mlsanityData to 14 Oct 2026

Beyond Multiple-Choice Accuracy: Real-World Challenges of Implementing Large Language Models in Healthcare

arXiv 2410.18460 ↗First posted 24 Oct 2024cs.AIcited by 4

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Abstract (arXiv)

Large Language Models (LLMs) have gained significant attention in the medical domain for their human-level capabilities, leading to increased efforts to explore their potential in various healthcare applications. However, despite such a promising future, there are multiple challenges and obstacles that remain for their real-world uses in practical settings. This work discusses key challenges for LLMs in medical applications from four unique aspects: operational vulnerabilities, ethical and social considerations, performance and assessment difficulties, and legal and regulatory compliance. Addressing these challenges is crucial for leveraging LLMs to their full potential and ensuring their responsible integration into healthcare.

Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). Builds on 14 of its 30 references that are in the map. First posted on arXiv 24 Oct 2024.

Builds on

14 of 30 references.

References · 14

  1. 2022Can large language models reason about medical questions?cited by 194
  2. 2023Large language models in healthcare and medical domain: A reviewcited by 127
  3. 2023Towards Mitigating Hallucination in Large Language Models via Self-Reflectioncited by 81
  4. 2024Towards Conversational Diagnostic AIcited by 79
  5. 2023Matching Patients to Clinical Trials with Large Language Modelscited by 69
  6. 2024Towards Evaluating and Building Versatile Large Language Models for Medicinecited by 40
  7. 2024Elephants Never Forget: Memorization and Learning of Tabular Data in Large Language Modelscited by 36
  8. 2024Unmasking and Quantifying Racial Bias of Large Language Models in Medical Report Generationcited by 31
  9. 2024Efficient Fine-Tuning of Large Language Models for Automated Medical Documentationcited by 16
  10. 2023The Reasonable Effectiveness of Diverse Evaluation Datacited by 10
  11. 2024Adversarial Attacks on Large Language Models in Medicinecited by 10
  12. 2024Prompt Injection Attacks on Large Language Models in Oncologycited by 8
2 more
  1. 2023Medical Foundation Models are Susceptible to Targeted Misinformation Attackscited by 5
  2. 2024A survey of recent methods for addressing AI fairness and bias in biomedicinecited by 5

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Cited by year

Citing papers per year: 2025: 4.

4 papers.

  1. 2025Memorization in Large Language Models in Medicine: Prevalence, Characteristics, and Implicationscited by 5
  2. 2025CLARITY: Clinical Assistant for Routing, Inference, and Triagecited by 2
  3. 2025How to Evaluate Medical AIcited by 1
  4. 2025A Field Guide to Deploying AI Agents in Clinical Practicecited by 0