Journal articles on the topic 'Local-interpretable-model-agnostic'
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Zafar, Muhammad Rehman, and Naimul Khan. "Deterministic Local Interpretable Model-Agnostic Explanations for Stable Explainability." Machine Learning and Knowledge Extraction 3, no. 3 (June 30, 2021): 525–41. http://dx.doi.org/10.3390/make3030027.
Full textNeves, Inês, Duarte Folgado, Sara Santos, Marília Barandas, Andrea Campagner, Luca Ronzio, Federico Cabitza, and Hugo Gamboa. "Interpretable heartbeat classification using local model-agnostic explanations on ECGs." Computers in Biology and Medicine 133 (June 2021): 104393. http://dx.doi.org/10.1016/j.compbiomed.2021.104393.
Full textPalatnik de Sousa, Iam, Marley Maria Bernardes Rebuzzi Vellasco, and Eduardo Costa da Silva. "Local Interpretable Model-Agnostic Explanations for Classification of Lymph Node Metastases." Sensors 19, no. 13 (July 5, 2019): 2969. http://dx.doi.org/10.3390/s19132969.
Full textJiang, Enshuo. "UniformLIME: A Uniformly Perturbed Local Interpretable Model-Agnostic Explanations Approach for Aerodynamics." Journal of Physics: Conference Series 2171, no. 1 (January 1, 2022): 012025. http://dx.doi.org/10.1088/1742-6596/2171/1/012025.
Full textNguyen, Hai Thanh, Cham Ngoc Thi Nguyen, Thao Minh Nguyen Phan, and Tinh Cong Dao. "Pleural Effusion Diagnosis using Local Interpretable Model-agnostic Explanations and Convolutional Neural Network." IEIE Transactions on Smart Processing & Computing 10, no. 2 (April 30, 2021): 101–8. http://dx.doi.org/10.5573/ieiespc.2021.10.2.101.
Full textAdmassu, Tsehay. "Evaluation of Local Interpretable Model-Agnostic Explanation and Shapley Additive Explanation for Chronic Heart Disease Detection." Proceedings of Engineering and Technology Innovation 23 (January 1, 2023): 48–59. http://dx.doi.org/10.46604/peti.2023.10101.
Full textRajapaksha, Dilini, and Christoph Bergmeir. "LIMREF: Local Interpretable Model Agnostic Rule-Based Explanations for Forecasting, with an Application to Electricity Smart Meter Data." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 11 (June 28, 2022): 12098–107. http://dx.doi.org/10.1609/aaai.v36i11.21469.
Full textSingh, Devesh. "Interpretable Machine-Learning Approach in Estimating FDI Inflow: Visualization of ML Models with LIME and H2O." TalTech Journal of European Studies 11, no. 1 (May 1, 2021): 133–52. http://dx.doi.org/10.2478/bjes-2021-0009.
Full textGhoshRoy, Debasmita, Parvez Ahmad Alvi, and KC Santosh. "Explainable AI to Predict Male Fertility Using Extreme Gradient Boosting Algorithm with SMOTE." Electronics 12, no. 1 (December 21, 2022): 15. http://dx.doi.org/10.3390/electronics12010015.
Full textToğaçar, Mesut, Nedim Muzoğlu, Burhan Ergen, Bekir Sıddık Binboğa Yarman, and Ahmet Mesrur Halefoğlu. "Detection of COVID-19 findings by the local interpretable model-agnostic explanations method of types-based activations extracted from CNNs." Biomedical Signal Processing and Control 71 (January 2022): 103128. http://dx.doi.org/10.1016/j.bspc.2021.103128.
Full textSathyan, Anoop, Abraham Itzhak Weinberg, and Kelly Cohen. "Interpretable AI for bio-medical applications." Complex Engineering Systems 2, no. 4 (2022): 18. http://dx.doi.org/10.20517/ces.2022.41.
Full textWeitz, Katharina, Teena Hassan, Ute Schmid, and Jens-Uwe Garbas. "Deep-learned faces of pain and emotions: Elucidating the differences of facial expressions with the help of explainable AI methods." tm - Technisches Messen 86, no. 7-8 (July 26, 2019): 404–12. http://dx.doi.org/10.1515/teme-2019-0024.
Full textHsia, Chih-Hsien, Yi-Hsuan Lee, and Chin-Feng Lai. "An Explainable and Lightweight Deep Convolutional Neural Network for Quality Detection of Green Coffee Beans." Applied Sciences 12, no. 21 (October 29, 2022): 10966. http://dx.doi.org/10.3390/app122110966.
