Dissecting scientific explanation in AI (sXAI): A case for medicine and healthcare
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Combining explainability of algorithms with privacy-preserving methods such as federated learning might help address privacy and security implications of XAI.
“Combining explainability of algorithms with privacy-preserving methods such as federated learning [27] might help.”
From Explainable Artificial Intelligence (XAI): Concepts and Challenges in Healthcare (2023) · cites this paper as [27]
Cites
Dermatologist-level classification of skin cancer with deep neural networks
Esteva, A., Kuprel, B., Novoa, R. A., Ko, J., Swetter, S. M., Blau, H. M., & Thrun, S. (2017) · Nature · doi:10.1038/nature21056 · Cited by 14,362 · see citing works
Rudin, C. (2019) · Nature Machine Intelligence · doi:10.1038/s42256-019-0048-x · Cited by 10,561 · see citing works
Stanford Encyclopedia of Philosophy
(2015) · Choice Reviews Online · doi:10.5860/choice.187763 · Cited by 5,364 · see citing works
A guide to deep learning in healthcare
Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., Cui, C., Corrado, G., Thrun, S., & Dean, J. (2019) · Nature Medicine · doi:10.1038/s41591-018-0316-z · Cited by 5,312 · see citing works
CAUSALITY: MODELS, REASONING AND INFERENCE
Hitchcock, C., & Pearl, J. (2001) · The Philosophical Review · doi:10.2307/3182612 · Cited by 4,824 · see citing works
Vannieuwenhoven, N. (2020) · McGill-Queen's University Press eBooks · doi:10.2307/j.ctvw1d7dg.9 · Cited by 3,392 · see citing works
Aspects of Scientific Explanation.
Resnik, M. D., & Hempel, C. G. (1966) · Philosophy and Phenomenological Research · doi:10.2307/2106169 · Cited by 3,331 · see citing works
Machamer, P., Darden, L., & Craver, C. F. (2000) · Philosophy of Science · doi:10.1086/392759 · Cited by 3,179 · see citing works
Towards A Rigorous Science of Interpretable Machine Learning
Doshi-Velez, F., & Kim, B. (2017) · arXiv · doi:10.48550/arxiv.1702.08608 · Cited by 3,121 · see citing works
Causality: models, reasoning, and inference
(2000) · Choice Reviews Online · doi:10.5860/choice.38-1494a · Cited by 2,969 · see citing works
Scientific Explanation and the Causal Structure of the World
Salmon, W. C. (1985) · Princeton University Press eBooks · doi:10.1515/9780691221489 · Cited by 2,484 · see citing works
Scientific Explanation and the Causal Structure of the World
Salmon, W. C. (2020) · Princeton University Press eBooks · doi:10.2307/j.ctv173f2gh · Cited by 1,992 · see citing works
Causability and explainability of artificial intelligence in medicine
Holzinger, A., Langs, G., Denk, H., Zatloukal, K., & Müller, H. (2019) · WIREs Data Mining and Knowledge Discovery · doi:10.1002/widm.1312 · Cited by 1,885 · see citing works
Stanford Encyclopedia of Philosophy
Wahlberg, L. (2017) · Lund University Publications (Lund University) · Cited by 1,854 · see citing works
Health as a Theoretical Concept
Boorse, C. (1977) · Philosophy of Science · doi:10.1086/288768 · Cited by 1,786 · see citing works
Causal Inference in Statistics
Pearl, J., Glymour, M., & Jewell, N. P. (2016) · Cited by 1,436 · see citing works
Kitcher, P. (1981) · Philosophy of Science · doi:10.1086/289019 · Cited by 1,138 · see citing works
Samek, W., Wiegand, T., & Müller, K.-R. (2017) · arXiv · doi:10.48550/arxiv.1708.08296 · Cited by 1,080 · see citing works
Artificial intelligence, bias and clinical safety
Challen, R., Denny, J., Pitt, M., Gompels, L., Edwards, T., & Tsaneva-Atanasova, K. (2019) · BMJ Quality & Safety · doi:10.1136/bmjqs-2018-008370 · Cited by 956 · see citing works
Bogen, J., & Woodward, J. (1988) · The Philosophical Review · doi:10.2307/2185445 · Cited by 943 · see citing works
Explanatory unification and the causal structure of the world
Kitcher, P. (1989) · University of Minnesota Digital Conservancy (University of Minnesota) · Cited by 938 · see citing works
Interactive machine learning for health informatics: when do we need the human-in-the-loop?
