanepe.2024.101196

  6. Nurmatov, U. B., Cowley, E. L., Taylor, B. J., & Gilbert, R. E. (2023). Consensus building on definitions and types of child maltreatment to improve recording and surveillance in Europe: Protocol for a multi-sectoral, European electronic Delphi study. BMJ Open, 13(9), e076517. https://doi.org/10.1136/bmjopen-2023-076517

  7. Alfandari, R., Przeperski, J., & Taylor, B. J. (2023). Interprofessional decision making. In B. J. Taylor, M. Beld, & J. Przeperski (Eds.), The SAGE handbook of decision making, assessment and risk in social work (pp. 176–184). SAGE Publications.

  8. Barak-Corren, Y., Fine, A. M., & Reis, B. Y. (2017). Early prediction model of patient hospitalization from the pediatric emergency department. Pediatrics, 139(5), e20162785. https://doi.org/10.1542/peds.2016-2785

  9. Barak-Corren, Y., Castro, V. M., Javitt, S., Hoffnagle, A. G., Dai, Y., Perlis, R. H., … & Smoller, J. W. (2020). Validation of an electronic health record-based suicide risk prediction modeling approach across multiple healthcare systems. JAMA Network Open, 3(3), e201262. https://doi.org/10.1001/jamanetworkopen.2020.1262

  10. Barak-Corren, Y., Dai, Y., Segal, G., Shalit, U., & Reis, B. Y. (2021). Prediction of patient disposition: Comparison of computer and human approaches and a proposed synthesis. Journal of the American Medical Informatics Association, 28(8), 1736–1745. https://doi.org/10.1093/jamia/ocab089

  11. Barak-Corren, Y., Dai, Y., Perlis, R. H., & Reis, B. Y. (2021). Prediction across healthcare settings: A case study in predicting emergency department disposition. NPJ Digital Medicine, 4, 169. https://doi.org/10.1038/s41746-021-00547-w

  12. Nock, M. K., Borges, G., Bromet, E. J., Kessler, R. C., Lee, S., & Millman, Z. B. (2022). Prediction of suicide attempts using clinician assessment, patient self-report, and electronic health records. JAMA Network Open, 5(1), e2144373. https://doi.org/10.1001/jamanetworkopen.2021.44373

  13. Bayramli, I., Dai, Y., Harel, N., Barak-Corren, Y., & Reis, B. Y. (2022). Predictive structured–unstructured interactions in EHR models: A case study of suicide prediction. NPJ Digital Medicine, 5, 15. https://doi.org/10.1038/s41746-022-00574-z

  14. Barak-Corren, Y., Dai, Y., Harel, N., Segal, G., & Reis, B. Y. (2023). The value of parental medical records for the prediction of diabetes and cardiovascular disease: A novel method for generating and incorporating family histories. Journal of the American Medical Informatics Association, 30(9), 1915–1924. https://doi.org/10.1093/jamia/ocad127

  15. Barak-Corren, Y., Zohar, Y., Harel, N., & Reis, B. Y. (2024). Harnessing the power of generative AI for clinical summaries: Perspectives from emergency physicians. Annals of Emergency Medicine, 84(2), 128–138. https://doi.org/10.1016/j.annemergmed.2024.03.008