Research

Projects

Publications

2026

  • Thirunavukarasu A. J. Feasibility and performance of eye movement perimetry for glaucoma triage in Tanzania. PLOS Global Public Health 6, e0007237 (2026).
  • Thirunavukarasu A. J. Can generative artificial intelligence enhance evidence-based and personalized medicine? PLOS Medicine 23, e1004931 (2026).
  • Wang N., Thirunavukarasu A. J. et al. Automated bulk classification of glaucoma severity and progression using perimetry results. Eye (2026).
  • Lim E., Thirunavukarasu A. J., He Y. V. et al. Building a code of conduct for AI-driven clinical consultations. Nature Medicine 32, 400–403 (2026).
  • Thirunavukarasu A. J., Li S., Qin P. et al. Clinical artificial intelligence applications of vision-language foundation models. PLOS Digital Health 5, e0001453 (2026).
  • Tuft S., Taylor E. H., McLean K., Thirunavukarasu A. J. et al. Regional and temporal trends in antimicrobial susceptibility among isolates from bacterial keratitis. The Lancet Microbe 7, 101359 (2026).
  • Ke Y., Jin L., Ong J. C. L., Thirunavukarasu A. J. et al. AI-induced never-skilling in medical education. Nature Medicine 32, 1997–2006 (2026).
  • Ning Y., Ma Y., Liu M., Collins G. S., Thirunavukarasu A. J. et al. Ethical principles and considerations in health AI. Patterns 9, 101662 (2026).
  • Cleland C. R., Tsang K., Taylor E. H., Thirunavukarasu A. J. et al. Will Artificial Intelligence Augment Global Health Inequalities? NEJM AI 3, AIcs2600267 (2026).
  • Yang R. et al. MAGIC: an international network for evaluating generative artificial intelligence in global health. Nature Medicine (2026).
  • Bauer F. et al. Assessing the Transferability of Peer-Assisted Ultrasound Training for Medical Students. Clinical Anatomy 39, 541–552 (2026).
  • Zhang L., Wu F., Thirunavukarasu A. J. et al. Emerging Semantic Segmentation from Positive and Negative Coarse Label Learning. MLMI 2025 (2026).
  • Stupnicki A. et al. Benchmarking eye health advice from generative artificial intelligence in terms of factual accuracy, safety, comprehensiveness and readability. Research Square (2026). [preprint]
  • Tan T. F. et al. Clinical Validation of Medical-based Large Language Model Chatbots on Ophthalmic Patient Queries with LLM-based Evaluation. arXiv 2602.05381 (2026).