Holzinger, A. (2016) · Brain Informatics · doi:10.1007/s40708-016-0042-6 · Cited by 906 · see citing works
Salmon, W. C. (1998) · doi:10.1093/0195108647.001.0001 · Cited by 854 · see citing works
Mittelstadt, B., Russell, C., & Wachter, S. (2019) · Proceedings of the Conference on Fairness, Accountability, and Transparency · doi:10.1145/3287560.3287574 · Cited by 794 · see citing works
Science, policy, and the value-free ideal
Douglas, H., & Project Muse (2009) · Choice Reviews Online · doi:10.5860/choice.47-1955 · Cited by 768 · see citing works
Lepri, B., Oliver, N., Letouzé, E., Pentland, A., & Vinck, P. (2018) · Philosophy & Technology · doi:10.1007/s13347-017-0279-x · Cited by 709 · see citing works
Salmon, W. C. (1998) · Choice Reviews Online · doi:10.5860/choice.35-6187 · Cited by 655 · see citing works
Machine Learning and Health Care Disparities in Dermatology
Adamson, A. S., & Smith, A. (2018) · JAMA Dermatology · doi:10.1001/jamadermatol.2018.2348 · Cited by 639 · see citing works
A Survey of Methods for Explaining Black Box Models
Guidotti, R., Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., & Pedreschi, D. (2019) · ACM Computing Surveys · doi:10.1145/3236009 · Cited by 629 · see citing works
Metaphysical Grounding: Understanding the Structure of Reality
Correia, F., & Schnieder, B. S. (2012) · Cited by 622 · see citing works
Discovery and explanation in biology and medicine
(1994) · Choice Reviews Online · doi:10.5860/choice.32-0909 · Cited by 606 · see citing works
Meaningful Human Control over Autonomous Systems: A Philosophical Account
Santoni de Sio, F., & van den Hoven, J. (2018) · Frontiers in Robotics and AI · doi:10.3389/frobt.2018.00015 · Cited by 566 · see citing works
Extending ourselves: computational science, empiricism, and scientific method
(2005) · Choice Reviews Online · doi:10.5860/choice.43-0272 · Cited by 487 · see citing works
Gilgun, J. F. (2002) · Qualitative Social Work · doi:10.1177/147332500200100309 · Cited by 483 · see citing works
Durán, J. M., & Jongsma, K. R. (2021) · Journal of Medical Ethics · doi:10.1136/medethics-2020-106820 · Cited by 446 · see citing works
Self-citationHolzinger, A., Carrington, A., & Müller, H. (2020) · KI - Künstliche Intelligenz · doi:10.1007/s13218-020-00636-z · Cited by 406 · see citing works
No understanding without explanation
Strevens, M. (2013) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2012.12.005 · Cited by 359 · see citing works
Causal–explanatory pluralism: How intentions, functions, and mechanisms influence causal ascriptions
Lombrozo, T. (2010) · Cognitive Psychology · doi:10.1016/j.cogpsych.2010.05.002 · Cited by 315 · see citing works
Achinstein, P. (1983) · Cited by 301 · see citing works
Program verification: the very idea
Fetzer, J. H. (1988) · Communications of the ACM · doi:10.1145/48529.48530 · Cited by 294 · see citing works
Ylikoski, P., & Kuorikoski, J. (2008) · Philosophical Studies · doi:10.1007/s11098-008-9324-z · Cited by 280 · see citing works
One Explanation Does Not Fit All: A Toolkit and Taxonomy of AI Explainability Techniques
Arya, V., Bellamy, R. K. E., Chen, P.-Y., Dhurandhar, A., Hind, M., Hoffman, S. C., Houde, S., Liao, Q. V., Luss, R., Mojsilović, A., et al. (2019) · arXiv · doi:10.48550/arxiv.1909.03012 · Cited by 268 · see citing works
Embedding Values in Artificial Intelligence (AI) Systems
van de Poel, I. (2020) · Minds and Machines · doi:10.1007/s11023-020-09537-4 · Cited by 255 · see citing works
Information processing, computation, and cognition
Piccinini, G., & Scarantino, A. (2010) · Journal of Biological Physics · doi:10.1007/s10867-010-9195-3 · Cited by 241 · see citing works
Reconstructing reality: models, mathematics, and simulations
(2015) · Choice Reviews Online · doi:10.5860/choice.190914 · Cited by 236 · see citing works
The Pragmatic Turn in Explainable Artificial Intelligence (XAI)
Páez, A. (2019) · Minds and Machines · doi:10.1007/s11023-019-09502-w · Cited by 229 · see citing works
Causality in Crisis? Statistical Methods and the Search for Causal Knowledge in the Social Sciences
Stinchcombe, A. L., McKim, V. R., & Turner, S. P. (1998) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2654303 · Cited by 214 · see citing works
Kolko, J. (2017) · doi:10.1007/1-4020-3907-7 · Cited by 200 · see citing works
Artificial Intelligence in Skin Cancer Diagnostics: The Patients' Perspective
