Local interpretable model-agnostic explanations for classification of lymph node metastases

Cited by (155)

Items 101–155 of 155

1. Bridging Explainable Machine Vision in CAD Systems for Lung Cancer Detection
   Nusaiba Alwarasneh, Yuen Shan Serene Chow, Sarah Teh Mei Yan, Chern Hong Lim · 2020 · Lecture notes in computer science
2. Using Explainable Artificial Intelligence to Increase Trust in Computer Vision.
   Christian Meske, Enrico Bunde · 2020 · arXiv (Cornell University)
3. Artificial intelligence enabled tumor diagnosis and treatment: Status, breakthroughs and challenges
   Yani Hu, Shuai Liang, Xu Zhou, Zhipeng Zeng, Junli Ding, Dong Hua · 2025 · Critical Reviews in Oncology/Hematology
4. Explainable Artificial Intelligence Method (ParaNet+) Localises Abnormal Parathyroid Glands in Scintigraphic Scans of Patients with Primary Hyperparathyroidism
   Dimitris J. Apostolopoulos, Ioannis D. Apostolopoulos, Nikolaos D. Papathanasiou, Trifon Spyridonidis, George Panayiotakis · 2023 · Algorithms
5. Fovea and diabetic retinopathy: Understanding the relationship using a deep interpretable classifier
   Latifah Listyalina, Evrita Lusiana Utari, Desty Ervira Puspaningtyas, Dhimas Arief Dharmawan · 2022 · Computer Methods and Programs in Biomedicine Update
6. Olive Oil Fly Population Pest Forecasting Using Explainable Deep Learning
   Andrés Manuel Chacón-Maldonado, A. R. Troncoso-García, Francisco Martinez Alvarez, Gualberto Asencio Cortés, Alicia Troncoso · 2023 · Lecture notes in networks and systems
7. Method of Improving the Management of Cancer Risk Groups by Coupling a Features-Attention Mechanism to a Deep Neural Network
   Darian M. Onchiş, Flavia Costi, Codruta Istin, Ciprian Cosmin Secasan, Gabriel Veniamin Cozma · 2024 · Applied Sciences
8. Unveiling the Depths of Explainable AI
   Wasim Khan, Mohammad Ishrat · 2024 · Advances in systems analysis, software engineering, and high performance computing book series
9. Integration of digital twin and machine learning technologies in renewable energy–hydrogen systems for next-generation sustainable energy
   Ibrahim Balarabe Mansir, Talal F. Qahtan · 2026 · Energy Sustainable Development/Energy for sustainable development
10. Enhancing explainability in medical image classification and analyzing osteonecrosis X-ray images using shadow learner system
    Yaoyang Wu, Simon James Fong, Liansheng Liu · 2024 · Applied Intelligence
11. MRI-Based Machine Learning and Radiomics Methods for Assessing Spinal Cord Function in Patients with Mild Cervical Spondylotic Myelopathy
    Wang He, Kai Wang, Yutian Wang, Zhenlei Liu, Lei Zhang, Shanhang Jia, Kun He, Xiangyu Zhang, Hao Wu · 2025 · Bioengineering
12. COVID-19 Interpretable Diagnosis Algorithm Based on a Small Number of Chest X-Ray Samples
    Ran Bu, Wei Xiang, Shitong Cao · 2021 · Journal of Shanghai Jiaotong University (Science)
13. SeCAM: Tightly Accelerate the Image Explanation via Region-Based Segmentation
    Phong X. NGUYEN, Hung Cao, Khang V. T. NGUYEN, Hung Viet Nguyen, Takehisa Yairi · 2022 · IEICE Transactions on Information and Systems
14. Multi-Feature Fusion in Graph Convolutional Networks for Data Network Propagation Path Tracing
    Dongsheng Jing, Yu Yang, Zhimin Gu, Renjun Feng, Yan Li, Haitao Jiang · 2024 · Electronics
15. Approximate Explanations for Classification of Histopathology Patches
    Iam Palatnik de Sousa, Marley M. B. R. Vellasco, Eduardo Costa da Silva · 2020 · Communications in computer and information science
16. A method for explaining individual predictions in neural networks
    Sejong Oh · 2025 · PeerJ Computer Science
17. Beyond Feature Selection: Interpretable Machine Learning for Mechanistic Insights in Metabolomics
    Haotian Bai, Yufei Ren, Jihan Wang, Yangyang Wang, Ying Yang · 2026 · Biology
18. Eichner classification based on panoramic X-ray images using deep learning: A pilot study
    Yuta Otsuka, Hiroko P. Indo, Yusuke Kawashima, Tatsuro Tanaka, Hiroshi Kono, Masafumi Kikuchi · 2024 · Bio-Medical Materials and Engineering
19. Explainable AI in Healthcare: Methods, Concepts, and Challenges
    Soram Patel, Heeya Amin · 2024 · Lecture notes in electrical engineering