2025

  • Huo B., Thirunavukarasu A. J. et al. Reporting guidelines for chatbot health advice studies: explanation and elaboration for CHART. BMJ 390, e083305 (2025).
  • Teo Z. L., Thirunavukarasu A. J. et al. Generative artificial intelligence in medicine. Nature Medicine 31, 3270–3282 (2025).
  • Thirunavukarasu A. J., Jain N. et al. Semi-automated screening reveals patients with glaucoma-induced blindness missing out on social support. British Journal of Ophthalmology 109, 1126–1131 (2025).
  • Sanghera R., Thirunavukarasu A. J. et al. High-performance automated abstract screening with large language model ensembles. Journal of the American Medical Informatics Association 32, 893–904 (2025).
  • Thirunavukarasu A. J., Guru S., Rocha H. & Sekhon C. Treatment allocation in ophthalmological randomised-control trials (TAO-RCT). Eye 39, 2591–2598 (2025).
  • Thirunavukarasu A. J., Lim E. & Huo B. How CHART can help to advance clinical artificial intelligence research. The Lancet Digital Health 7, 100910 (2025).
  • Rocha H., Chong Y. J., Thirunavukarasu A. J. et al. Performance of foundation models vs physicians in textual and multimodal ophthalmological questions. JAMA Ophthalmology 144, 5–13 (2025).
  • Oddy C., Lowcock D., Davies T. W. et al. Structural and organisational impacts of peri-operative enhanced care services in the UK (REPACC). Anaesthesia 81, 500–512 (2025).
  • Li S. et al. μ² Tokenizer: Differentiable Multi-Scale Multi-Modal Tokenizer for Radiology Report Generation. MICCAI 2025 3–12 (2026).
  • Hay S. I. et al. Burden of 375 diseases and injuries, 1990–2023: GBD Study 2023. The Lancet 406, 1873–1922 (2025).
  • Schumacher A. E. et al. Global age-sex-specific all-cause mortality and life expectancy estimates, GBD Study 2023. The Lancet 406, 1731–1810 (2025).
  • Raji S., Thirunavukarasu A. J. et al. Functional vision tests as clinical trial outcome measures in ophthalmology. BMJ Open 15, e097970 (2025).
  • Thirunavukarasu A. J., Raji S. & Cehajic Kapetanovic J. Visualising treatment effects in low-vision settings. Gene Therapy 33, 372–382 (2025).
  • Huo B., Collins G. S., Chartash D., Thirunavukarasu A. J. et al. CHART statement. Co-published in British Journal of Surgery 112, znaf142; BMJ Medicine 4, e001632; JAMA Network Open 8, e2530220; BMC Medicine 23, 447; Annals of Family Medicine; Artificial Intelligence in Medicine 168, 103222 (2025).
  • Husøy A. K. et al. Global, regional, and national burden of headache disorders, 1990–2023: GBD Study 2023. The Lancet Neurology 24, 1005–1015 (2025).
  • Tan T. F., Thirunavukarasu A. J., Quek C. & Ting D. S. W. Evaluation of ophthalmic large language models: quantitative vs. qualitative methods. Current Opinion in Ophthalmology 36, 466–471 (2025).
  • Sinha A., Thirunavukarasu A. J., Bonshahi A. & Brassett C. Impact of anatomical research projects for medical students. Clinical Anatomy 38, 347–354 (2025).
  • Tham Y. C. et al. Building the world's first truly global medical foundation model. Nature Medicine 31, 3580–3585 (2025).
  • Ong J. C. L. et al. International partnership for governing generative artificial intelligence models in medicine. Nature Medicine 31, 2836–2839 (2025).
  • Huo B. et al. Large Language Models for Chatbot Health Advice Studies: A Systematic Review. JAMA Network Open 8, e2457879 (2025).
  • Bai Y. et al. EVLF-FM: Explainable Vision Language Foundation Model for Medicine. arXiv 2509.24231 (2025).
  • Qin P., Thirunavukarasu A. J. & Zhang L. Deep Learning Ensemble for Predicting Diabetic Macular Edema Onset. DIAMOND/MARIO 2024, MICCAI 64–73 (Springer Nature, 2025).

2024

  • Thirunavukarasu A. J. et al. Large language models approach expert-level clinical knowledge and reasoning in ophthalmology. PLOS Digital Health 3, e0000341 (2024).
  • Thirunavukarasu A. J. et al. A validated web-application (GFDC) for automatic classification of glaucomatous visual field defects using Hodapp-Parrish-Anderson criteria. npj Digital Medicine 7, 131 (2024).
  • Thirunavukarasu A. J. et al. Robot-Assisted Eye Surgery: A Systematic Review of Effectiveness, Safety, and Practicality in Clinical Settings. Translational Vision Science & Technology 13, 20 (2024).
  • Thirunavukarasu A. J. et al. Nanohydroxyapatite Coating Attenuates Fibrotic and Immune Responses to Promote Keratoprosthesis Biointegration in Advanced Ocular Surface Disorders. ACS Applied Materials & Interfaces 16, 25892–25908 (2024).
  • Thirunavukarasu A. J. et al. Clinical performance of automated machine learning: A systematic review. Annals of the Academy of Medicine, Singapore 53, 187–207 (2024).
  • Sienko A., Thirunavukarasu A. J., Kuzmich T. & Allen L. An Initial Validation of Community-Based Air-Conduction Audiometry in Adults With DigiBel. JMIR Formative Research 8, e51770 (2024).
  • Li Y. et al. The next generation of healthcare ecosystem in the metaverse. Biomedical Journal 47, 100679 (2024).
  • Thirunavukarasu A. J. & O'Logbon J. The potential and perils of generative artificial intelligence in psychiatry and mental health. Nature Mental Health 2, 745–746 (2024).
  • Vallance A. E. et al. A systematic methodology review of fluorescence-guided cancer surgery to inform the development of a core master protocol and outcome set. BMC Cancer 24, 697 (2024).