Jutzi, T. B., Krieghoff-Henning, E. I., Holland-Letz, T., Utikal, J. S., Hauschild, A., Schadendorf, D., Sondermann, W., Fröhling, S., Hekler, A., Schmitt, M., et al. (2020) · Frontiers in Medicine · doi:10.3389/fmed.2020.00233 · Cited by 196 · see citing works
The Logic of Explanatory Power
Schupbach, J. N., & Sprenger, J. (2011) · Philosophy of Science · doi:10.1086/658111 · Cited by 186 · see citing works
Kitcher, P., & Salmon, W. C. (1987) · The Journal of Philosophy · doi:10.2307/2026782 · Cited by 179 · see citing works
(1991) · Choice Reviews Online · doi:10.5860/choice.28-5038 · Cited by 165 · see citing works
The Routledge Companion to Philosophy of Medicine
Schües, C. (2016) · Routledge eBooks · doi:10.4324/9781315720739 · Cited by 164 · see citing works
Automated Inference on Criminality using Face Images.Preprint
Wu, X., & Zhang, X. (2016) · arXiv (Cornell University) · Cited by 152 · see citing works
Robustness Analysis as Explanatory Reasoning
Schupbach, J. N. (2016) · The British Journal for the Philosophy of Science · doi:10.1093/bjps/axw008 · Cited by 143 · see citing works
Grounds for Trust: Essential Epistemic Opacity and Computational Reliabilism
Durán, J. M., & Formanek, N. (2018) · Minds and Machines · doi:10.1007/s11023-018-9481-6 · Cited by 138 · see citing works
Self-citationAccuracy of Computer-Aided Diagnosis of Melanoma: A Meta-analysis
Dick, V., Sinz, C., Mittlböck, M., Kittler, H., & Tschandl, P. (2019) · JAMA Dermatology · doi:10.1001/jamadermatol.2019.1375 · Cited by 125 · see citing works
WHO recommendations on the diagnosis of HIV infection in infants and children
MOFENSON, L. M., Sherman, G. G., Penazzato, M., et al. (2010) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-110368 · Cited by 112 · see citing works
Models of Success Versus the Success of Models: Reliability without Truth
Winsberg, E. B. (2006) · Synthese · doi:10.1007/s11229-004-5404-6 · Cited by 83 · see citing works
The Pragmatic Turn in Explainable Artificial Intelligence (XAI)
Páez, A. (2019) · PhilPapers (PhilPapers Foundation) · Cited by 80 · see citing works
(2008) · Cambridge University Press eBooks · doi:10.1017/cbo9780511814273 · Cited by 79 · see citing works
How could models possibly provide how-possibly explanations?
Verreault-Julien, P. (2018) · Studies in History and Philosophy of Science Part A · doi:10.1016/j.shpsa.2018.06.008 · Cited by 74 · see citing works
Causes without Mechanisms: Experimental Regularities, Physical Laws, and Neuroscientific Explanation
Weber, M. (2008) · Philosophy of Science · doi:10.1086/594541 · Cited by 71 · see citing works
Philosophy and Computer Science
Colburn, T. R. (2015) · Routledge eBooks · doi:10.4324/9781315701769 · Cited by 64 · see citing works
Computer Simulations in Science and Engineering
Durán, J. M. (2018) · The frontiers collection · doi:10.1007/978-3-319-90882-3 · Cited by 60 · see citing works
Self-citationReasoning: studies of human inference and its foundations
(2009) · Choice Reviews Online · doi:10.5860/choice.46-2593 · Cited by 54 · see citing works
Ethics and the Metaphysics of Medicine
Richman, K. A. (2004) · The MIT Press eBooks · doi:10.7551/mitpress/2840.001.0001 · Cited by 53 · see citing works
Hamilton, J. G., Garzon, M. G., Westerman, J. S., Shuk, E., Hay, J. L., Walters, C. B., Elkin, E. B., Bertelsen, C., Cho, J. S., Daly, B., et al. (2019) · Journal of Oncology Practice · doi:10.1200/jop.18.00417 · Cited by 50 · see citing works
On the Foundations of Computing
Primiero, G. (2019) · Oxford University Press eBooks · doi:10.1093/oso/9780198835646.001.0001 · Cited by 48 · see citing works
Philosophy and Computer Science
Fetzer, J. H. (2001) · Studies in cognitive systems · doi:10.1007/978-94-010-0973-7_10 · Cited by 45 · see citing works
Open the Black Box Data-Driven Explanation of Black Box Decision SystemsPreprint
Pedreschi, D., Giannotti, F., Guidotti, R., Monreale, A., Pappalardo, L., Ruggieri, S., & Turini, F. (2018) · arXiv.org · doi:10.48550/arxiv.1806.09936 · Cited by 39 · see citing works
Mantzavinos, C. (2015) · Elsevier eBooks · doi:10.1016/b978-0-08-097086-8.63100-8 · Cited by 39 · see citing works
Computers, Justification, and Mathematical Knowledge
Arkoudas, K., & Bringsjord, S. (2007) · Minds and Machines · doi:10.1007/s11023-007-9063-5 · Cited by 33 · see citing works
Hontela, S. (1987) · PubMed · Cited by 31 · see citing works
What do patterns in empirical data tell us about the structure of the world?
