Research Digests
Structured summaries of peer-reviewed research relevant to AI use in speech-language pathology. Each digest explains what the study found and why it matters for clinical practice.
Research here is early-stage and mostly from adjacent fields. Apply the same evidence-appraisal skills you use with any emerging literature.
Adapted LLMs Can Outperform Medical Experts in Clinical Text Summarization
Adapted large language models produced clinical summaries rated higher than those written by medical experts, supporting the copilot model of documentation assistance.
Large Language Models in Medicine: Capabilities, Limitations, and the Path Forward
A comprehensive review establishing what LLMs can and cannot do in healthcare, providing the evidence base for informed clinical adoption.
Chatbot Responses Rated Higher Quality and More Empathetic Than Physician Responses
AI chatbot responses to patient questions were rated significantly higher in quality and empathy than physician responses, raising important questions about clinical communication.
Considering the Possibilities and Pitfalls of GPT-3 in Healthcare Delivery
An early ethical analysis of generative AI in healthcare that identified bias, privacy, and misinformation risks that remain central to responsible clinical AI use today.
LLMs Show Promise for Medical Education: Case-Based Learning and Feedback
Large language models offer meaningful opportunities for clinical education through case-based learning and feedback generation, with direct relevance to SLP student supervision.