A Platform for the Biomedical Application of Large Language Models
Current-generation Large Language Models (LLMs) have stirred enormous interest in recent months, yielding great potential for accessibility and automation, while simultaneously posing significant challenges and risk of misuse. To facilitate interfacing with LLMs in the biomedical space, while at the same time safeguarding their functionalities through sensible constraints, we propose a dedicated, open-source framework: BioChatter. Based on open-source software packages, we synergise the many functionalities that are currently developing around LLMs, such as knowledge integration / retrieval-augmented generation, model chaining, and benchmarking, resulting in an easy-to-use and inclusive framework for application in many use cases of biomedicine. We focus on robust and user-friendly implementation, including ways to deploy privacy-preserving local open-source LLMs. We demonstrate use cases via two multi-purpose web apps (https://chat.biocypher.org), and provide documentation, support, and an open community.
Code (2)
Tasks
BenchmarkingPrivacy PreservingRetrievalRetrieval-augmented GenerationSimilar Papers 제목 키워드 기반
Advancing Chinese biomedical text mining with community challenges
Objective: This study aims to review the recent advances in community challenges for biomedical text mining in China. Methods: We collected information of evaluation tasks released in community challenges of biomedical t…
AttributeAttribute ExtractionEvent Extractiongraph construction+11CBLUE: A Chinese Biomedical Language Understanding EvaluationBenchmark
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually offering great promise for medical practice. With the development of biomedical language understanding bench…
named-entity-recognitionNamed Entity RecognitionNamed Entity Recognition (NER)Natural Language Understanding+2CBLUE: A Chinese Biomedical Language Understanding Evaluation Benchmark
Artificial Intelligence (AI), along with the recent progress in biomedical language understanding, is gradually changing medical practice. With the development of biomedical language understanding benchmarks, AI applicat…
Intent ClassificationMedical Concept NormalizationMedical Relation ExtractionNamed Entity Recognition+6BiomedBench: A benchmark suite of TinyML biomedical applications for low-power wearables
The design of low-power wearables for the biomedical domain has received a lot of attention in recent decades, as technological advances in chip manufacturing have allowed real-time monitoring of patients using low-compl…
Epistemic AI platform accelerates innovation by connecting biomedical knowledge
Epistemic AI accelerates biomedical discovery by finding hidden connections in the network of biomedical knowledge. The Epistemic AI web-based software platform embodies the concept of knowledge mapping, an interactive p…
Information RetrievalRetrieval