McAllister, J. W. (2009) · Synthese · doi:10.1007/s11229-009-9613-x · Cited by 26 · see citing works
Cloud Computing Systems and Applications in Healthcare
Bhatt, C., & Peddoju, S. K. (2016) · Advances in healthcare information systems and administration book series · doi:10.4018/978-1-5225-1002-4 · Cited by 24 · see citing works
Understanding Programming Languages
Turner, R. (2007) · Minds and Machines · doi:10.1007/s11023-007-9062-6 · Cited by 21 · see citing works
Varying the Explanatory Span: Scientific Explanation for Computer Simulations
Durán, J. M. (2017) · International Studies in the Philosophy of Science · doi:10.1080/02698595.2017.1370929 · Cited by 19 · see citing works
Self-citationHealth of Organisms and Health of Persons: An Embedded Instrumentalist Approach
Richman, K. A., & Budson, A. E. (2000) · Metamedicine · doi:10.1023/a:1009994806758 · Cited by 13 · see citing works
A Practical Guide to Skin Cancer
(2018) · Springer eBooks · doi:10.1007/978-3-319-74903-7 · Cited by 10 · see citing works
Computer simulations in science and engineering - Concepts - Practices - PerspectivesPreprint
Durán, J. M. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1904.01053 · Cited by 9 · see citing works
Self-citationExplaining simulated phenomena : a defense of the epistemic power of computer simulations
Durán, J. M. (2014) · OPUS Publication Server of the University of Stuttgart (University of Stuttgart) · doi:10.18419/opus-5392 · Cited by 5 · see citing works
Self-citationReiss, J., & Ankeny, R. A. (2016) · Cited by 5 · see citing works
Causality and Causal Inference in Medicine
Reiss, J. (2016) · doi:10.4324/9781315720739.ch6 · Cited by 5 · see citing works
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Explainable Artificial Intelligence (XAI): Concepts and Challenges in Healthcare
Hulsen, T. (2023) · AI · doi:10.3390/ai4030034 · Cited by 305 · see citing works
Explainability in medicine in an era of AI-based clinical decision support systems
Pierce, R. L., Van Biesen, W., Van Cauwenberge, D., Decruyenaere, J., & Sterckx, S. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.903600 · Cited by 95 · see citing works
- Authors
- Durán, J. M.
- Affiliations
- Delft University of Technology (NL)
- Corresponding author
- Durán, Juan M.
- ORCID
- Durán, Juan M.
- Venue
- Artificial Intelligence
- Publisher
- Elsevier BV
- Published
- 2021-08
- Volume
- 297
- Pages
- 103498
- ISSN
- 0004-3702 (ISSN-L)
- OpenAlex
- W3137844837
- Cited by
- 62
- References
- 84
- Citations by year
- 2026: 4 · 2025: 17 · 2024: 18 · 2023: 13 · 2022: 9 · 2021: 1
- FWCI
- 3.62
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.elsevier.com/tdm/userlicense/1.0/ (tdm)
- www.elsevier.com/legal/tdmrep-license (tdm)
- www.elsevier.com/open-access/userlicense/1.0/ (vor, 1461 d)
- doi.org/10.15223/policy-017 (stm-asf)
- doi.org/10.15223/policy-037 (stm-asf)
- doi.org/10.15223/policy-012 (stm-asf)
- doi.org/10.15223/policy-029 (stm-asf)
- doi.org/10.15223/policy-004 (stm-asf)
- Locations
- Artificial Intelligence (publishedVersion)
- Funders
- European Commission
- Netherlands Institute for Advanced Study in the Humanities and Social Sciences
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Explainable Artificial Intelligence (XAI)
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Philosophy and History of Science
- Social Sciences › Safety Research › Ethics and Social Impacts of AI
- Keywords
- scientific explanation, explainable AI, artificial intelligence in healthcare, health care, explanatory power, theory of explanation, explanatory relations
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