Logo Lanfrica
  • Home
  • Atlas
  • Insights
  • Docs
  • Sign in

© 2026 Lanfrica. All rights reserved. All copyrights of the resources shown on the Lanfrica website belong to the original copyright holders, unless explicitly stated otherwise.

Contextual Evaluation of Large Language Models for Classifying Tropical and Infectious Diseases

Domain:

healthcarenatural language processing

Record type:

paperdataset
Creator:
AsiTomGhaTiy
Host:avatar
While large language models (LLMs) have shown promise for medical question answering, there is limited work focused on tropical and infectious disease-specific exploration. We build on an opensource tropical and infectious diseases (TRINDs) dataset, expanding it to include demographic and semantic clinical and consumer augmentations yielding 11000+ prompts. We evaluate LLM performance on these, comparing generalist and medical LLMs, as well as LLM outcomes to human experts. We demonstrate through systematic experimentation, the benefit of contextual information such as demographics, location, gender, risk factors for optimal LLM response. Finally we develop a prototype of TRINDs-LM, a research tool that provides a playground to navigate how context impacts LLM outputs for health. Accepted at 2 NeurIPS 2024 workshops: Generative AI for Health Workshop and Workshop on Advancements In Medical Foundation Models: Explainability, Robustness, Security, and Beyond

Visit

arxiv.org

Tasks

question answering

Tags

Computation and LanguageArtificial Intelligence

Similar

Leveraging social media data and large language models for understanding public health behaviours in the context of infectious diseases and vaccinationLocalised Contextual Large Language Models (LLM’s) for Personalised Medicine in AfricaContextual Phenotyping of Pediatric Sepsis Cohort Using Large Language ModelsSerological Surveillance Development for Tropical Infectious Diseases Using Simultaneous Microsphere-Based Multiplex Assays and Finite Mixture ModelsMulti-lingual Functional Evaluation for Large Language ModelsEvaluation Mirage: A Layered Evaluation of Large Language Models and Language Identification for African NLP

Leveraging social media data and large language models for understanding public health behaviours in the context of infectious diseases and vaccination

This thesis explores the integration of artificial intelligence (AI) and, more specifically, large l

Localised Contextual Large Language Models (LLM’s) for Personalised Medicine in Africa

Contextual Phenotyping of Pediatric Sepsis Cohort Using Large Language Models

Clustering patient subgroups is essential for personalized care and efficient resource use. Traditio

Serological Surveillance Development for Tropical Infectious Diseases Using Simultaneous Microsphere-Based Multiplex Assays and Finite Mixture Models

Background

A strategy to combat infectious diseases, including neglected tropical dise

Multi-lingual Functional Evaluation for Large Language Models

Multi-lingual competence in large language models is often evaluated via static data benchmarks such

Evaluation Mirage: A Layered Evaluation of Large Language Models and Language Identification for African NLP

David Ifeoluwa Adelani (Supervisor) As Large Language Models (LLMs) are increasingly deployed in glo