{
  "id": "AIBD-0038",
  "title": "ChatGPT proposes ALMS1 and a 44-year-old nephrology patient receives a confirmed Alström syndrome diagnosis within two business days",
  "summary": "ChatGPT proposed ALMS1 for a 44-year-old with lifelong deafness, blindness, cardiomyopathy and CKD; Alström syndrome confirmed in two days.",
  "date_observed": "2023-12-08",
  "date_basis": "unassessed",
  "date_precision": "unassessed",
  "benefit_status": null,
  "source_collection": null,
  "source_entry": null,
  "account": "Haller and colleagues at the Medical University of Vienna described a 44-year-old man in a letter published in Clinical Kidney Journal on 8 December 2023. He “presented to our nephrological institution with a complex medical history”. It included “progressive hearing loss and amaurosis since shortly after birth”, dilated cardiomyopathy, chronic kidney disease and cirrhosis. The physicians “used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)”. A geneticist “within just two business days confirmed that the patient actually possesses two distinct mutations in ALMS1”. Further tests then characterized hypogonadism and metabolic findings consistent with the syndrome. The consultation date is not stated.",
  "category": "benefit created",
  "unexpected": true,
  "purpose": "ChatGPT is a general-purpose conversational assistant. Generating candidate genes for a rare multisystem disease is not a function it was built for. This benefit was not its designed purpose.",
  "system": "ChatGPT",
  "model_version": "ChatGPT (Sep 14 version), as cited by the authors",
  "developer": "OpenAI",
  "deployer": "Medical University of Vienna, Division of Nephrology and Dialysis",
  "location": "Vienna, Austria",
  "domain": "Healthcare / nephrology and clinical genetics",
  "segment": "Rare disease diagnosis",
  "benefit_type": "Improved Physical Health",
  "taxonomy_note": null,
  "registry_ids": {},
  "ratings": [
    {
      "group": "personal",
      "depth": 2,
      "reason": "A unifying genetic diagnosis at 44 for symptoms present since infancy, enabling targeted follow-up. No curative treatment is reported, so material rather than life-saving."
    }
  ],
  "ai_role": {
    "status": "assessed",
    "statement": "ChatGPT proposed ALMS1 among candidate genes from a physician-written history. The clinicians framed the query and ordered targeted genetic testing, which made the diagnosis."
  },
  "evidence": [
    {
      "kind": "case report",
      "citation": "Haller F, Autherith M, Lehner R, Schmidt A, Sunder-Plassmann G (2023). Utilizing artificial intelligence and next-generation sequencing to facilitate the diagnosis of rare diseases. Clinical Kidney Journal (letter; PMC10783252).",
      "title": "Utilizing artificial intelligence and next-generation sequencing to facilitate the diagnosis of rare diseases",
      "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/",
      "date": "2023-12-08",
      "written_by": "deployer",
      "quote": "we used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)"
    }
  ],
  "replication": {
    "produced_by": [
      "A structured multisystem history entered by physicians",
      "Rapid access to targeted genetic testing",
      "Clinicians willing to test an AI-generated hypothesis"
    ],
    "must_hold": [
      "The AI's candidate list includes the true gene",
      "Confirmatory sequencing is available"
    ],
    "echoes": []
  },
  "paired_incident": {
    "database": "AI Incident Database",
    "identifier": "1281",
    "title": "Alleged Harmful Health Outcomes Following Reported Use of Purported ChatGPT-Generated Medical Advice in Hyderabad",
    "url": "https://incidentdatabase.ai/cite/1281",
    "severity": null,
    "group": "personal",
    "basis": "Same system and specialty: ChatGPT in nephrology; it proposed ALMS1 for a Vienna kidney patient, while in Hyderabad its advice led a kidney-transplant recipient to stop medication and suffer graft failure."
