Abstract
The integration of artificial intelligence (AI) into scientific research is accelerating rapidly, with large language models (LLMs) and generative AI tools now widely adopted by researchers worldwide. While the most common use of LLMs is primarily to enhance written outputs, emerging uses like streamlining systematic reviews and improving research efficiency, with some AI-assisted workflows demonstrating over 350-fold acceleration while maintaining expert-level quality. Beyond text, AI is increasingly applied in drug and protein target discovery, enabling rapid identification of previously inaccessible targets and accelerating early-stage drug development. In medical imaging, multimodal AI models have shown the ability to detect pathologies such as glaucoma from fundus photographs with high accuracy, and generative models can create high-quality, medical-grade images to augment datasets, aid training, and produce educational figures. Despite potential risks, the benefits of these technologies are becoming increasingly evident, with AI poised to transform research methodology, diagnostics, and medical education.
References
ExplanAItions—Researchers and AI. (n.d.). Retrieved November 26, 2025, from https://www.wiley.com/en-us/about-us/ai-resources/ai-study/for-researchers/
Generative AI policies for journals. (n.d.). Www.Elsevier.Com. Retrieved November 26, 2025, from https://www.elsevier.com/about/policies-and-standards/generative-ai-policies-for-journals
Musleh, A., Alwisi, N., Serhan, H. A., Toubasi, A., Malkawi, L., & Alryalat, S. A. (2025). Artificial Intelligence Powered Research Automation (AIPRA) Versus Human Expert: A Two-Arm Ophthalmology Comparative Study (p. 2025.10.27.25338904). medRxiv. https://doi.org/10.1101/2025.10.27.25338904
Michelson, M., & Reuter, K. (2019). The significant cost of systematic reviews and meta-analyses: A call for greater involvement of machine learning to assess the promise of clinical trials. Contemporary Clinical Trials Communications, 16, 100443. https://doi.org/10.1016/j.conctc.2019.100443
Ren, F., Ding, X., Zheng, M., Korzinkin, M., Cai, X., Zhu, W., Mantsyzov, A., Aliper, A., Aladinskiy, V., Cao, Z., Kong, S., Long, X., Liu, B. H. M., Liu, Y., Naumov, V., Shneyderman, A., V. Ozerov, I., Wang, J., W. Pun, F., … Zhavoronkov, A. (2023). AlphaFold accelerates artificial intelligence powered drug discovery: Efficient discovery of a novel CDK20 small molecule inhibitor. https://doi.org/10.1039/D2SC05709C
AlRyalat, S. A., Musleh, A. M., & Kahook, M. Y. (2024). Evaluating the strengths and limitations of multimodal ChatGPT-4 in detecting glaucoma using fundus images. Frontiers in Ophthalmology, 4. https://doi.org/10.3389/fopht.2024.1387190
Introducing Nano Banana Pro. (2025, November 20). Google. https://blog.google/technology/ai/nano-banana-pro/
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