Can artificial intelligence-strengthened ChatGPT or other large language models transform nucleic acid research?

Large language model to multimodal large language model: A journey to shape the biological macromolecules to biological sciences and medicine

After ChatGPT was released, large language models (LLMs) became more popular. Academicians use ChatGPT or LLM models for different purposes, and the use of ChatGPT or LLM is increasing from medical science to diversified areas. Recently, the multimodal LLM (MLLM) has also become popular. Therefore, we comprehensively illustrate the LLM and MLLM models for a complete understanding. We also aim for simple and extended reviews of LLMs and MLLMs for a broad category of readers, such as researchers, students in diversified fields, and other academicians. The review article illustrates the LLM and MLLM models, their working principles, and their applications in diversified fields. First, we demonstrate the technical concept of LLMs, working principle, Black Box, and the evolution of LLMs. To explain the working principle, we discuss the tokenization process, token representation, and token relationships. We also extensively demonstrate the application of LLMs in biological macromolecules, medical science, biological science, and other areas. We illustrate the multimodal applications of LLMs or MLLMs. Finally, we illustrate the limitations, challenges, and future prospects of LLMs. The review acts as a booster dose for clinicians, a primer for molecular biologists, and a catalyst for scientists, and also benefits diversified academicians.

Large language models reshaping molecular biology and drug development

The utilization of large language models (LLMs) has become a significant advancement in the domains of medicine and clinical informatics, providing a revolutionary potential for scientific breakthroughs and customized therapies. LLM models are trained on large datasets and exhibit the capacity to comprehend and analyze intricate biological data, encompassing genomic sequences, protein structures, and clinical health records. With the utilization of their comprehension of the language of biology, they possess the ability to reveal concealed patterns and insights that may evade human researchers. LLMs have been shown to positively impact various aspects of molecular biology, including the following: genomic analysis, drug development, precision medicine, biomarker development, experimental design, collaborative research, and accessibility to specialized expertise. However, it is imperative to acknowledge and tackle the obstacles and ethical implications involved. The careful consideration of data bias and generalization, data privacy and security, explainability and interpretability, and ethical concerns around responsible application is vital. The successful resolution of these obstacles will enable us to fully utilize the capabilities of LLMs, leading to substantial progress in the fields of molecular biology and pharmaceutical research. This progression also has the ability to bolster influential impacts for both the individual and the broader community.

A scoping review of ChatGPT's role in healthcare education and research

OBJECTIVES

To examine and consolidate literature regarding the advantages and disadvantages of utilizing ChatGPT in healthcare education and research.

DESIGN/METHODS

We searched seven electronic databases (PubMed/Medline, CINAHL, Embase, PsycINFO, Scopus, ProQuest Dissertations and Theses Global, and Web of Science) from November 2022 until September 2023. This scoping review adhered to Arksey and O'Malley's framework and followed reporting guidelines outlined in the PRISMA-ScR checklist. For analysis, we employed Thomas and Harden's thematic synthesis framework.

RESULTS

A total of 100 studies were included. An overarching theme, "Forging the Future: Bridging Theory and Integration of ChatGPT" emerged, accompanied by two main themes (1) Enhancing Healthcare Education, Research, and Writing with ChatGPT, (2) Controversies and Concerns about ChatGPT in Healthcare Education Research and Writing, and seven subthemes.

CONCLUSIONS

Our review underscores the importance of acknowledging legitimate concerns related to the potential misuse of ChatGPT such as 'ChatGPT hallucinations', its limited understanding of specialized healthcare knowledge, its impact on teaching methods and assessments, confidentiality and security risks, and the controversial practice of crediting it as a co-author on scientific papers, among other considerations. Furthermore, our review also recognizes the urgency of establishing timely guidelines and regulations, along with the active engagement of relevant stakeholders, to ensure the responsible and safe implementation of ChatGPT's capabilities. We advocate for the use of cross-verification techniques to enhance the precision and reliability of generated content, the adaptation of higher education curricula to incorporate ChatGPT's potential, educators' need to familiarize themselves with the technology to improve their literacy and teaching approaches, and the development of innovative methods to detect ChatGPT usage. Furthermore, data protection measures should be prioritized when employing ChatGPT, and transparent reporting becomes crucial when integrating ChatGPT into academic writing.

ChatGPT and large language models in orthopedics: from education and surgery to research

ChatGPT has quickly popularized since its release in November 2022. Currently, large language models (LLMs) and ChatGPT have been applied in various domains of medical science, including in cardiology, nephrology, orthopedics, ophthalmology, gastroenterology, and radiology. Researchers are exploring the potential of LLMs and ChatGPT for clinicians and surgeons in every domain. This study discusses how ChatGPT can help orthopedic clinicians and surgeons perform various medical tasks. LLMs and ChatGPT can help the patient community by providing suggestions and diagnostic guidelines. In this study, the use of LLMs and ChatGPT to enhance and expand the field of orthopedics, including orthopedic education, surgery, and research, is explored. Present LLMs have several shortcomings, which are discussed herein. However, next-generation and future domain-specific LLMs are expected to be more potent and transform patients' quality of life.

Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science

The release of ChatGPT has initiated new thinking about AI-based Chatbot and its application and has drawn huge public attention worldwide. Researchers and doctors have started thinking about the promise and application of AI-related large language models in medicine during the past few months. Here, the comprehensive review highlighted the overview of Chatbot and ChatGPT and their current role in medicine. Firstly, the general idea of Chatbots, their evolution, architecture, and medical use are discussed. Secondly, ChatGPT is discussed with special emphasis of its application in medicine, architecture and training methods, medical diagnosis and treatment, research ethical issues, and a comparison of ChatGPT with other NLP models are illustrated. The article also discussed the limitations and prospects of ChatGPT. In the future, these large language models and ChatGPT will have immense promise in healthcare. However, more research is needed in this direction.