English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Recently, Large Language Models (LLMs) have showcased remarkable capabilitiesin natural language understanding. While demonstrating proficiency in everydayconversations and question-answering situations, these models frequentlystruggle in domains that require precision, such as medical applications, dueto their lack of domain-specific knowledge. In this paper, we describe theprocedure for building a powerful, open-source language model specificallydesigned for medicine applications, termed as PMC-LLaMA. Our contributions arethreefold: (i) we systematically investigate the process of adapting ageneral-purpose foundation language model towards medical domain, this involvesdata-centric knowledge injection through the integration of 4.8M biomedicalacademic papers and 30K medical textbooks, as well as comprehensive fine-tuningfor alignment with domain-specific instructions; (ii) we contribute alarge-scale, comprehensive dataset for instruction tuning. This datasetencompasses medical question-answering (QA), rationale for reasoning, andconversational dialogues, comprising a total of 202M tokens; (iii) we conductthorough ablation studies to demonstrate the effectiveness of each proposedcomponent. While evaluating on various public medical question-answeringbenchmarks, our lightweight PMCLLaMA, which consists of only 13 billionparameters, exhibits superior performance, even surpassing ChatGPT. All models,codes, datasets can be found in https://github.com/chaoyi-wu/PMC-LLaMA.

PMC-LLaMA: Towards Building Open-source Language Models for Medicine