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Discrimination of Breast Cancer with Microcalcifications on Mammography by Deep LearningCopy number variants calling for single cell sequencing data by multi-constrained optimization.nbCNV: a multi-constrained optimization model for discovering copy number variants in single-cell sequencing dataDiagnostic assessment by dynamic contrast-enhanced and diffusion-weighted magnetic resonance in differentiation of breast lesions under different imaging protocolsOptimal combination of feature selection and classification via local hyperplane based learning strategy.Development of a ten-signature classifier using a support vector machine integrated approach to subdivide the M1 stage into M1a and M1b stages of nasopharyngeal carcinoma with synchronous metastases to better predict patients' survivalDiagnosis of breast masses from dynamic contrast-enhanced and diffusion-weighted MR: a machine learning approach.Recovering hidden diagonal structures via non-negative matrix factorization with multiple constraints.Multiparametric tissue characterization of brain neoplasms and their recurrence using pattern classification of MR images.Using nonlinear diffusion and mean shift to detect and connect cross-sections of axons in 3D optical microscopy images.A short review of variants calling for single-cell-sequencing data with applications.Repulsive force based snake model to segment and track neuronal axons in 3D microscopy image stacks.A new iterative triclass thresholding technique in image segmentation.Discrimination of malignant and benign breast masses using automatic segmentation and features extracted from dynamic contrast-enhanced and diffusion-weighted MRI.PROBABILISTIC SEGMENTATION OF BRAIN TUMORS BASED ON MULTI-MODALITY MAGNETIC RESONANCE IMAGESBreast Microcalcification Diagnosis Using Deep Convolutional Neural Network from Digital MammogramsSimultaneous Interrogation of Cancer Omics to Identify Subtypes With Significant Clinical DifferencesQuantitative analysis and prediction of regional lymph node status in rectal cancer based on computed tomography imagingPredicting underestimation of ductal carcinoma in situ: a comparison between radiomics and conventional approachesFinding Correlated Patterns via High-Order Matching for Multiple Sourced Biological DataCorrection to: Radiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroupsMolecular Decision Tree Algorithms Predict Individual Recurrence Pattern for Locally Advanced Nasopharyngeal CarcinomaIdentification of Multidimensional Regulatory Modules Through Multi-Graph Matching With Network ConstraintsRadiomics on multi-modalities MR sequences can subtype patients with non-metastatic nasopharyngeal carcinoma (NPC) into distinct survival subgroupsLow-rank analysis-synthesis dictionary learning with adaptively ordinal locality
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description
onderzoeker
@nl
researcher ORCID ID = 0000-0002-2747-7234
@en
name
Hongmin Cai
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Hongmin Cai
@en
Hongmin Cai
@es
Hongmin Cai
@nl
type
label
Hongmin Cai
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Hongmin Cai
@en
Hongmin Cai
@es
Hongmin Cai
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prefLabel
Hongmin Cai
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Hongmin Cai
@en
Hongmin Cai
@es
Hongmin Cai
@nl
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P31
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0000-0002-2747-7234