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The need for a system view to regulate artificial intelligence/machine learning-based software as medical device

NPJ digital medicine, 2020-04, Vol.3 (1), p.53-4, Article 53

2020

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A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C

Advances in data analysis and classification, 2020-12, Vol.14 (4), p.801-819

2020

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Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

NeuroImage (Orlando, Fla.), 2018-12, Vol.183, p.504-521

2018

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Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters

Management science, 2013-03, Vol.59 (3), p.613-640

2013

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Direct-to-consumer medical machine learning and artificial intelligence applications

Nature machine intelligence, 2021-04, Vol.3 (4), p.283-287

2021

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Artificial intelligence to support the integration of variable renewable energy sources to the power system

Applied energy, 2021-05, Vol.290, p.116754, Article 116754

2021

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The non-linear nature of the cost of comprehensibility

Journal of big data, 2022-03, Vol.9 (1), p.1-23, Article 30

2022

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How AI can learn from the law: putting humans in the loop only on appeal

NPJ digital medicine, 2023-08, Vol.6 (1), p.160-160, Article 160

2023

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Grit and academic resilience during the COVID-19 pandemic

NPJ science of learning, 2024-09, Vol.9 (1), p.57-10, Article 57

2024

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Support Vector Machines: Theory and Applications

Machine Learning and Its Applications, p.249-257

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Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers

Machine learning, 2004-04, Vol.55 (1), p.71-97

2004

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Convex multi-task feature learning

Machine learning, 2008-12, Vol.73 (3), p.243-272

2008

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Share buybacks and gender diversity

Journal of corporate finance (Amsterdam, Netherlands), 2017-08, Vol.45, p.669-686

2017

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Beware explanations from AI in health care

Science (American Association for the Advancement of Science), 2021-07, Vol.373 (6552), p.284-286

2021

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Uncovering Sparsity and Heterogeneity in Firm-Level Return Predictability Using Machine Learning

Journal of financial and quantitative analysis, 2023-12, Vol.58 (8), p.3384-3419

2023

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Implementation of collaborative e-supply-chain initiatives: an initial challenging and final success case from grocery retailing

Journal of information technology, 2009-09, Vol.24 (3), p.269-281

2009

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Can metafeatures help improve explanations of prediction models when using behavioral and textual data?

Machine learning, 2024-07, Vol.113 (7), p.4245-4284

2024

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Beyond conjoint analysis: Advances in preference measurement

Marketing letters, 2008-12, Vol.19 (3/4), p.337-354

2008

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Algorithms on regulatory lockdown in medicine

Science (American Association for the Advancement of Science), 2019-12, Vol.366 (6470), p.1202-1204

2019

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Mixing User- and Publisher-Generated Content: Quantifying the Spillover Effect of User-Generated Content in a Hybrid Content Environment

Journal of interactive marketing, 2024-08

2024

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Network Centrality and Managerial Market-Timing Ability

Journal of financial and quantitative analysis, 2022-03, Vol.57 (2), p.704-760

2022

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Pandemic lockdown, isolation, and exit policies based on machine learning predictions

Production and operations management, 2023-05, Vol.32 (5), p.1307-1322

2023

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Algorithmovigilance, lessons from pharmacovigilance

NPJ digital medicine, 2024-10, Vol.7 (1), p.270

2024

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Disjunctions of Conjunctions, Cognitive Simplicity, and Consideration Sets

Journal of marketing research, 2010-06, Vol.47 (3), p.485-496

2010

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The European artificial intelligence strategy: implications and challenges for digital health

The Lancet. Digital health, 2020-07, Vol.2 (7), p.e376-e379

2020

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The need for a system view to regulate artificial intelligence/machine learning-based software as medical device

A comparison of instance-level counterfactual explanation algorithms for behavioral and textual data: SEDC, LIME-C and SHAP-C

Reproducible evaluation of classification methods in Alzheimer's disease: Framework and application to MRI and PET data

Dynamic Experiments for Estimating Preferences: An Adaptive Method of Eliciting Time and Risk Parameters

Direct-to-consumer medical machine learning and artificial intelligence applications

Artificial intelligence to support the integration of variable renewable energy sources to the power system

The non-linear nature of the cost of comprehensibility

How AI can learn from the law: putting humans in the loop only on appeal

Grit and academic resilience during the COVID-19 pandemic

Support Vector Machines: Theory and Applications

Leave One Out Error, Stability, and Generalization of Voting Combinations of Classifiers

Convex multi-task feature learning

Share buybacks and gender diversity

Beware explanations from AI in health care

Uncovering Sparsity and Heterogeneity in Firm-Level Return Predictability Using Machine Learning

Implementation of collaborative e-supply-chain initiatives: an initial challenging and final success case from grocery retailing

Can metafeatures help improve explanations of prediction models when using behavioral and textual data?

Beyond conjoint analysis: Advances in preference measurement

Algorithms on regulatory lockdown in medicine

Mixing User- and Publisher-Generated Content: Quantifying the Spillover Effect of User-Generated Content in a Hybrid Content Environment

Network Centrality and Managerial Market-Timing Ability

Pandemic lockdown, isolation, and exit policies based on machine learning predictions

Algorithmovigilance, lessons from pharmacovigilance

Disjunctions of Conjunctions, Cognitive Simplicity, and Consideration Sets

The European artificial intelligence strategy: implications and challenges for digital health

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