Potential reduction in healthcare carbon footprint by autonomous artificial intelligence

Wolf, Risa M.; Abràmoff, Michael D.; Channa, Roomasa; Tava, Chris; Clarida, W.; Lehmann, Harold P.

doi:10.1038/s41746-022-00605-w

Cited by 20 publications

(11 citation statements)

References 33 publications

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“…Although major challenges related to data governance/ management, 135,[175][176][177][178][179][180][181][182][183] ethical/legal, [184][185][186][187] and environmental 188,189 considerations would need to be addressed, these "dynamic multimodal ML models" may become cost-effective in different populations 169,[190][191][192][193] if conceived as the integrative tools needed to provide precision health 22,164,165,168,[194][195][196] and support some of the iterative cycles of knowledge generation and continuous improvement of "learning health systems". 11,[197][198][199][200]…”

Section: Opportunitiesmentioning

confidence: 99%

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

Gonzalez,

Saha,

Campbell

et al. 2024

Journal of Pathology Informatics

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Section: Opportunitiesmentioning

confidence: 99%

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

Gonzalez,

Saha,

Campbell

et al. 2024

Journal of Pathology Informatics

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“…Recently, the UK-based National Health Service set two ambitious aims of (i) becoming net carbon zero through direct emissions by 2040 (e.g., on site hospital energy and water consumption) and (ii) reducing indirect emissions by 80% around 2036, which is greatly influenced by e.g., information and communication technology (ICT), and medical devices. Accordingly, there is a real and pressing demand for reliable alternatives in those current examples to aid healthcare services to improve their environmental and economic impact while striking a careful balance in maintaining robust and clinically suitable healthcare services 26 , 27 .…”

Section: Why Sustainability Needs To Be Consideredmentioning

confidence: 99%

Considerations for integrating wearables into the everyday healthcare practice

Powell

Godfrey

2023

npj Digit. Med.

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Wearable technologies are becoming ever more popular as suggested tools for use in modern medicine. Studies evidence their growing pragmatism and provision of objective data for a more informative and personalised approach to patient care. Yet many wearables are one dimensional, despite the underlying technology being common across a large array of tools. That is primarily due to the accompanying software, unmodifiable or black box-based scripts that generally lack accessibility or modification, meaning wearables may often get discarded. Use of wearables for sustainable healthcare needs careful consideration.

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“…Another study showed that an autonomous A.I. could reduce GHG emissions by 80% but only compared marginal GHG emissions from one additional diabetic eye exam (Wolf et al, 2022).…”

Section: Erent Perspectives To Reduce Carbon Emissionsmentioning

confidence: 99%

The current state and potential evolution of carbon emissions in the healthcare sector: a narrative review article

Mominkhan,

Alamri,

Balharith

et al. 2023

Front. Sustain. Energy Policy

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Over 98% of the world's greenhouse gas emissions in 2014 came from carbon dioxide (CO2), methane, and nitrous oxide. Over one century, CO2 emissions increased from 3.09 to 37.12 billion metric tons. The healthcare sector is one of the major sources of greenhouse gas emissions. The carbon footprint of a country's healthcare system is influenced by its domestic economy, healthcare expenditure, and energy system. The aim of this study is to present a concise of the present status of carbon emissions within the healthcare sectors on a global scale, as well as the forthcoming endeavors to mitigate these emissions. A narrative review of studies on climate change, carbon emissions, and greenhouse gases in the healthcare sector was conducted using Medline PubMed, Web of Science, Scopus and Google Scholar databases from 2005 to April 2023. According to the data, several countries emit more carbon per capita than others. The Conference of the Parties on Climate Change (COP26) recently encompassed extensive efforts culminating in releasing initiatives toward zero-carbon healthcare sectors. Efforts in some medical practices, smart technology to save energy, digital health, artificial intelligence technology, and monitoring have contributed to reducing carbon emissions. In conclusion, the healthcare sector with zero carbon emissions must be sustainable, adaptable, and efficient while delivering safe, high-quality care. Addressing the sector's carbon footprint requires innovative strategies, a multisector approach, health professionals' participation, community engagement, and regular monitoring of emissions and performance indicators to ensure patient service quality and low carbon emissions in the healthcare sector.

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Potential reduction in healthcare carbon footprint by autonomous artificial intelligence

Cited by 20 publications

References 33 publications

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

Seeing the random forest through the decision trees. Supporting learning health systems from histopathology with machine learning models: Challenges and opportunities

Considerations for integrating wearables into the everyday healthcare practice

The current state and potential evolution of carbon emissions in the healthcare sector: a narrative review article

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