  },
  "headline": "ChatGPT proposes ALMS1; Alström confirmed in two business days",
  "metric": "Alström syndrome confirmed in two days",
  "comparator": {
    "against": "untargeted analysis of the sequenced exome",
    "before": "the genetic analysis of the sequenced exome can take up to months",
    "after": "the suspected diagnosis of AS was confirmed within just two business days",
    "basis": "assumed",
    "quote": "After providing the geneticist with the information generated from ChatGPT, the suspected diagnosis of AS was confirmed within just two business days.",
    "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/"
  },
  "later": {
    "status": "unknown",
    "date": null,
    "note": "No later development found.",
    "quote": null,
    "url": null
  },
  "value": null,
  "developer_country": "United States",
  "deployer_country": "Austria",
  "unrated_because": null,
  "brief_notes": null,
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    {
      "date": "2026-10-20",
      "change": "Record drafted from the cited sources.",
      "source": null,
      "editor": "AIBD"
    },
    {
      "date": "2026-10-20",
      "change": "Paired with AI Incident Database incident 1281 (high confidence); severity not given by the source.",
      "source": "https://incidentdatabase.ai/cite/1281",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Added what the benefit is measured against from the cited sources.",
      "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
      "source": "https://trustible.ai/post/a-framework-for-measuring-the-benefits-of-ai/",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Country of the deployer added from the organization's own site or a registry.",
      "source": "https://en.wikipedia.org/wiki/Medical_University_of_Vienna",
      "editor": "AIBD"
    },
    {
      "date": "2026-10-21",
      "change": "Country of the developer added from the organization's own site or a registry.",
      "source": "https://en.wikipedia.org/wiki/OpenAI",
      "editor": "AIBD"
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    {
      "date": "2026-10-21",
      "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
      "source": null,
      "editor": "AIBD"
    }
  ],
  "confidence": "claimed",
  "shade": "low",
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          "answer": "Alström syndrome confirmed in two days",
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        "state": "not_assessed",
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        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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      "outcomes[].id": {
        "state": "not_assessed",
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      "outcomes[].stakeholder_group": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "ratings": [
              {
                "group": "personal",
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                "reason": "A unifying genetic diagnosis at 44 for symptoms present since infancy, enabling targeted follow-up. No curative treatment is reported, so material rather than life-saving."
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            ]
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          "source_refs": []
        },
        "review_state": "record_mapped",
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      },
      "outcomes[].status": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "outcomes[].tradeoffs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
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        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "unexpected": true,
            "purpose": "ChatGPT is a general-purpose conversational assistant. Generating candidate genes for a rare multisystem disease is not a function it was built for. This benefit was not its designed purpose."
          }
        },
        "provenance": {
          "kind": "legacy_record",
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            "purpose"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "places[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
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            "location": "Vienna, Austria",
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            "deployer_country": "Austria"
          }
        },
        "provenance": {
          "kind": "legacy_record",
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            "deployer_country"
          ],
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        },
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      },
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          "kind": "record_fields",
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            "purpose": "ChatGPT is a general-purpose conversational assistant. Generating candidate genes for a rare multisystem disease is not a function it was built for. This benefit was not its designed purpose."
          }
        },
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          "kind": "legacy_record",
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          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
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      "record_dates": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
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                "date": "2026-10-20",
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                "editor": "AIBD"
              },
              {
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              },
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                "date": "2026-10-21",
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              },
              {
                "date": "2026-10-21",
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                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the deployer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/Medical_University_of_Vienna",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/OpenAI",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
                "editor": "AIBD"
              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "replication.attempts[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "replication.conditions": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "replication": {
              "produced_by": [
                "A structured multisystem history entered by physicians",
                "Rapid access to targeted genetic testing",
                "Clinicians willing to test an AI-generated hypothesis"
              ],
              "must_hold": [
                "The AI's candidate list includes the true gene",
                "Confirmatory sequencing is available"
              ],
              "echoes": []
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "replication"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "revision_history[]": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "revisions": [
              {
                "date": "2026-10-20",
                "change": "Record drafted from the cited sources.",
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              },
              {
                "date": "2026-10-20",
                "change": "Paired with AI Incident Database incident 1281 (high confidence); severity not given by the source.",
                "source": "https://incidentdatabase.ai/cite/1281",
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              },
              {
                "date": "2026-10-21",
                "change": "Added what the benefit is measured against from the cited sources.",
                "source": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/",
                "editor": "AIBD"
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              {
                "date": "2026-10-21",
                "change": "Benefit type set to Improved Physical Health under Trustible's full taxonomy of 23 types; it was Improved Knowledge Discovery among the six first used.",
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                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the deployer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/Medical_University_of_Vienna",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Country of the developer added from the organization's own site or a registry.",
                "source": "https://en.wikipedia.org/wiki/OpenAI",
                "editor": "AIBD"
              },
              {
                "date": "2026-10-21",
                "change": "Prose pass: a rating reason, account, purpose, the replication conditions, the system's part rewritten in shorter sentences with abbreviations expanded; facts, figures and quotations unchanged.",
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              }
            ]
          }
        },
        "provenance": {
          "kind": "legacy_record",
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sector": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "domain": "Healthcare / nephrology and clinical genetics",
            "segment": "Rare disease diagnosis"
          }
        },
        "provenance": {
          "kind": "legacy_record",
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          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "sources[].access_version": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "sources[].citation_locator": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "evidence": [
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                "title": "Utilizing artificial intelligence and next-generation sequencing to facilitate the diagnosis of rare diseases",
                "url": "https://pmc.ncbi.nlm.nih.gov/articles/PMC10783252/",
                "date": "2023-12-08",
                "written_by": "deployer",
                "quote": "we used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)"
              }
            ]
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        },
        "provenance": {
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        "review_state": "record_mapped",
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      "sources[].id": {
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          "record_fields": [],
          "source_refs": []
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        "review_state": "record_mapped",
        "coverage": "complete"
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      "sources[].language": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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      "sources[].relationship": {
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        "value": {
          "kind": "record_fields",
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            "evidence": [
              {
                "kind": "case report",
                "citation": "Haller F, Autherith M, Lehner R, Schmidt A, Sunder-Plassmann G (2023). Utilizing artificial intelligence and next-generation sequencing to facilitate the diagnosis of rare diseases. Clinical Kidney Journal (letter; PMC10783252).",
                "title": "Utilizing artificial intelligence and next-generation sequencing to facilitate the diagnosis of rare diseases",
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                "date": "2023-12-08",
                "written_by": "deployer",
                "quote": "we used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)"
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        "provenance": {
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        "review_state": "record_mapped",
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        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
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      "strategic_assessments[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial",
        "family": "strategic assessments"
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      "summary": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
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            "account": "Haller and colleagues at the Medical University of Vienna described a 44-year-old man in a letter published in Clinical Kidney Journal on 8 December 2023. He “presented to our nephrological institution with a complex medical history”. It included “progressive hearing loss and amaurosis since shortly after birth”, dilated cardiomyopathy, chronic kidney disease and cirrhosis. The physicians “used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)”. A geneticist “within just two business days confirmed that the patient actually possesses two distinct mutations in ALMS1”. Further tests then characterized hypogonadism and metabolic findings consistent with the syndrome. The consultation date is not stated."
