Research graph
References from An integrated AI pipeline for automated cytogenetic analysis of bone marrow karyograms in hematological malignancies: A Pix2Pix enhancement and deep learning detection approach. Local targets link to admitted publications; unresolved targets remain external evidence.
Integration of artificial intelligence in cytogenetic workflows: challenges and opportunities
2023 · External reference
The perception-distortion tradeoff
2018 · External reference
ChromoEnhancer: an artificial intelligence-based tool to enhance neoplastic karyograms as an aid for effective analysis
10.3390/cells11142244 · 2022 · External reference
Unresolved reference
2023 · External reference
Chromosomal abnormalities of mesenchymal stromal cells in hematological malignancies
2025 · External reference
Diagnosis and management of AML in adults: 2022 recommendations from an international expert panel on behalf of the ELN
10.1182/blood.2022016867 · 2022 · External reference
Five-year follow-up of patients receiving imatinib for chronic myeloid leukemia
10.1056/nejmoa062867 · 2006 · External reference
Automated deep aberration detection from chromosome karyotype images
2023 · External reference
Artificial intelligence-assisted diagnostic cytology and genomic testing for hematologic disorders
10.3390/cells12131755 · 2023 · External reference
Revised international prognostic scoring system for myelodysplastic syndromes
10.1182/blood-2012-03-420489 · 2012 · External reference
Deep residual learning for image recognition
2016 · External reference
Interactive machine learning for health informatics: when do we need the human-in-the-loop?
10.1007/s40708-016-0042-6 · 2016 · External reference
Image-to-image translation with conditional adversarial networks
2017 · External reference
Chromosome segmentation in metaphase images using deep learning
2018 · External reference
Automatic karyotype analysis using deep convolutional neural networks
2019 · External reference
Automated analysis of metaphase chromosome images using convolutional neural networks
2019 · External reference
Key challenges for delivering clinical impact with artificial intelligence
10.1186/s12916-019-1426-2 · 2019 · External reference
High-performance medicine: the convergence of human and artificial intelligence
10.1038/s41591-018-0300-7 · 2019 · External reference
Making a completely blind image quality analyzer
10.1109/lsp.2012.2227726 · 2013 · External reference
Deep MR to CT synthesis using unpaired data
2017 · External reference
Human-in-the-loop machine learning: a state of the art
10.1007/s10462-022-10246-w · 2023 · External reference
Complacency and bias in human use of automation: an attentional integration
10.1177/0018720810376055 · 2010 · External reference
Validating whole slide imaging for diagnostic purposes in pathology
10.5858/arpa.2013-0093-cp · 2013 · External reference
Clinical validation of AI systems for chromosomal abnormality detection in hematologic malignancies
2024 · External reference
U-Net: convolutional networks for biomedical image segmentation
2015 · External reference
YOLOv3: an incremental improvement
2018 · External reference
Squeeze-and-excitation networks
2018 · External reference
Unresolved reference
2020 · External reference
Blind image quality evaluation using perception-based features
2015 · External reference
Image quality assessment: from error visibility to structural similarity
10.1109/tip.2003.819861 · 2004 · External reference
