Probabilistic Machine Learning for Healthcare

Chen, Irene Y.; Joshi, Shalmali; Ghassemi, Marzyeh; Ranganath, Rajesh

doi:10.48550/arxiv.2009.11087

Cited by 2 publications

(2 citation statements)

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“…On the other end of the spectrum of learning there are two mostly prominent and presently popular, successful, and widely implemented classes of pure AI/Digital learnings models, specifically Machine learning and Deep learning (for their application in economics and for other advanced methods see [127]; for application in agriculture see [128]; for application in logistics see [129]; for application in healthcare see [130]), which are now generally recognized as 'general purpose technologies' [131] (see Figure 6b).…”

Section: Learningmentioning

confidence: 99%

Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models

Russ

2021

Sustainability

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This conceptual, interdisciplinary paper will start by introducing the commencement of a new era in which human society faces continuously accelerating technological revolutions, named the Post Accelerating Data and Knowledge Online Society, or ‘Padkos’ (“food for the journey; prog; provisions for journey”—in Afrikaans) for short. In this context, a conceptual model of sustainable development with a focus on knowledge management and sharing will be proposed. The construct of knowledge management will be unpacked into a new three-layer model with a focus on the knowledge-human and data-machine spheres. Then, each sphere will be discussed with concentration on the learning and decision- making processes, the digital supporting systems and the human actors’ aspects. Moreover, the recombination of new knowledge development and contemporary knowledge management into one amalgamated construct will be proposed. The holistic conceptual model of knowledge management for sustainable development is comprised by time, cybersecurity and two alternative humanistic paradigms (Homo Technologicus and Homo Sustainabiliticus). Two additional particular models are discussed in depth. First, a recently proposed model of quantum organizational decision-making is elaborated. Next, a boundary management and learning process is deliberated. The paper ends with a number of propositions and several implications for the future based on the deliberations in the paper and the models discussed and with conclusions.

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Section: Learningmentioning

confidence: 99%

Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models

Russ

2021

Sustainability

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“…The only research that I'm aware of that approaches the question of performative prediction in the context of medical AI is a review article(Chen et al 2021); there, the authors simply note the possibility of distributional shift (aka performative prediction).22 Thanks to an anonymous referee for encouraging clarity on this point.…”

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confidence: 99%

Predicting and preferring

Sharadin

2023

Inquiry

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The use of machine learning, or "artificial intelligence" (AI) in medicine is widespread and growing. In this paper, I focus on a specific proposed clinical application of AI: using models to predict incapacitated patients' treatment preferences. Drawing on results from machine learning, I argue this proposal faces a special moral problem. Machine learning researchers owe us assurance on this front before experimental research can proceed. In my conclusion I connect this concern to broader issues in AI safety.

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Probabilistic Machine Learning for Healthcare

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Cited by 2 publications

References 82 publications

Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models

Knowledge Management for Sustainable Development in the Era of Continuously Accelerating Technological Revolutions: A Framework and Models

Predicting and preferring

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