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furm [2024/03/05 09:17] nigam |
furm [2024/03/13 21:39] (current) nigam |
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The impact of using artificial intelligence (AI) to guide patient care or operational processes is an interplay of the AI model’s output, the decision-making protocol based on that output, and the capacity of the stakeholders involved to take the necessary subsequent action. Estimating the effects of this interplay before deployment, and studying it in real time afterwards, are essential to bridge the chasm between AI model development and achievable benefit. To accomplish this, the Data Science team at Stanford Health Care has developed a mechanism to identify fair, useful and reliable AI models (FURM) by conducting an ethical review to identify potential value mismatches, simulations to estimate usefulness, financial projections to assess sustainability, | The impact of using artificial intelligence (AI) to guide patient care or operational processes is an interplay of the AI model’s output, the decision-making protocol based on that output, and the capacity of the stakeholders involved to take the necessary subsequent action. Estimating the effects of this interplay before deployment, and studying it in real time afterwards, are essential to bridge the chasm between AI model development and achievable benefit. To accomplish this, the Data Science team at Stanford Health Care has developed a mechanism to identify fair, useful and reliable AI models (FURM) by conducting an ethical review to identify potential value mismatches, simulations to estimate usefulness, financial projections to assess sustainability, | ||
- | * arxiv doi – //in progress// \\ | + | * arxiv doi – http://arxiv.org/abs/2403.07911 |
- | * file – {{: | + | * direct link to pdf - https:// |
* Underlying tools - https:// | * Underlying tools - https:// | ||