An Empirical Comparison of Interpretable Models to Post-Hoc Explanations by Parisa Mahya, Johannes Fürnkranz

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A Mass Conservation Relaxed (MCR) LSTM Model for Streamflow Simulation Across CONUS by Yihan Wang, Lujun Zhang, N. Benjamin Erichson, Tiantian Yang

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TorchSISSO: A PyTorch-based implementation of the sure independence screening and sparsifying operator for efficient and interpretable model discovery by Madhav Muthyala, Farshud Sorourifar, Joel A. Paulson

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From explainable to interpretable deep learning for natural language processing in healthcare: How far from reality? by Guangming Huang, Yingya Li, Shoaib Jameel, Yunfei Long, Giorgos Papanastasiou

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Interpretable survival network for progression risk analysis of multimodality imaging biomarkers in poor-prognosis head and neck cancers by Lise Wei, Madhava P. Aryal, Choonik Lee, Jennifer L. Shah, Michelle L. Mierzwa, Yue Cao

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An interpretable survival model for diffuse large B-cell lymphoma patients using a biologically informed visible neural network by Jie Tan, Jiancong Xie, Jiarong Huang, Weizhen Deng, Hua Chai, Yuedong Yang

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Interpretable Combinatorial Machine Learning-Based Shale Fracability Evaluation Methods by Di Wang, Dingyu Jiao, Zihang Zhang, Runze Zhou, Weize Guo, Huai Su

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Interpretable deep learning to uncover the molecular binding patterns determining TCR–epitope interaction predictions by Ceder Dens, Wout Bittremieux, Fabio Affaticati, Kris Laukens, Pieter Meysman

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Genome-wide association studies of ischemic stroke based on interpretable machine learning by Stefan Nikolić, Dmitry I. Ignatov, Gennady V. Khvorykh, Svetlana A. Limborska, Andrey V. Khrunin

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Target Material Property‐Dependent Cluster Analysis of Inorganic Compounds by Nobuya Sato, Akira Takahashi, Shin Kiyohara, Kei Terayama, Ryo Tamura, Fumiyasu Oba

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Interpretable machine learning for predicting sepsis risk in emergency triage patients by Zheng Liu, Wenqi Shu, Teng Li, Xuan Zhang, Wei Chong

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Predicting stroke severity of patients using interpretable machine learning algorithms by Amir Sorayaie Azar, Tahereh Samimi, Ghanbar Tavassoli, Amin Naemi, Bahlol Rahimi, Zahra Hadianfard, Uffe Kock Wiil, Surena Nazarbaghi, Jamshid Bagherzadeh Mohasefi, Hadi Lotfnezhad Afshar

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Explainable AI (XAI) in image segmentation in medicine, industry, and beyond: A survey by Rokas Gipiškis, Chun-Wei Tsai, Olga Kurasova

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An Interpretable Machine Learning Procedure Which Unravels Hidden Interplanetary Drivers of the Low Latitude Dayside Magnetopause by Sheng Li, Yang‐Yi Sun, Chieh‐Hung Chen

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A Novel Approach for Model Interpretability and Domain Aware Fine-Tuning in AdaBoost by Raj Joseph Kiran, J. Sanil, S. Asharaf

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A multi-objective, multi-interpretable machine learning demonstration verified by domain knowledge for ductile thermoelectric materials by Xiangdong Wang, Yan Cao, Jialin Ji, Ye Sheng, Jiong Yang, Xuezhi Ke

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CIME4R: Exploring iterative, AI-guided chemical reaction optimization campaigns in their parameter space by Christina Humer, Rachel Nicholls, Henry Heberle, Moritz Heckmann, Michael Pühringer, Thomas Wolf, Maximilian Lübbesmeyer, Julian Heinrich, Julius Hillenbrand, Giulio Volpin, Marc Streit

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Prediction of Distant Metastasis of Renal Cell Carcinoma Based on Interpretable Machine Learning: A Multicenter Retrospective Study by Dong J, Duan M, Liu X, Li H, Zhang Y, Zhang T, Fu C, Yu J, Hu W, Peng S

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Uncovering the epigenetic regulatory clues of PRRT1 in Alzheimer’s disease: a strategy integrating multi-omics analysis with explainable machine learning by Fang Wang, Ying Liang, Qin-Wen Wang

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Full cycle rice growth monitoring with dual-pol SAR data and interpretable deep learning by Ji Ge, Hong Zhang, Lu Xu, Wenjiang Huang, Jingling Jiang, Mingyang Song, Zihuan Guo, Chao Wang

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