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "summary",
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].autonomy_permissions": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].component_role": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "ChatGPT suggested candidate genes from a physician’s written clinical history."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Restated the mechanical task already described in the existing system and AI-role fields. No new source review is claimed.",
          "record_fields": [
            "system",
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].deployment_configuration": {
        "state": "value_present",
        "value": {
          "kind": "text",
          "text": "The authors identified the ChatGPT interface as the September 14 version."
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Separated the model, software, hardware, or operation already described in the existing record. No new source review is claimed.",
          "record_fields": [
            "model_version",
            "system",
            "ai_role"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].inputs_outputs": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_name": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "systems[].model_version": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "model_version": "ChatGPT (Sep 14 version), as cited by the authors"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "model_version"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial",
        "display": {
          "answer": "Exact release not established.",
          "editor_note": ""
        }
      },
      "systems[].product_name": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "system": "ChatGPT"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
            "system"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "systems[].provider": {
        "state": "value_present",
        "value": {
          "kind": "structured",
          "data": {
            "application_developer": "OpenAI"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Mapped from the existing case description without a new external source review.",
          "record_fields": [
            "developer"
          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      },
      "taxonomy_crosswalks[]": {
        "state": "not_assessed",
        "review_state": "not_assessed",
        "coverage": "partial"
      },
      "title": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "title": "ChatGPT proposes ALMS1 and a 44-year-old nephrology patient receives a confirmed Alström syndrome diagnosis within two business days",
            "headline": "ChatGPT proposes ALMS1; Alström confirmed in two business days"
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
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      "version": {
        "state": "value_present",
        "value": {
          "kind": "identifiers",
          "identifiers": [
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          "role": "SHA-256 of normalized original case data"
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        "provenance": {
          "kind": "curatorial",
          "basis": "Deterministic content version assigned by the local migration.",
          "record_fields": [],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "complete"
      },
      "workflow": {
        "state": "value_present",
        "value": {
          "kind": "record_fields",
          "fields": {
            "account": "Haller and colleagues at the Medical University of Vienna described a 44-year-old man in a letter published in Clinical Kidney Journal on 8 December 2023. He “presented to our nephrological institution with a complex medical history”. It included “progressive hearing loss and amaurosis since shortly after birth”, dilated cardiomyopathy, chronic kidney disease and cirrhosis. The physicians “used ChatGPT to obtain potential genetic targets based on the patient's medical history. One such target was the Alström Syndrome 1 gene (ALMS1)”. A geneticist “within just two business days confirmed that the patient actually possesses two distinct mutations in ALMS1”. Further tests then characterized hypogonadism and metabolic findings consistent with the syndrome. The consultation date is not stated.",
            "replication": {
              "produced_by": [
                "A structured multisystem history entered by physicians",
                "Rapid access to targeted genetic testing",
                "Clinicians willing to test an AI-generated hypothesis"
              ],
              "must_hold": [
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              ],
              "echoes": []
            }
          }
        },
        "provenance": {
          "kind": "legacy_record",
          "basis": "Preserved from the existing AIBD record; external sources were not rechecked.",
          "record_fields": [
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          ],
          "source_refs": []
        },
        "review_state": "record_mapped",
        "coverage": "partial"
      }
    },
    "summary": {
      "total": 91,
      "addressed": 91,
      "known": 33,
      "reviewed": 0,
      "record_mapped": 33,
      "not_assessed": 58,
      "complete": false,
      "by_state": {
        "value_present": 33,
        "not_reported": 0,
        "unresolved": 0,
        "not_assessed": 58,
        "not_applicable": 0,
        "withheld": 0,
        "source_unavailable": 0
      }
    }
  }
}