Full textMassaoudi, Mohamed, Ines Chihi, Lilia Sidhom, Mohamed Trabelsi, Shady S. Refaat, and Fakhreddine S. Oueslati. "Enhanced Random Forest Model for Robust Short-Term Photovoltaic Power Forecasting Using Weather Measurements." Energies 14, no. 13 (July 2, 2021): 3992. http://dx.doi.org/10.3390/en14133992.
Full textBaşağaoğlu, Hakan, Debaditya Chakraborty, Cesar Do Lago, Lilianna Gutierrez, Mehmet Arif Şahinli, Marcio Giacomoni, Chad Furl, Ali Mirchi, Daniel Moriasi, and Sema Sevinç Şengör. "A Review on Interpretable and Explainable Artificial Intelligence in Hydroclimatic Applications." Water 14, no. 8 (April 11, 2022): 1230. http://dx.doi.org/10.3390/w14081230.
Full textHijazi, Haytham, Manar Abu Talib, Ahmad Hasasneh, Ali Bou Nassif, Nafisa Ahmed, and Qassim Nasir. "Wearable Devices, Smartphones, and Interpretable Artificial Intelligence in Combating COVID-19." Sensors 21, no. 24 (December 17, 2021): 8424. http://dx.doi.org/10.3390/s21248424.
Full textLu, Haohui, and Shahadat Uddin. "Explainable Stacking-Based Model for Predicting Hospital Readmission for Diabetic Patients." Information 13, no. 9 (September 15, 2022): 436. http://dx.doi.org/10.3390/info13090436.
Full textEL Shawi, Radwa, and Mouaz H. Al-Mallah. "Interpretable Local Concept-based Explanation with Human Feedback to Predict All-cause Mortality." Journal of Artificial Intelligence Research 75 (November 18, 2022): 833–55. http://dx.doi.org/10.1613/jair.1.14019.
Full textConnie, Tee, Yee Fan Tan, Michael Kah Ong Goh, Hock Woon Hon, Zulaikha Kadim, and Li Pei Wong. "Explainable health prediction from facial features with transfer learning." Journal of Intelligent & Fuzzy Systems 42, no. 3 (February 2, 2022): 2491–503. http://dx.doi.org/10.3233/jifs-211737.
Full textAssegie, Tsehay Admassu, Thulasi Karpagam, Radha Mothukuri, Ravulapalli Lakshmi Tulasi, and Minychil Fentahun Engidaye. "Extraction of human understandable insight from machine learning model for diabetes prediction." Bulletin of Electrical Engineering and Informatics 11, no. 2 (April 1, 2022): 1126–33. http://dx.doi.org/10.11591/eei.v11i2.3391.
Full textUdo Sass, A., E. Esatbeyoglu, and T. Iwwerks. "Signal Pre-Selection for Monitoring and Prediction of Vehicle Powertrain Component Aging." Science & Technique 18, no. 6 (December 5, 2019): 519–24. http://dx.doi.org/10.21122/2227-1031-2019-18-6-519-524.
Full textUllah, Ihsan, Andre Rios, Vaibhav Gala, and Susan Mckeever. "Explaining Deep Learning Models for Tabular Data Using Layer-Wise Relevance Propagation." Applied Sciences 12, no. 1 (December 23, 2021): 136. http://dx.doi.org/10.3390/app12010136.
Full textKumar, Akshi, Shubham Dikshit, and Victor Hugo C. Albuquerque. "Explainable Artificial Intelligence for Sarcasm Detection in Dialogues." Wireless Communications and Mobile Computing 2021 (July 2, 2021): 1–13. http://dx.doi.org/10.1155/2021/2939334.
Full textPatel, Jinal, Charmi Amipara, Tariq Ahamed Ahanger, Komal Ladhva, Rajeev Kumar Gupta, Hashem O. Alsaab, Yusuf S. Althobaiti, and Rajnish Ratna. "A Machine Learning-Based Water Potability Prediction Model by Using Synthetic Minority Oversampling Technique and Explainable AI." Computational Intelligence and Neuroscience 2022 (September 20, 2022): 1–15. http://dx.doi.org/10.1155/2022/9283293.
Full textAlharbi, Basma, Zhenwen Liang, Jana M. Aljindan, Ammar K. Agnia, and Xiangliang Zhang. "Explainable and Interpretable Anomaly Detection Models for Production Data." SPE Journal 27, no. 01 (November 30, 2021): 349–63. http://dx.doi.org/10.2118/208586-pa.
Full textModhukur, Vijayachitra, Shakshi Sharma, Mainak Mondal, Ankita Lawarde, Keiu Kask, Rajesh Sharma, and Andres Salumets. "Machine Learning Approaches to Classify Primary and Metastatic Cancers Using Tissue of Origin-Based DNA Methylation Profiles." Cancers 13, no. 15 (July 27, 2021): 3768. http://dx.doi.org/10.3390/cancers13153768.
