Opportunities and challenges for ChatGPT and large language models in biomedicine and health
Tian S, Jin Q, Yeganova L, Lai P, Zhu Q, Chen X, Yang Y, Chen Q, Kim W, Comeau D, Islamaj R, Kapoor A, Gao X, Lu Z. Opportunities and challenges for ChatGPT and large language models in biomedicine and health. Briefings In Bioinformatics 2023, 25: bbad493. PMID: 38168838, PMCID: PMC10762511, DOI: 10.1093/bib/bbad493.Peer-Reviewed Original ResearchConceptsLarge language modelsLanguage modelSensitive patient dataBiomedical information retrievalText generation tasksInformation retrievalPrivacy concernsDomain expertsInformation extractionText summarizationBiomedical domainArt methodsDiverse applicationsPrevious stateBiomedical researchersGeneration taskPatient dataSuch methodsTaskDistinct complexityGeneration capabilityExtensive literature surveySummarizationRecent rapid progressChallengesAIONER: all-in-one scheme-based biomedical named entity recognition using deep learning
Luo L, Wei C, Lai P, Leaman R, Chen Q, Lu Z. AIONER: all-in-one scheme-based biomedical named entity recognition using deep learning. Bioinformatics 2023, 39: btad310. PMID: 37171899, PMCID: PMC10212279, DOI: 10.1093/bioinformatics/btad310.Peer-Reviewed Original ResearchConceptsDeep learningEntity recognitionTraining dataEntity typesLabeling training dataNatural language textText mining tasksSignificant domain expertiseMulti-task learningMining tasksInformation extractionBioNER taskDomain expertiseBiomedical entitiesIndependent tasksSource codeBenchmark tasksLanguage textBiomedical textArt approachesAccurate annotationExternal dataData scarcityTaskLearning