Public articles linked to the same research event.
Journal of pediatric hematology/oncology This feasibility study fed deidentified treatment summaries into OpenAI GPT-4o with structured prompts to draft long-term follow-up recommendations for childhood cancer and HSCT survivors, then compared them with clinician-generated recommendations based on institutional standards and Children's Oncology Group Long-Term Follow-Up Guidelines (version 5) in an independent validation cohort of 40 survivors, finding 467 AI-generated versus 446 clinician-generated items, with 385 of 446 clinician recommendations (86.3%) also identified by AI and 385 of 467 AI recommendations (82.4%) also present in clinician plans, while most discordant recommendations involved radiation-related exposures and survivorship scenarios requiring nuanced clinical interpretation.
This feasibility study fed deidentified treatment summaries into OpenAI GPT-4o with structured prompts to draft long-term follow-up recommendations for childhood cancer and HSCT survivors, then compared them with clinician-generated recommendations based on institutional standards and Children's Oncology Group Long-Term Follow-Up Guidelines (version 5) in an independent validation cohort of 40 survivors, finding 467 AI-generated versus 446 clinician-generated items, with 385 of 446 clinician recommendations (86.3%) also identified by AI and 385 of 467 AI recommendations (82.4%) also present in clinician plans, while most discordant recommendations involved radiation-related exposures and survivorship scenarios requiring nuanced clinical interpretation.
This feasibility study fed deidentified treatment summaries into OpenAI GPT-4o with structured prompts to draft long-term follow-up recommendations for childhood cancer and HSCT survivors, then compared them with clinician-generated recommendations based on institutional standards and Children's Oncology Group Long-Term Follow-Up Guidelines (version 5) in an independent validation cohort of 40 survivors, finding 467 AI-generated versus 446 clinician-generated items, with 385 of 446 clinician recommendations (86.3%) also identified by AI and 385 of 467 AI recommendations (82.4%) also present in clinician plans, while most discordant recommendations involved radiation-related exposures and survivorship scenarios requiring nuanced clinical interpretation.
This feasibility study fed deidentified treatment summaries into OpenAI GPT-4o with structured prompts to draft long-term follow-up recommendations for childhood cancer and HSCT survivors, then compared them with clinician-generated recommendations based on institutional standards and Children's Oncology Group Long-Term Follow-Up Guidelines (version 5) in an independent validation cohort of 40 survivors, finding 467 AI-generated versus 446 clinician-generated items, with 385 of 446 clinician recommendations (86.3%) also identified by AI and 385 of 467 AI recommendations (82.4%) also present in clinician plans, while most discordant recommendations involved radiation-related exposures and survivorship scenarios requiring nuanced clinical interpretation.