Daniel Milad, M.D.

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Daniel Milad, M.D.

Daniel Milad, M.D.

@DanielMiladMD

Ophthalmology Chief Resident Physician @UMontreal

Montreal, Quebec, Canada Katılım Kasım 2022
46 Takip Edilen24 Takipçiler
Daniel Milad, M.D.
Daniel Milad, M.D.@DanielMiladMD·
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Rohan Paul@rohanpaul_ai

GPT-5 delivers near‑perfect ophthalmology answers, and the mini‑low mode gives the best accuracy per dollar. The study pits 12 GPT‑5 configurations against o1, o3, and GPT‑4o on 260 closed American Academy of Ophthalmology Basic and Clinical Science Course questions, then checks accuracy and explanation quality. Questions were answered with no examples in the prompt, and each reply had to be a single letter plus a 1‑sentence justification, so grading stayed strict and simple. GPT‑5 exposes a “reasoning effort” control, from low to high, that increases the model’s private thinking tokens before it speaks, the minimal setting underperformed and was dropped. Top result, GPT‑5‑high hit 96.5% accuracy, o3‑high scored 95.8%, o1‑high 92.7%, GPT‑4o 86.5%, while GPT‑5‑nano‑low trailed at 77.3%. Head‑to‑head strength was estimated with a Bradley‑Terry model, which turns pairwise wins into a single “skill” score, GPT‑5‑high was 1.66x stronger than o3‑high and 5.10x stronger than o1‑high on accuracy, and 1.11x stronger than o3‑high on rationale quality. Rationales were graded by an LLM judge that compared each 1‑sentence explanation to the official reference text and picked the closer one, which scales cleanly beyond small human panels. Cost mattered, plotting accuracy against mean cost per question showed a Pareto frontier from GPT‑5‑nano‑low to GPT‑5‑high, and GPT‑5‑mini‑low sat on that frontier as the best low‑cost high‑performance point, meaning nothing else was both cheaper and more accurate. Practical read, GPT‑5‑high fits settings where every point of accuracy matters, GPT‑5‑mini‑low fits budgeted scale, and GPT‑5‑medium tracks close to o3‑high on performance and cost. ---- Paper – arxiv. org/abs/2508.09956 Paper Title: "Performance of GPT-5 Frontier Models in Ophthalmology Question Answering"

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Fares Antaki
Fares Antaki@FaresAntaki·
🚨 Excited to share our new preprint benchmarking OpenAI’s GPT-5 series for ophthalmology question answering. Using the AAO BCSC dataset, we tested GPT-5 (including mini & nano) across four reasoning levels vs three older LLMs. GPT-5 with high reasoning scored an impressive 96.5%, ranking first in our LLM arena for both accuracy and justification quality. The most cost-efficient configuration was GPT-5-mini with low reasoning. We also introduce a scalable new method for evaluating long-form answers using LLM-as-a-judge autograding. 🔗 arxiv.org/abs/2508.09956 @DanielMiladMD @SumitSharmaMD @pearsekeane @YihTham
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Fares Antaki
Fares Antaki@FaresAntaki·
Great work, @dominicwllmsn, for leading our project on using AI to enhance clinical trial recruitment in geographic atrophy. The AI system can shortlist patients by looking through their OCTs for unique imaging inclusion criteria like GA lesion area, foveal involvement, etc.
INSIGHTeyehub@INSIGHTeyehub

Preprint alert. #AI could aid #clinicaltrials recruitment of people with geographic atrophy (GA), which causes irreversible vision loss and affects 5-10 million globally. The study used anonymised eye data from 300k+ patients at @Moorfields 🔗 bit.ly/3OZe0cM

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Daniel Milad, M.D.
Daniel Milad, M.D.@DanielMiladMD·
6/7 🆚 Interestingly, comparing GPT-4 to human experts revealed no significant difference in decision-making skills, though senior residents excelled in accuracy. #HumanVsAI
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Fares Antaki
Fares Antaki@FaresAntaki·
👋🏻 Happy to share my talk on LLMs in ophthalmology from Day 1 of the CCOI 2024 conference. I spoke about their emerging role in medicine and eye care, emphasising their potential and necessary caution. Hope you find this helpful! 🤖 I invite you to join Day 2 of the CCOI 2024 conference tomorrow. Registration is free, and you can sign up here: lnkd.in/e5iiWBrc
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INSIGHTeyehub
INSIGHTeyehub@INSIGHTeyehub·
# 1 in the top ten list of most downloaded papers in #Ophthalmology Science @AAOjournal this year Work by @FaresAntaki of @chumontreal @med_umontreal @Moorfields @UCLeye @DanielMiladMD and colleagues @ciusss_csmtl @EiasSaih
Ophthalmology@AAOjournal

1. Evaluating the Performance of ChatGPT in Ophthalmology: An Analysis of Its Successes and Shortcomings #Ophthalmology" target="_blank" rel="nofollow noopener">ophthalmologyscience.org/article/S2666-… #Science #Top102023

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