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https://ahro.austin.org.au/austinjspui/handle/1/35620| Title: | Environmental impact of large language models in medicine. | Austin Authors: | Kleinig, Oliver;Sinhal, Shreyans;Khurram, Rushan;Gao, Christina;Spajic, Luke;Zannettino, Andrew;Schnitzler, Margaret;Guo, Christina;Zaman, Sarah;Smallbone, Harry;Ittimani, Mana;Chan, Weng Onn;Stretton, Brandon;Godber, Harry;Chan, Justin;Turner, Richard C;Warren, Leigh R;Clark, Jonathan CM ;Sivagangabalan, Gopal;Marshall-Webb, Matthew;Moseley, Genevieve;Driscoll, Simon;Kovoor, Pramesh;Chow, Clara K;Luo, Yuchen;Thiagalingam, Aravinda;Zaka, Ammar;Gould, Paul;Ramponi, Fabio;Gupta, Aashray;Kovoor, Joshua G;Bacchi, Stephen | Affiliation: | School of Medicine, University of Adelaide, Adelaide, South Australia, Australia.;Division of Medicine, Lyell McEwin Hospital, Adelaide, South Australia, Australia. Oxford Martin Programme on the Future of Food, Nuffield Department of Population Health, University of Oxford, Oxford, UK. School of Medicine, University of Adelaide, Adelaide, South Australia, Australia.;Division of Medicine, Royal Adelaide Hospital, Adelaide, South Australia, Australia. Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.;Northern Clinical School, Westmead Clinical School, Royal North Shore Hospital, Sydney, New South Wales, Australia. Department of Infectious Diseases, Alfred Hospital, Melbourne, Victoria, Australia. Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.;Westmead Applied Research Centre, Department of Cardiology, Westmead Hospital, Sydney, New South Wales, Australia. Division of Medicine, Fiona Stanley Hospital, Perth, Western Australia, Australia. Division of Medicine, Royal Prince Alfred Hospital, Sydney, New South Wales, Australia. School of Medicine, University of Adelaide, Adelaide, South Australia, Australia.;Division of Medicine, Royal Adelaide Hospital, Adelaide, South Australia, Australia. Division of Medicine, Royal Adelaide Hospital, Adelaide, South Australia, Australia. Strategy & General Counsel, Spark Festival, Sydney, New South Wales, Australia. School of Medicine, New York University, New York, New York, USA. School of Medicine, University of Tasmania, Hobart, Tasmania, Australia. School of Medicine, University of Adelaide, Adelaide, South Australia, Australia. Centre for Mathematics and Precision Healthcare, Institute of GlobalHealth Innovation, National Heart and Lung Institute, Imperial College London, London, UK.;NHS Digital, Leeds, UK. Westmead Applied Research Centre, Department of Cardiology, Westmead Hospital, Sydney, New South Wales, Australia. Division of Surgery, Box Hill Hospital, Melbourne, Victoria, Australia. School of Medicine, Deakin University, Geelong, Victoria, Australia. Department of Meteorology, University of Reading, Reading, UK. Westmead Applied Research Centre, Department of Cardiology, Westmead Hospital, Sydney, New South Wales, Australia. Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia.;Westmead Applied Research Centre, Department of Cardiology, Westmead Hospital, Sydney, New South Wales, Australia. The Surgery Centre Westmead Applied Research Centre, Department of Cardiology, Westmead Hospital, Sydney, New South Wales, Australia. Division of Medicine, Gold Coast University Hospital, Gold Coast, Queensland, Australia. Department of Cardiology, Princess Alexandra Hospital, Brisbane, Queensland, Australia. Division of Cardiothoracic Surgery, Yale School of Medicine, New Haven, Connecticut, USA. School of Medicine, University of Adelaide, Adelaide, South Australia, Australia.;Division of Medicine, Lyell McEwin Hospital, Adelaide, South Australia, Australia. |
Issue Date: | Dec-2024 | Date: | 2024 | Publication information: | Internal Medicine Journal 2024-12; 54(12) | Abstract: | The environmental impact of large language models (LLMs) in medicine spans carbon emission, water consumption and rare mineral usage. Prior-generation LLMs, such as GPT-3, already have concerning environmental impacts. Next-generation LLMs, such as GPT-4, are more energy intensive and used frequently, posing potentially significant environmental harms. We propose a five-step pathway for clinical researchers to minimise the environmental impact of the natural language algorithms they create. | URI: | https://ahro.austin.org.au/austinjspui/handle/1/35620 | DOI: | 10.1111/imj.16549 | ORCID: | 0000-0003-3320-4424 0009-0005-0033-3352 0000-0002-6646-6167 0000-0002-7939-3489 0000-0002-3880-3840 |
Journal: | Internal Medicine Journal | Start page: | 2083 | End page: | 2086 | PubMed URL: | 39542015 | ISSN: | 1445-5994 | Type: | Journal Article | Subjects: | environment large language model water use |
| Appears in Collections: | Journal articles |
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