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

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Towards Explainable Anomaly Detection in Safety-critical Systems: Employing FRAM and SpecTRM in International Space Station Telemetry by Shota Iino, Hideki Nomoto, Takashi Fukui, Sayaka Ishizawa, Yohei Yagisawa, Takayuki Hirose, Yasutaka Michiura

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A Comprehensive Guide to Interpretable AI-Powered Discoveries in Astronomy by Maggie Lieu

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Interpretable Machine Learning for the German residential rental market – shedding light into model mechanics by Severin Bachmann

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Interpretable Machine Learning Analysis of Design Factors in Hydrogel Supercapacitors by Liying Xu, Siqi Liu, Dandan Hu, Junhao Liu, Yuze Zhang, Ziqiang Li, Zichuan Su, Daxin Liang

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Network-based predictive models for artificial intelligence: an interpretable application of machine learning techniques in the assessment of depression in stroke patients by Wenwei Zuo, Xuelian Yang

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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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Exploring Mechanisms and Biomarkers of Breast Cancer Invasion and Migration: An Explainable Gene–Pathway–Compounds Neural Network by Xia Qian, Dandan Sun, Yichen Ma, Ling Qiu, Jie Wu

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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 Using Temporal Transformers for Battery Degradation Prediction by James Sadler, Rizwaan Mohammed, Kotub Uddin

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Explainable artificial intelligence for energy efficiency in experimental refrigeration Systems: Advanced cutting-edge sunflower optimization by Mehmet Das, Oguzhan Pektezel, Cebrail Barut, Gungor Yildirim, Bilal Alatas

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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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Investigating pedestal dependencies at JET using an interpretable neural network architecture by A. Gillgren, A. Ludvig-Osipov, D. Yadykin, P. Strand, JET contributors

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ASSOCIATION RULES IN RANDOM FOREST FOR THE MOST INTERPRETABLE MODEL by Hafizah Ilma, Khairil Anwar Notodiputro, Bagus Sartono

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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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Using interpretable survival analysis to assess hospital length of stay by Yan Li, Trevor Hall, Fahad Razak, Amol Verma, Mark Chignell, Lu Wang

Subjects: “…Interpretable machine learning…”
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Interpretable XGBoost model identifies idiopathic central precocious puberty in girls using four clinical and imaging features by Lu Tian, Yan Zeng, Helin Zheng, Jinhua Cai

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Fully Interpretable and Adjustable Model for Depression Diagnosis: A Qualitative Approach by Kuo Deng, Xiaomeng Ye, Kun Wang, Angelina Pennino, Abigail Jarvis, Yola Hall

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Modeling microbiome-trait associations with taxonomy-adaptive neural networks by Yifan Jiang, Matthew Aton, Qiyun Zhu, Yang Young Lu

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Interpretable model based on MRI radiomics to predict the expression of Ki-67 in breast cancer by Li Zhang, Qinglin Du, Mengyi Shen, Xin He, Dingyi Zhang, Xiaohua Huang

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