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RBMO Study Led by Belén Lledó Compared General AI Chatbots on IVF/PGT Questions – Fertiligent AI
Belén Lledo/institutobernabeu.com
Oct 4, 2025, 07:44

RBMO Study Led by Belén Lledó Compared General AI Chatbots on IVF/PGT Questions – Fertiligent AI

Fertiligent AI shared a post on LinkedIn about a paper by Belén Lledo et al. published in RBMO:

“A new RBMO study compared general AI chatbots on IVF/PGT questions (ChatGPT-3.5, Gemini 1.5, and Llama-2). Useful—but the takeaway isn’t ‘AI is ready out-of-the-box.’ It’s that generalist LLMs struggle on domain nuance—and why a fertility-trained LLM is the right path forward.

Why a Fertility-trained LLM outperforms generalists:

  1. Guideline-true by design. Tuned to ASRM/ESHRE guidance and updated clinic SOPs; answers reflect current practice, not internet averages. (RBMO found quality varied with complexity.) (ScienceDirect)
  2. Lower hallucinations, higher citations. Retrieval from curated fertility corpora (patient leaflets, consent forms, lab standards) with inline sources for clinical review.
  3. Context that actually matters. Embryology, PGT-A/PGT-M nuance, ovarian reserve, AMA counseling, medication protocols—handled with structured reasoning, not generic medical talk.
  4. Safety rails and scope control. Built-in disclaimers, triage triggers, and handoff to clinicians when questions cross into diagnosis.
  5. Clinic-grade privacy. Architected for PHI handling and audit trails; responses are logged and reviewable.
  6. Localization for real patients. Multilingual outputs, readability tuning, and culturally sensitive counseling for high-anxiety moments.
  7. Continuous updates. Domain models are retrained/augmented as guidance changes—avoiding the ‘snapshot’ problem of frozen general models.

Note: the RBMO study used older baselines (ChatGPT-3.5 and Gemini 1.5). Newer general models have improved—but specialization still wins when accuracy, guardrails, and citations are non-negotiable in patient education and clinic workflows.
At Fertiligent AI, we’re building exactly this: a fertility-trained LLM with verified sources, clinic-first safety, and seamless clinician handoff—so teams can scale guidance without compromising care.

Sources: RBMO comparative evaluation of chatbots for PGT (uses ChatGPT-3.5, Gemini 1.5, Llama-2); RBMO study on reliability of AI counseling for fertility patients.”

Title: Assessing the performance of generative AI chatbots in preimplantation genetic testing: a comparative study of expert evaluations

Authors: Belén Lledo, Paola Carbone, Jose A. Ortiz, Ruth Morales, Adoración Rodríguez-Arnedo, Leyre Herrero, Elisa Alvarez, Jorge Ten, Lydia Luque, Juan C. Castillo, Jordi Suñol, Annalisa Racca, Andrea Bernabeu

Belén Lledó

Adoración Rodríguez-Arnedo Andrea Bernabeu Annalisa Racca ASRM Belén Lledo ChatGPT Elisa Alvarez ESHRE Fertiligent AI Fertility Fertility News IVF Jordi Suñol Jorge Ten Jose A. Ortiz Juan C. Castillo Leyre Herrero Lydia Luque Paola Carbone RBMO Ruth Morales
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