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Found 4 papers, 2 papers with code
Conversational Bots for Psychotherapy: A Study of Generative Transformer Models Using Domain-specific Dialogues
Through quantitative evaluation of the linguistic quality, we observe that the dialog generation model - DialoGPT (345M) with transfer learning on video data attains scores similar to a human response baseline.
Large language models in biomedical natural language processing: benchmarks, baselines, and recommendations
Biomedical literature is growing rapidly, making it challenging to curate and extract knowledge manually.
Integrating Commercial and Social Determinants of Health: A Unified Ontology for Non-Clinical Determinants of Health
The objectives of this research are 1) to develop an ontology for CDoH by utilizing PubMed articles and ChatGPT; 2) to foster ontology reuse by integrating CDoH with an existing SDoH ontology into a unified structure; 3) to devise an overarching conception for all non-clinical determinants of health and to create an initial ontology, called N-CODH, for them; 4) and to validate the degree of correspondence between concepts provided by ChatGPT with the existing SDoH ontology
Improving Large Language Models for Clinical Named Entity Recognition via Prompt Engineering
Results: Using baseline prompts, GPT-3. 5 and GPT-4 achieved relaxed F1 scores of 0. 634, 0. 804 for MTSamples, and 0. 301, 0. 593 for VAERS.
