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      How can artificial intelligence impact sustainability: A systematic literature review

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      Journal of Cleaner Production
      Elsevier BV

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          Artificial intelligence in healthcare: past, present and future

          Artificial intelligence (AI) aims to mimic human cognitive functions. It is bringing a paradigm shift to healthcare, powered by increasing availability of healthcare data and rapid progress of analytics techniques. We survey the current status of AI applications in healthcare and discuss its future. AI can be applied to various types of healthcare data (structured and unstructured). Popular AI techniques include machine learning methods for structured data, such as the classical support vector machine and neural network, and the modern deep learning, as well as natural language processing for unstructured data. Major disease areas that use AI tools include cancer, neurology and cardiology. We then review in more details the AI applications in stroke, in the three major areas of early detection and diagnosis, treatment, as well as outcome prediction and prognosis evaluation. We conclude with discussion about pioneer AI systems, such as IBM Watson, and hurdles for real-life deployment of AI.
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            Federated Learning: Challenges, Methods, and Future Directions

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              EnergyPlus: creating a new-generation building energy simulation program

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                Author and article information

                Contributors
                (View ORCID Profile)
                Journal
                Journal of Cleaner Production
                Journal of Cleaner Production
                Elsevier BV
                09596526
                November 2022
                November 2022
                : 376
                : 134120
                Article
                10.1016/j.jclepro.2022.134120
                679cd450-acbb-4fa7-b3b9-6a791cddda2c
                © 2022

                https://www.elsevier.com/tdm/userlicense/1.0/

                https://doi.org/10.15223/policy-017

                https://doi.org/10.15223/policy-037

                https://doi.org/10.15223/policy-012

                https://doi.org/10.15223/policy-029

                https://doi.org/10.15223/policy-004

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