Co-intelligence: a proposal for human-artificial intelligence collaboration for large language models in medical research.
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| Title: | Co-intelligence: a proposal for human-artificial intelligence collaboration for large language models in medical research. |
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| Authors: | Ong AY; Institute of Ophthalmology, University College London, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; NIHR Moorfields Biomedical Research Centre, London, UK. Electronic address: ariel.ong@nhs.net., Merle DA; Institute of Ophthalmology, University College London, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; NIHR Moorfields Biomedical Research Centre, London, UK., Shah NH; Clinical Excellence Research Centre, Stanford University, CA, USA; Center for Biomedical Informatics Research, Stanford University, CA, USA., Tham YC; Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore; Centre for Innovation and Precision Eye Health, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Ophthalmology and Visual Science Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore., Wong TY; Singapore Eye Research Institute, Singapore National Eye Centre, Singapore; Beijing Visual Science and Translational Eye Research Institute (BERI), Tsinghua Medicine, Tsinghua University, Beijing, China; Beijing Key Laboratory of Intelligent Diagnostic Technology and Devices for Major Blinding Eye Diseases, Tsinghua Medicine, Tsinghua University, Beijing, China., Keane PA; Institute of Ophthalmology, University College London, London, UK; Moorfields Eye Hospital NHS Foundation Trust, London, UK; NIHR Moorfields Biomedical Research Centre, London, UK. Electronic address: p.keane@ucl.ac.uk. |
| Source: | The Lancet. Digital health [Lancet Digit Health] 2026 Jun; Vol. 8 (6), pp. 100982. Date of Electronic Publication: 2026 May 27. |
| Publication Type: | Journal Article; Review |
| Journal Info: | Publisher: Elsevier Ltd Country of Publication: England NLM ID: 101751302 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 2589-7500 (Electronic) Linking ISSN: 25897500 NLM ISO Abbreviation: Lancet Digit Health Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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