Publication | Open Access
Harnessing Large Language Models in Medical Research and Scientific Writing: A Closer Look to The Future
14
Citations
17
References
2023
Year
Artificial IntelligenceEngineeringLarge Language ModelNatural Language ProcessingLarge Language ModelsComputational LinguisticsLanguage EngineeringGrammarScientific WritingAi HealthcarePublic HealthBiomedical Text MiningMachine TranslationNlp TaskLinguisticsLanguage TechnologyTranslational RelevanceClinical DataMedical EthicsMedical ResearchMedicineClinical Decision Support SystemHealth InformaticsCustomer Service
Large Language Models (LLMs), a form of artificial intelligence generating natural language responses based on user input, have demonstrated potential across various applications such as entertainment, education, and customer service. This review comprehensively highlights their current research status and potential applications within the medical domain, addressing the challenges and opportunities for future development and implementation. Key aspects covered include diverse data sources for training and testing, such as electronic health records and clinical trials; ethical considerations, including privacy and consent; evaluation techniques focusing on accuracy and coherence; and clinical applications ranging from diagnosis to patient education. The review concludes that LLMs hold significant promise for enhancing the quality and efficiency of medical research and scientific writing but also emphasize the need for careful design and regulation to ensure safety and reliability.
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