2023

  • Thirunavukarasu A. J. et al. Large language models in medicine. Nature Medicine 29, 1930–1940 (2023).
  • Tan T. F., Thirunavukarasu A. J., Campbell J. P. et al. Artificial intelligence and digital health in global eye health: opportunities and challenges. The Lancet Global Health 11, e1432–e1443 (2023).
  • Thirunavukarasu A. J., Hassan R., Limonard A. & Savant S. V. Accuracy and reliability of self-administered visual acuity tests: Systematic review of pragmatic trials. PLOS ONE 18, e0281847 (2023).
  • Thirunavukarasu A. J. et al. Trialling a Large Language Model (ChatGPT) in General Practice With the Applied Knowledge Test: Observational Study Demonstrating Opportunities and Limitations in Primary Care. JMIR Medical Education 9, e46599 (2023).
  • Thirunavukarasu A. J. Large language models will not replace healthcare professionals: curbing popular fears and hype. Journal of the Royal Society of Medicine 116, 181–182 (2023).
  • Thirunavukarasu A. J. et al. Electron beam-irradiated donor cornea for on-demand lenticule implantation to treat corneal diseases and refractive error. Acta Biomaterialia 169, 334–347 (2023).
  • Ng F. Y. C., Thirunavukarasu A. J., Cheng H. et al. Artificial intelligence education: An evidence-based medicine approach for consumers, translators, and developers. Cell Reports Medicine 4, 101230 (2023).
  • Thirunavukarasu A. J. How Can the Clinical Aptitude of AI Assistants Be Assayed? Journal of Medical Internet Research 25, e51603 (2023).
  • Thirunavukarasu A. J. et al. Democratizing Artificial Intelligence Imaging Analysis With Automated Machine Learning: Tutorial. Journal of Medical Internet Research 25, e49949 (2023).
  • Basu S., Thirunavukarasu A. J., Maheshwari V., Zode M. & Hassan R. Burden, determinants and treatment status of metabolic syndrome among older adults in India: a nationally representative, community-based cross-sectional survey. BMJ Public Health 1, e000389 (2023).
  • Tan T. F., Thirunavukarasu A. J. et al. Generative Artificial Intelligence through ChatGPT and Other Large Language Models in Ophthalmology: Clinical Applications and Challenges. Ophthalmology Science 3, 100394 (2023).
  • Yang R. et al. Large language models in health care: Development, applications, and challenges. Health Care Science 2, 255–263 (2023).
  • Dohle E. et al. Human spinal cord tissue is an underutilised resource in degenerative cervical myelopathy: findings from a systematic review of human autopsies. Acta Neurochirurgica 165, 1121–1131 (2023).

2022

  • Thirunavukarasu A. J., Mullinger D., Rufus-Toye R. M., Farrell S. & Allen L. E. Clinical validation of a novel web-application for remote assessment of distance visual acuity. Eye 36, 2057–2061 (2022).
  • Thirunavukarasu A. J., Hassan R., Savant S. V. & Hamilton D. L. Analgesia for retinopathy of prematurity screening: A systematic review. Pain Practice 22, 642–651 (2022).
  • Thirunavukarasu A. J., Ross A. C. & Gilbert R. M. Vitamin A, systemic T-cells, and the eye: Focus on degenerative retinal disease. Frontiers in Nutrition 9, 914457 (2022).

2021

  • Thirunavukarasu A. J. et al. Temporomandibular joint anatomy: Ultrasonographic appearances and sexual dimorphism. Clinical Anatomy 34, 1043–1049 (2021).
  • Thirunavukarasu A. J. Evaluating the mainstream impact of ophthalmological research with Google Trends. Eye 35, 3165–3167 (2021).
  • Thirunavukarasu A. J., Ferro A., Singh Dubb S., Hamilton D. L. & Brassett C. Investigating the correlation between bone density and fracture frequency in the mandibular condyle with micro-computed tomography. British Journal of Oral and Maxillofacial Surgery 59, 380–383 (2021).
  • Allen L., Thirunavukarasu A. J., Podgorski S. & Mullinger D. Novel web application for self-assessment of distance visual acuity to support remote consultation. BMJ Open Ophthalmology 6, e000801 (2021).
  • Thirunavukarasu A. J., Malem A. & Mourtzoukos S. Combined Phacoemulsification and Intravitreal Dexamethasone is an Effective Option for High-Risk Diabetic Patients. Cureus 13, e17603 (2021).
  • Thirunavukarasu A. J. Comment on: The reliability of visual acuity measurements from inpatient referrals to ophthalmology. Eye 36, 1844 (2021).