Full textGrzeszczyk, Tadeusz A., and Michal K. Grzeszczyk. "Justifying Short-Term Load Forecasts Obtained with the Use of Neural Models." Energies 15, no. 5 (March 2, 2022): 1852. http://dx.doi.org/10.3390/en15051852.
Full textKawakura, Shinji, Masayuki Hirafuji, Seishi Ninomiya, and Ryosuke Shibasaki. "Analyses of Diverse Agricultural Worker Data with Explainable Artificial Intelligence: XAI based on SHAP, LIME, and LightGBM." European Journal of Agriculture and Food Sciences 4, no. 6 (November 8, 2022): 11–19. http://dx.doi.org/10.24018/ejfood.2022.4.6.348.
Full textHung, Sheng-Chieh, Hui-Ching Wu, and Ming-Hseng Tseng. "Remote Sensing Scene Classification and Explanation Using RSSCNet and LIME." Applied Sciences 10, no. 18 (September 4, 2020): 6151. http://dx.doi.org/10.3390/app10186151.
Full textWang, Huan, Wei Wu, Chunxia Han, Jiaqi Zheng, Xinyu Cai, Shimin Chang, Junlong Shi, Nan Xu, and Zisheng Ai. "Prediction Model of Osteonecrosis of the Femoral Head After Femoral Neck Fracture: Machine Learning–Based Development and Validation Study." JMIR Medical Informatics 9, no. 11 (November 19, 2021): e30079. http://dx.doi.org/10.2196/30079.
Full textAkpudo, Ugochukwu Ejike, and Jang-Wook Hur. "An Explainable DL-Based Condition Monitoring Framework for Water-Emulsified Diesel CR Systems." Electronics 10, no. 20 (October 15, 2021): 2522. http://dx.doi.org/10.3390/electronics10202522.
Full textIbrahim, Muhammad Amien, Samsul Arifin, I. Gusti Agung Anom Yudistira, Rinda Nariswari, Abdul Azis Abdillah, Nerru Pranuta Murnaka, and Puguh Wahyu Prasetyo. "An Explainable AI Model for Hate Speech Detection on Indonesian Twitter." CommIT (Communication and Information Technology) Journal 16, no. 2 (June 8, 2022): 175–82. http://dx.doi.org/10.21512/commit.v16i2.8343.
Full textManikis, Georgios C., Georgios S. Ioannidis, Loizos Siakallis, Katerina Nikiforaki, Michael Iv, Diana Vozlic, Katarina Surlan-Popovic, Max Wintermark, Sotirios Bisdas, and Kostas Marias. "Multicenter DSC–MRI-Based Radiomics Predict IDH Mutation in Gliomas." Cancers 13, no. 16 (August 5, 2021): 3965. http://dx.doi.org/10.3390/cancers13163965.
Full textLee, Won-Yung, Youngseop Lee, Siwoo Lee, Young Woo Kim, and Ji-Hwan Kim. "A Machine Learning Approach for Recommending Herbal Formulae with Enhanced Interpretability and Applicability." Biomolecules 12, no. 11 (October 31, 2022): 1604. http://dx.doi.org/10.3390/biom12111604.
Full textChen, Yunsheng, Dionne M. Aleman, Thomas G. Purdie, and Chris McIntosh. "Understanding machine learning classifier decisions in automated radiotherapy quality assurance." Physics in Medicine & Biology 67, no. 2 (January 17, 2022): 025001. http://dx.doi.org/10.1088/1361-6560/ac3e0e.
Full textShamsara, Jamal. "A Random Forest Model to Predict the Activity of a Large Set of Soluble Epoxide Hydrolase Inhibitors Solely Based on a Set of Simple Fragmental Descriptors." Combinatorial Chemistry & High Throughput Screening 22, no. 8 (December 19, 2019): 555–69. http://dx.doi.org/10.2174/1386207322666191016110232.
Full textNguyen, Xuan V., Engin Dikici, Sema Candemir, Robyn L. Ball, and Luciano M. Prevedello. "Mortality Prediction Analysis among COVID-19 Inpatients Using Clinical Variables and Deep Learning Chest Radiography Imaging Features." Tomography 8, no. 4 (July 13, 2022): 1791–803. http://dx.doi.org/10.3390/tomography8040151.
Full textElliott, Shiloh N., Ashley J. B. Shields, Elizabeth M. Klaehn, and Iris Tien. "Identifying Critical Infrastructure in Imagery Data Using Explainable Convolutional Neural Networks." Remote Sensing 14, no. 21 (October 25, 2022): 5331. http://dx.doi.org/10.3390/rs14215331.
