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Automated Detection of Glaucoma With Interpretable Machine Learning Using Clinical Data and Multimodal Retinal Images
Mehta, Parmita, Petersen, Christine A., Wen, Joanne C., Banitt, Michael R., Chen, Philip P., Bojikian, Karine D., Egan, Catherine, Lee, Su-In, Balazinska, Magdalena, Lee, Aaron Y., Rokem, Ariel
Published in American journal of ophthalmology (01.11.2021)
Published in American journal of ophthalmology (01.11.2021)
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Development and Validation of Interpretable Machine Learning Models for Clinically Significant Prostate Cancer Diagnosis in Patients With Lesions of PI‐RADS v2.1 Score ≥3
Ruan, Mingjian, Liu, Yi, Yao, Kaifeng, Wang, Kexin, Fan, Yu, Wu, Shiliang, Wang, Xiaoying
Published in Journal of magnetic resonance imaging (01.11.2024)
Published in Journal of magnetic resonance imaging (01.11.2024)
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Progress Toward Interpretable Machine Learning-Based Disruption Predictors Across Tokamaks
Rea, C., Montes, K. J., Pau, A., Granetz, R. S., Sauter, O.
Published in Fusion science and technology (16.11.2020)
Published in Fusion science and technology (16.11.2020)
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Classification by ordinal sums of conjunctive and disjunctive functions for explainable AI and interpretable machine learning solutions
Hudec, Miroslav, Mináriková, Erika, Mesiar, Radko, Saranti, Anna, Holzinger, Andreas
Published in Knowledge-based systems (23.05.2021)
Published in Knowledge-based systems (23.05.2021)
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Interpretable machine learning-based predictive modeling of patient outcomes following cardiac surgery
Abbasi, Adeel, Li, Cindy, Dekle, Max, Bermudez, Christian A., Brodie, Daniel, Sellke, Frank W., Sodha, Neel R., Ventetuolo, Corey E., Eickhoff, Carsten
Published in The Journal of thoracic and cardiovascular surgery (01.01.2025)
Published in The Journal of thoracic and cardiovascular surgery (01.01.2025)
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Actionable Explainable AI (AxAI): A Practical Example with Aggregation Functions for Adaptive Classification and Textual Explanations for Interpretable Machine Learning
Saranti, Anna, Hudec, Miroslav, Mináriková, Erika, Takáč, Zdenko, Großschedl, Udo, Koch, Christoph, Pfeifer, Bastian, Angerschmid, Alessa, Holzinger, Andreas
Published in Machine learning and knowledge extraction (01.12.2022)
Published in Machine learning and knowledge extraction (01.12.2022)
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Development and validation of 10‐year risk prediction models of cardiovascular disease in Chinese type 2 diabetes mellitus patients in primary care using interpretable machine learning‐based methods
Dong, Weinan, Wan, Eric Yuk Fai, Fong, Daniel Yee Tak, Tan, Kathryn Choon‐Beng, Tsui, Wendy Wing‐Sze, Hui, Eric Ming‐Tung, Chan, King Hong, Fung, Colman Siu Cheung, Lam, Cindy Lo Kuen
Published in Diabetes, obesity & metabolism (01.09.2024)
Published in Diabetes, obesity & metabolism (01.09.2024)
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An interpretable machine learning model for diagnosis of Alzheimer's disease
Das, Diptesh, Ito, Junichi, Kadowaki, Tadashi, Tsuda, Koji
Published in PeerJ (San Francisco, CA) (01.03.2019)
Published in PeerJ (San Francisco, CA) (01.03.2019)
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Interpretable machine learning model for imaging-based outcome prediction after cardiac arrest
Liu, Chang, Elmer, Jonathan, Arefan, Dooman, Pease, Matthew, Wu, Shandong
Published in Resuscitation (01.10.2023)
Published in Resuscitation (01.10.2023)
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Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture
Štajduhar, Andrija, Lipić, Tomislav, Lončarić, Sven, Judaš, Miloš, Sedmak, Goran
Published in Scientific reports (05.04.2023)
Published in Scientific reports (05.04.2023)
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Analysis of the Outcome of the Driving Test for Learner Drivers Based on an Interpretable Machine Learning Framework
Ding, Yang, Zhao, Xiaohua, Yao, Ying, He, Chenxi, Chai, Rui, Liu, Shuo
Published in Transportation research record (01.11.2024)
Published in Transportation research record (01.11.2024)
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Evaluating Familiarity Ratings of Domain Concepts with Interpretable Machine Learning: A Comparative Study
Huang, Jingxiu, Wu, Xiaomin, Wen, Jing, Huang, Chenhan, Luo, Mingrui, Liu, Lixiang, Zheng, Yunxiang
Published in Applied sciences (01.12.2023)
Published in Applied sciences (01.12.2023)
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Development and validation of an interpretable machine learning-based calculator for predicting 5-year weight trajectories after bariatric surgery: a multinational retrospective cohort SOPHIA study
Saux, Patrick, Bauvin, Pierre, Raverdy, Violeta, Teigny, Julien, Verkindt, Hélène, Soumphonphakdy, Tomy, Debert, Maxence, Jacobs, Anne, Jacobs, Daan, Monpellier, Valerie, Lee, Phong Ching, Lim, Chin Hong, Andersson-Assarsson, Johanna C, Carlsson, Lena, Svensson, Per-Arne, Galtier, Florence, Dezfoulian, Guelareh, Moldovanu, Mihaela, Andrieux, Severine, Couster, Julien, Lepage, Marie, Lembo, Erminia, Verrastro, Ornella, Robert, Maud, Salminen, Paulina, Mingrone, Geltrude, Peterli, Ralph, Cohen, Ricardo V, Zerrweck, Carlos, Nocca, David, Le Roux, Carel W, Caiazzo, Robert, Preux, Philippe, Pattou, François
Published in The Lancet. Digital health (01.10.2023)
Published in The Lancet. Digital health (01.10.2023)
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