Interpretable Machine Learning In Healthcare

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Interpretable Machine Learning in Healthcare IEEE Conference

(5 days ago) WebThis tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models and systems in healthcare. We discuss many uses in which interpretable machine …

https://ieeexplore.ieee.org/document/8419428/

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Interpretable Machine Learning in Healthcare - Google Sites

(3 days ago) WebApplying machine learning (ML) in healthcare is gaining momentum rapidly. However, the black-box characteristics of the existing ML approach inevitably lead to less …

https://sites.google.com/view/imlh2023/home

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Designing interpretable ML system to enhance trust in healthcare: …

(7 days ago) WebInherently interpretable machine learning models (White-Box) The traditional approach to implementing interpretable models involves selecting White-Box methods like DT and …

https://www.sciencedirect.com/science/article/pii/S1566253524001908

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(PDF) Interpretable Machine Learning in Healthcare

(5 days ago) WebInterpretable Machine Learning in Healthcare. Muhammad Aurangzeb Ahmad, Carly Eckert, Ankur T eredesai, and Greg McKelve …

https://www.researchgate.net/publication/328416903_Interpretable_Machine_Learning_in_Healthcare

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Explainable and interpretable artificial intelligence in medicine: a

(Just Now) WebThis review aims to explore the growing impact of machine learning and deep learning algorithms in the medical field, with a specific focus on the critical issues …

https://link.springer.com/article/10.1007/s44163-024-00114-7

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Interpretability of machine learning‐based prediction models in …

(3 days ago) WebThere is a need of ensuring that learning (ML) models are interpretable. Higher interpretability of the model means easier comprehension and explanation of …

https://wires.onlinelibrary.wiley.com/doi/abs/10.1002/widm.1379

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Interpretable Machine Learning: Moving from mythos to diagnostics

(8 days ago) WebAbstract. The emergence of machine learning as a society-changing technology in the past decade has triggered concerns about people's inability to …

https://dl.acm.org/doi/10.1145/3511299

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Interpretable Machine Learning in Healthcare - Semantic Scholar

(9 days ago) WebThe landscape of recent advances to address the challenges model interpretability in healthcare and also how one would go about choosing the right …

https://www.semanticscholar.org/paper/Interpretable-Machine-Learning-in-Healthcare-Ahmad-Teredesai/7d065e649e3bfc7d6d36166f50eab37b8404eae0

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Techniques for interpretable machine learning Communications …

(8 days ago) WebThis tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models …

https://dl.acm.org/doi/10.1145/3359786

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Interpretability of machine learning‐based prediction models …

(2 days ago) WebThe machine learning (ML) systems have shown a great success in analysis of complex patterns (Murdoch, Singh, Kumbier, Abbasi-Asl, & Yu, 2018) and are present in a wide …

https://zitniklab.hms.harvard.edu/publications/papers/interpretableML-survey20.pdf

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Interpretable Machine Learning in Healthcare - IEEE Computer …

(2 days ago) WebThis tutorial extensively covers the definitions, nuances, challenges, and requirements for the design of interpretable and explainable machine learning models and systems in …

https://www.computer.org/csdl/proceedings-article/ichi/2018/537701a447/12OmNApu5y9

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Multiple stakeholders drive diverse interpretability - Nature

(Just Now) WebApplications of machine learning are becoming increasingly common in medicine and healthcare, enabling more accurate predictive models. However, this often …

https://www.nature.com/articles/s42256-023-00698-2

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Symmetry Free Full-Text A Review of Interpretable ML in …

(1 days ago) WebThe development of interpretable machine learning models in healthcare has recently become a trending research area to overcome the barriers in applying …

https://www.mdpi.com/2073-8994/13/12/2439

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Explainable AI for Healthcare: From Black Box to Interpretable …

(Just Now) WebXAI initiatives in order to identify potential projections in healthcare. 3 Explainable AI 3.1 Emergence of XAI XAI is a research field that aims to make AI systems results more …

https://link.springer.com/content/pdf/10.1007/978-981-15-0947-6_31.pdf

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Interpretable Machine Learning in Healthcare through Generalized

(4 days ago) WebWe have investigated the risk factors that lead to severe retinopathy of prematurity using statistical analysis and logistic regression as a form of generalized additive model (GAM) …

https://ieeexplore.ieee.org/document/8876951

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Interpretability of Machine Learning Solutions in Public Healthcare

(3 days ago) WebPublic healthcare has a history of cautious adoption for artificial intelligence (AI) systems. The rapid growth of data collection and linking capabilities combined with …

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187858/

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Interpretable Machine Learning in Healthcare

(7 days ago) Webpredictions, interpretable machine learning systems give users reasons to accept or reject predictions and recommendations. Audits of machine learning systems in domains like …

https://www.comp.hkbu.edu.hk/~iib/2018/Aug/article1/iib_vol19no1_article1.pdf

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Machine learning in healthcare - Nature

(5 days ago) WebClinical implementations of machine learning that are accurate, robust and interpretable will eventually gain the trust of healthcare providers and patients. Editorial …

https://www.nature.com/collections/zbkpvddmhm

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Abstract - arXiv.org

(6 days ago) WebAs machine learning has matured into wide-spread adoption, building models that users can Carly Eckert, and Ankur Teredesai. Interpretable machine learning in …

https://arxiv.org/pdf/1909.09223.pdf

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Interpretability of machine learning based prediction models …

(2 days ago) WebThe machine learning (ML) systems have shown a great success in analysis of complex patterns (Murdoch, et al., 2018) and are present in a wide range of applications in …

https://arxiv.org/pdf/2002.08596

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