20. The Importance of Interpretability in AI Systems and Its Implications for Deep Learning
    Muhammad Adnan · 2024 · Advances in computational intelligence and robotics book series
21. On Deep Research Problems in Deep Learning
    Anwaar Ulhaq · 2021
22. Secure Digital Health Data Transmission in Healthcare Industry 4.0—An Overview
    Dhivya Ravichandran, W. Sylvia Lilly Jebarani, A R Gopinath, Chanthini Baskar, Rengarajan Amirtharajan · 2025
23. AI-driven prognostics in pediatric bone marrow transplantation: a CAD approach with Bayesian and PSO optimization
    Mahmoud Badawy, Yousry AbdulAzeem, Hanaa Y. ZainEldin, Hossam Magdy Balaha, Amna Bamaqa, Rasha F. El-Agamy, Hanaa A. Sayed, Mostafa A. Elhosseini · 2025 · BMC Medical Informatics and Decision Making
24. A robust and interpretable framework for sports activity recognition based on wearable sensor signals and image representations
    Jian Li, Yi-Bo Fan, Jun-Hui Gong, Junyi Chen, Ruo-Yu Chen, Wenyan Zhang, Yu-Liang Zhao · 2026 · Engineering applications of artificial intelligence
25. An AI based framework using Aquila-optimized capsule network for radar object detection
    Aymin Javed, Nadeem Javaid, Yousra Asim, Zeeshan Ali, Badr Alsamani, Abdul Khader Jilani Saudagar · 2026 · Complex & Intelligent Systems
26. Building a reliable coagulant dosage prediction framework for water purification processes using CatBoost and explainable AI (XAI)
    Khaled Merabet, Il-Moon Chung, Amel Fouchal, Francesco Granata, Özgür Kişi, Sungwon Kim, Salim Heddam, Mohammad Zounemat‐Kermani · 2026 · Engineering Applications of Computational Fluid Mechanics
27. Explainability-Enhanced Neural Network for Thoracic Diagnosis Improvement
    Flavia Costi, Darian M. Onchiş, Codruta Istin, Gabriel Veniamin Cozma · 2023 · Lecture notes in computer science
28. Improved DeTraC Binary Coyote Net‐Based Multiple Instance Learning for Predicting Lymph Node Metastasis of Breast Cancer From Whole‐Slide Pathological Images
    M. Ramkumar, R. Sarath Kumar, R. Padmapriya, S. Balu Mahandiran · 2024 · International Journal of Medical Robotics and Computer Assisted Surgery
29. INTELIGÊNCIA ARTIFICIAL EXPLICÁVEL PARA CLASSIFICADORES DE IMAGENS MÉDICAS
    Iam Palatnik de Sousa · 2021
30. Explainable-AI to Discover Associated Genes for Classifying Hepato-cellular Carcinoma from High-dimensional Data
    Easin Hasan, Fahad B. Mostafa, Md Shafaeat Hossain, Jonathon Loftin · 2022 · medRxiv
31. Classificações Explicáveis para Imagens de Células Infectadas por Malária
    Iam Palatnik de Sousa, Marley M. B. R. Vellasco, Eduardo Silva · 2020
32. Edge Computing Based Miniature Maps Using Embedded Webserver For Prediction of Malignancy
    Anil Johny, K. N. Madhusoodanan, Sanju Cyriac · 2022 · International Conference on Devices, Circuits and Systems (ICDCS)
33. A Dataset Generation Framework for Evaluating Megapixel Image Classifiers and Their Explanations
    Gautam Machiraju, Sylvia K. Plevritis, Parag Mallick · 2022 · Lecture notes in computer science
34. Integrative approach for classifying male tumors based on DNA methylation 450K data
    Jiming Wu, Wang‐Ren Qiu, Zi Liu, Zhaochun Xu, Shouhua Zhang · 2023 · Mathematical Biosciences & Engineering
35. Global Shapley Explanations and LIME on HLA-B27 Positivity in Ankylosing Spondylitis Patients
    Nurmuhammet Taş, Buminhan Şeferoğlu, Muhammet Emin Naldan, Hülya Naldan, Kevser Kübra Kırboğa, Mesut Işık · 2023 · Research Square
36. Study on risk factors of diabetic peripheral neuropathy and development of a prediction model based on machine learning
    Qiyuan Cui, Wang Li, Xiaoyan Wang, Yun Zheng, Jiaxi Lin, Lu Liu, Jinzhou Zhu, Mingqing He · 2023 · Research Square
37. Beyond Accuracy: Building Trustworthy Extreme Events Predictions Through Explainable Machine Learning
    Mulomba Mukendi Christian, Asser Kasai Itakala, Pierrot Muteba Tibasima · 2024 · European Journal of Theoretical and Applied Sciences
38. Drawing Attributions From Evolved Counterfactuals
    Ján Jakubík, Halina Kwaśnicka · 2024 · Genetic and Evolutionary Computation Conference Companion (GECCO Companion)
39. User Experience and Trust Improvement Evaluation on Healthcare oriented Explainable Artificial Intelligence Interventions: Systematic Review (Preprint)
    Samantha Cramer, Elina Gastreich de Llanes, Jonas Bäcker, Robin Manz, Philip Meyer, Dominik Müller, Ludwig Christian Hinske, Johannes Raffler, Iñaki Soto‐Rey · 2025
40. Predicting the Recovery of Psychophysiological State after Chronic Stress: A Neural Network Model
    Vitaliy Tsymbalyuk, Stepan N. Vadzyuk, P.S. Tabas, O.M. Ratynska, V. V. SAS, M.O. Sopiga · 2025 · Fìzìologìčnij žurnal
41. Advances in Cyclone Intensity Classification: A Comparative Analysis
    M S Manju, Rajesh Kumar Pateriya, Rajeev Kumar Gupta · 2025 · International Conference on Signal Processing, Computing and Control (ISPCC)
42. Smart Digital Twin System for optimized Elderly Type 2 Diabetes through Personalized Management using Adaptive Predictive Control
    Kavitha Kavitha, Abdul Kadher K. Mohaideen, Manivannan, Sravanthi K, S.Vinayagan, Elango B · 2025
43. Introduction to artificial intelligence in chemical engineering
    Bilal Fareed, Tazien Rashid, Farooq Sher, Naadhira Seedat, Miguel Angel Pans Castillo, Anka Trajkovska Petkoska, Edisa Papraćanin, Mika E. T. Sillanpää · 2025 · Elsevier eBooks
44. Shedding Light Inside the Black Box: Techniques for Explainable Artificial Intelligence in Healthcare
    Loris Belcastro, Riccardo Cantini, Fabrizio Marozzo, Domenico Talia, Paolo Trunfio A · 2025 · Springer eBooks
45. Capsule-ConvKAN: A Hybrid Neural Approach for Medical Image Classification
    Laura Pituková, Peter Sinčák, László Kovács, P. Wang · 2025 · Conference proceedings/Conference proceedings - IEEE International Conference on Systems, Man, and Cybernetics
46. Explainability Methods for AI-Assisted Diagnosis of Lymph Node Metastases in Digital Pathology: A Quantitative Comparative Study
    Eduardo Costa da Silva · 2026 · Diagnostics
47. Explainable AI and Transparency in Clinical Decision Support
    Deepak Gupta, Nasiba Jumaniyazova, Afakova Mamura, Jobir Akhmedov, Gulshoda Masharipova, Dilorom Masharipova, Shakhrijakhon Aminqulov · 2026 · Advances in computational intelligence and robotics book series
48. Explainable metaheuristic-optimized XGBoost models for chlorophyll-a concentration prediction: A comparative study based on SHAP and LIME interpretability
    Khaled Merabet, Sungwon Kim, Özgür Kişi, Francesco Granata, Salim Heddam, Mohammad Zounemat‐Kermani · 2026 · Journal of environmental chemical engineering
49. Enhancing cybersecurity with Explainable Artificial Intelligence: technical framework and applications in training labs
    Ahmad Almufarreh, Ashfaq Ahmad, Muhammad Arshad, Choo Wou Onn, Yegon Michael Kiplangat · 2026 · Frontiers in Computer Science
50. Machine learning approaches to predict maternal anemia and Identifying associated factors among pregnant women in Sub-Saharan Africa
    Eliyas Addisu Taye, Gabrela Yimer Hailie, Abel Temeche Kassaw · 2026 · Journal of Public Health Research
51. Single-cell and spatial transcriptomics characterisation of RSPO2+ nucleus pulposus cells reveals a WNT/FN1–CD44 degenerative axis and therapeutic targets in IVDD
    Qiuwei Li, Guoyan Liang, Kaida Bo, Liang Kang, Peilin Jin, Chenhao Zhao, Renjie Zhang, Fengjuan Lyu, Cailiang Shen · 2026 · Journal of Orthopaedic Translation
52. Explainable Early Alzheimer's Disease Detection Using a Hybrid Capsule and Vision Transformer-Based Framework with LIME
    SARAVANAN S, Baghavathi Priya S · 2026 · Research Square
53. An update of artificial intelligence in pathology: Current applications, challenges, and future directions
    Jenson A. Tham, Fuda Xie, Bonan Chen, Peiyao Yu, Jialin Wu, Tiejun Feng, Gary M.K. Tse, Ka Fai To, Wei Kang · 2026 · Intelligent Systems with Applications
54. Development of an Interpretable Triage Tool for Colorectal Polyp Risk Stratification Within a Population-Based Screening Program: Machine Learning Approach
    Zhenmiao Ye, Jiajin Li, Yimin Xie, Qian Li, Yilun Huang, Guohua Zhang, Xue Yang · 2026 · JMIR Medical Informatics
55. SHAP and LIME-based interpretation of metaheuristic-optimized least square support vector machine in high-performance concrete chloride penetration assessment
    Jitendra Khatti, Aleksandra Bogdanović, Asmaa A. Mashaly · 2026 · International Journal of Material Forming