Full textYu, Chenyan, Yao Li, Minyue Yin, Jingwen Gao, Liting Xi, Jiaxi Lin, Lu Liu, et al. "Automated Machine Learning in Predicting 30-Day Mortality in Patients with Non-Cholestatic Cirrhosis." Journal of Personalized Medicine 12, no. 11 (November 19, 2022): 1930. http://dx.doi.org/10.3390/jpm12111930.
Full textAhmed, Md Sabbir, Md Tasin Tazwar, Haseen Khan, Swadhin Roy, Junaed Iqbal, Md Golam Rabiul Alam, Md Rafiul Hassan, and Mohammad Mehedi Hassan. "Yield Response of Different Rice Ecotypes to Meteorological, Agro-Chemical, and Soil Physiographic Factors for Interpretable Precision Agriculture Using Extreme Gradient Boosting and Support Vector Regression." Complexity 2022 (September 19, 2022): 1–20. http://dx.doi.org/10.1155/2022/5305353.
Full textDindorf, Carlo, Wolfgang Teufl, Bertram Taetz, Gabriele Bleser, and Michael Fröhlich. "Interpretability of Input Representations for Gait Classification in Patients after Total Hip Arthroplasty." Sensors 20, no. 16 (August 6, 2020): 4385. http://dx.doi.org/10.3390/s20164385.
Full textPetrescu, Livia, Cătălin Petrescu, Ana Oprea, Oana Mitruț, Gabriela Moise, Alin Moldoveanu, and Florica Moldoveanu. "Machine Learning Methods for Fear Classification Based on Physiological Features." Sensors 21, no. 13 (July 1, 2021): 4519. http://dx.doi.org/10.3390/s21134519.
Full textKitamura, Shinji, Kensaku Takahashi, Yizhen Sang, Kazuhiko Fukushima, Kenji Tsuji, and Jun Wada. "Deep Learning Could Diagnose Diabetic Nephropathy with Renal Pathological Immunofluorescent Images." Diagnostics 10, no. 7 (July 9, 2020): 466. http://dx.doi.org/10.3390/diagnostics10070466.
Full textSteed, Ryan, and Aylin Caliskan. "A set of distinct facial traits learned by machines is not predictive of appearance bias in the wild." AI and Ethics 1, no. 3 (January 12, 2021): 249–60. http://dx.doi.org/10.1007/s43681-020-00035-y.
Full textMehta, Harshkumar, and Kalpdrum Passi. "Social Media Hate Speech Detection Using Explainable Artificial Intelligence (XAI)." Algorithms 15, no. 8 (August 17, 2022): 291. http://dx.doi.org/10.3390/a15080291.
Full textKnapič, Samanta, Avleen Malhi, Rohit Saluja, and Kary Främling. "Explainable Artificial Intelligence for Human Decision Support System in the Medical Domain." Machine Learning and Knowledge Extraction 3, no. 3 (September 19, 2021): 740–70. http://dx.doi.org/10.3390/make3030037.
Full textDeng, Shangkun, Yingke Zhu, Xiaoru Huang, Shuangyang Duan, and Zhe Fu. "High-Frequency Direction Forecasting of the Futures Market Using a Machine-Learning-Based Method." Future Internet 14, no. 6 (June 9, 2022): 180. http://dx.doi.org/10.3390/fi14060180.
Full textKikutsuji, Takuma, Yusuke Mori, Kei-ichi Okazaki, Toshifumi Mori, Kang Kim, and Nobuyuki Matubayasi. "Explaining reaction coordinates of alanine dipeptide isomerization obtained from deep neural networks using Explainable Artificial Intelligence (XAI)." Journal of Chemical Physics 156, no. 15 (April 21, 2022): 154108. http://dx.doi.org/10.1063/5.0087310.
Full textDindorf, Carlo, Jürgen Konradi, Claudia Wolf, Bertram Taetz, Gabriele Bleser, Janine Huthwelker, Friederike Werthmann, et al. "Classification and Automated Interpretation of Spinal Posture Data Using a Pathology-Independent Classifier and Explainable Artificial Intelligence (XAI)." Sensors 21, no. 18 (September 21, 2021): 6323. http://dx.doi.org/10.3390/s21186323.
Full textZhu, Mingzhe, Bo Zang, Linlin Ding, Tao Lei, Zhenpeng Feng, and Jingyuan Fan. "LIME-Based Data Selection Method for SAR Images Generation Using GAN." Remote Sensing 14, no. 1 (January 3, 2022): 204. http://dx.doi.org/10.3390/rs14010204.
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