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References from Demystifying the black box: A survey on explainable artificial intelligence (XAI) in bioinformatics. Local targets link to admitted publications; unresolved targets remain external evidence.
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10.1038/s41467-023-41146-4 · 2023 · External reference
Explainable deep learning methods in medical image classification: a survey
2023 · External reference
Interpretable machine learning methods for predictions in systems biology from omics data
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Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models
10.1038/s41551-023-01034-0 · 2023 · External reference
A multidisciplinary survey and framework for design and evaluation of explainable AI systems
2021 · External reference
PMFN-SSL: Self-supervised learning-based progressive multimodal fusion network for cancer diagnosis and prognosis
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Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
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RNA-seq data science: from raw data to effective interpretation
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A survey of best practices for RNA-seq data analysis
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10.1016/j.csbj.2022.10.030 · Admitted local publication
Explainable artificial intelligence for omics data: a systematic mapping study
10.1093/bib/bbad453 · 2024 · External reference
Interpretation of deep learning in genomics and epigenomics
10.1093/bib/bbaa177 · 2021 · External reference
Multiomics and eXplainable artificial intelligence for decision support in insulin resistance early diagnosis: a pediatric population-based longitudinal study
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10.1016/j.csbj.2021.06.030 · Admitted local publication
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10.1093/bib/bbad056 · 2023 · External reference
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Explainable artificial intelligence model for identifying COVID-19 gene biomarkers
10.1016/j.compbiomed.2023.106619 · 2023 · External reference
Investigation of potential biomarkers in prediction of acute myocardial infarction via explainable artificial intelligence
10.5455/medscience.2023.03.035 · 2023 · External reference
Bladder cancer gene expression prediction with explainable algorithms
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A performance evaluation of drug response prediction models for individual drugs
10.1038/s41598-023-39179-2 · 2023 · External reference
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Explainable artificial intelligence to predict and identify prostate cancer tissue by gene expression
10.1016/j.cmpb.2023.107719 · 2023 · External reference
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10.1109/bibm58861.2023.10385498
10.1109/bibm58861.2023.10385498 · External reference
Survival prediction via hierarchical multimodal co-attention transformer: a computational histology-radiology solution
2023 · External reference
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10.1109/access.2019.2907040
10.1109/access.2019.2907040 · External reference
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Convolutional neural networks for the evaluation of cancer in barrett's esophagus: explainable AI to lighten up the black-box
10.1016/j.compbiomed.2021.104578 · 2021 · External reference
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10.1016/j.patcog.2018.08.012 · 2019 · External reference
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Non-small cell lung cancer diagnosis aid with histopathological images using explainable deep learning techniques
10.1016/j.cmpb.2022.107108 · 2022 · External reference
10.1109/icnsc55942.2022.10004157
10.1109/icnsc55942.2022.10004157 · External reference
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10.3390/a14100278 · 2021 · External reference
10.1109/cvprw.2017.114
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10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00068 · External reference
Attention guided grad-CAM: an improved explainable artificial intelligence model for infrared breast cancer detection
2023 · External reference
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10.1007/978-3-031-16443-9_67 · External reference
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10.1016/j.media.2023.102809
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Multi-orientation local texture features for guided attention-based fusion in lung nodule classification
10.1109/access.2023.3243104 · 2023 · External reference
Improving explainability results of convolutional neural networks in microscopy images
2023 · External reference
A transfer learning and explainable solution to detect mpox from smartphones images
10.1016/j.pmcj.2023.101874 · 2024 · External reference
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10.1109/cvpr.2018.00474
10.1109/cvpr.2018.00474 · External reference
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DeepOCT: an explainable deep learning architecture to analyze macular edema on OCT images
2022 · External reference
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Omics data preprocessing for machine learning: a case study in childhood obesity
10.3390/genes14020248 · 2023 · External reference
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10.1038/s42256-019-0048-x
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Dermatologist-like explainable AI enhances trust and confidence in diagnosing melanoma
10.1038/s41467-023-43095-4 · 2024 · External reference
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Never tell me the odds: Investigating pro-hoc explanations in medical decision making
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On generating trustworthy counterfactual explanations
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Decoding the black box: Explainable AI (XAI) for cancer diagnosis, prognosis, and treatment planning-A state-of-the art systematic review
2024 · External reference
XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data
10.1093/bib/bbab315 · 2021 · External reference
10.1016/j.csbj.2021.01.010 · Admitted local publication
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Explainable artificial intelligence for breast cancer: a visual case-based reasoning approach
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Auditing the inference processes of medical-image classifiers by leveraging generative AI and the expertise of physicians
2023 · External reference
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eXplainable Artificial Intelligence (XAI) for the identification of biologically relevant gene expression patterns in longitudinal human studies, insights from obesity research
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Computational modeling for deciphering tissue microenvironment heterogeneity from spatially resolved transcriptomics
2024 · External reference
