PhilArchive
open access
How Clinical AI Underserves Transgender Patients: The Transgender Data Gap, Statistical Misgendering, and Healthcare Avoidance and Delay
I identify three mutually reinforcing issues that cause clinical AI to underserve transgender patients. I call these issues the transgender data gap, statistical misgendering, and healthcare avoidance and delay (HAD). I am the first scholar to discuss these issues within the context of clinical AI. I conclude that transgender patients deserve to know when clinical AI underserves them.
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- The relationship between autism and gender dysphoria, and their co-occurrence with transgender identity: research conditions and implications.#265198
- The Copenhagen Gender Identity Cohort#1008133
- Psychotherapy Trial With Transgender Clients#1452789
- The Notion of Gender in Psychiatry: A Focus on DSM-5#116618
- Being Trans, Being Loved: Clashing Identities and the Limits of Love#727161
Record · ID 1506729
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive