Generative Artificial Intelligence and Large Language Models in Smart Healthcare Applications: Current Status and Future Perspectives

Strategic Insights -

Research into artificial intelligence (AI) is yielding new insights into its potential in smart healthcare applications. As climate change, habitat destruction, and increased population ages contribute to rising disease incidence, AI models can process and analyze vast amounts of medical data. Generative pre-trained transformers (GPT) and bidirectional encoder representations from transformers (BERT) have demonstrated significant capabilities in various medical tasks, according to research from Aligarh Muslim University. These models hold promise for intelligent virtual health assistants, personalized patient care plans, and early detection of medical conditions.

Key Takeaways:

  • The systematic literature review conducted by researchers identified 108 papers on generative AI and LLMs in healthcare applications, published in peer-reviewed journals such as PubMed, PMC, Cochrane Library, Google Scholar, and Web of Science.
  • Generative AI and LLMs have demonstrated significant capabilities in medical tasks, including intelligent virtual health assistants, personalized patient care plans, and early detection of medical conditions.
  • Researchers are actively exploring the potential of AI to transform healthcare, with a focus on addressing issues such as bias, lack of explainability, and integration difficulties.
  • The future of generative AI and LLMs in healthcare is promising, with ongoing research and development expected to drive innovation and improvement.
  • Researchers Md Asraful Haque and his team from Aligarh Muslim University have been conducting research into the applications of generative AI and LLMs in healthcare.
  • The study aims to provide an overview of the potential benefits and challenges of using generative AI and LLMs in smart healthcare applications.

Statistics:

  • 108 papers were identified in the systematic literature review on generative AI and LLMs in healthcare applications.
  • The literature review was conducted across 5 databases: PubMed, PMC, Cochrane Library, Google Scholar, and Web of Science.
  • Researchers have been actively exploring AI applications in healthcare, with a focus on intelligent virtual health assistants, personalized patient care plans, and early detection of medical conditions.
  • The study aims to address challenges and ethical considerations in the use of generative AI and LLMs in healthcare.
  • The research has identified the need for ongoing research and development to address issues such as bias, lack of explainability, and integration difficulties.

Sources:

  • NewsRx. Study Data from Aligarh Muslim University Provide New Insights into Artificial Intelligence (Generative artificial intelligence and large language models in smart healthcare applications: Current status and future perspectives). Journal of Engineering. August 25, 2025; p 3809.
  • Haque, M. A., et al. "Generative artificial intelligence and large language models in smart healthcare applications: Current status and future perspectives." Computational Biology and Chemistry 120 (2025): 108611.
  • Elsevier Sci Ltd. Computational Biology and Chemistry. www.journals.elsevier.com/computational-biology-and-chemistry/
  • Aligarh Muslim University. Interdisciplinary Center for Artificial Intelligence. Zakir Husain College of Engineering and Technology. Aligarh, India.