Check out our latest work on Contextual Evaluation of Large Language Models for Tropical and Infectious Diseases (openreview.net/forum?id=yXe...), accepted at two NeurIPs workshops: GenAI4health (genai4health.github.io) and AIM-FM (aim-fm-24.github.io/NeurIPS/). #llms #genai4health #globalhealth - ThreadSky

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Check out our latest work on Contextual Evaluation of Large Language Models for Tropical and Infectious Diseases (https://openreview.net/forum?id=yXe...), accepted at two NeurIPs workshops: GenAI4health (https://genai4health.github.io) and AIM-FM (aim-fm-24.github.io/NeurIPS/). #llms #genai4health #globalhealth

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dr-nyamewaa.bsky.social•77 days ago

Many thanks to all co-authors: @kat-heller.bsky.social , @nenadtomasev.bsky.social , Chintan Ghate, Tiya Tiyasirichokchai, @adoubleva.bsky.social , Oluwatosin Akande, Geoffrey Siwo, Steve Adudans, Sylvanus Aitkins, Odianosen Ehiakhamen, and Eric Ndombi.

dr-nyamewaa.bsky.social•77 days ago

We find that including context such as risk factors and location in addition to symptoms also improves model performance. Additionally we assemble a panel of human experts to set a human expert baseline score on the dataset and to provide ratings of data quality, usefulness, etc

dr-nyamewaa.bsky.social•77 days ago

Results show that LLMs perform worse on TRINDs than they do on reported US-based health QAs, indicating a distribution shift in the data and the need for further optimization for global diseases. We also find that LLMs more accurately identify diseases that are common or specific.

cryptoshot.bsky.social•77 days ago

First, GPU demand skyrocketed to build LLMs

Then, compute demand went up for AI inference and processing

Next, memory demand will rocket for AI Agents' reasoning and cognitive capacity

https://Origintrail.io $TRAC provides that memory

dr-nyamewaa.bsky.social•77 days ago

We develop and expand the TRopical and INfectious Diseases (TRINDs) dataset to evaluate LLMs for these contexts, and demonstrate through systematic experimentation, the effect of contextual information on LLM outputs for disease classification.

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