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Computational Mathematics Modeling in Cancer Analysis : First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings / / edited by Wenjian Qin, Nazar Zaki, Fa Zhang, Jia Wu, Fan Yang
Computational Mathematics Modeling in Cancer Analysis : First International Workshop, CMMCA 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Proceedings / / edited by Wenjian Qin, Nazar Zaki, Fa Zhang, Jia Wu, Fan Yang
Edizione [1st ed. 2022.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022
Descrizione fisica 1 online resource (171 pages)
Disciplina 636.80896994
616.99400113
Collana Lecture Notes in Computer Science
Soggetto topico Image processing - Digital techniques
Computer vision
Computer engineering
Computer networks
Machine learning
Computers
Computer Imaging, Vision, Pattern Recognition and Graphics
Computer Engineering and Networks
Machine Learning
Computing Milieux
ISBN 3-031-17266-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Cellular Architecture on Whole Slide Images Allows the Prediction of Survival in Lung Adenocarcinoma -- Is More Always Better? Effects of Patch Sampling in Distinguishing Chronic Lymphocytic Leukemia from Transformation to Diffuse Large B-cell Lymphoma -- Repeatability of Radiomic Features against Simulated Scanning Position Stochasticity across Imaging Modalities and Cancer Subtypes: A Retrospective Multi-Institutional Study on Head-and-Neck Cases -- MLCN: Metric Learning Constrained Network for Whole Slide Image Classification with Bilinear Gated Attention Mechanism -- NucDETR: End-to-End Transformer for Nucleus Detection in Histopathology Images -- Self-supervised learning based on a pre-trained method for the subtype classification of spinal tumors -- CanDLE: Illuminating Biases in Transcriptomic Pan-Cancer Diagnosis -- Cross-Stream Interactions: Segmentation of Lung Adenocarcinoma Growth Patterns -- Modality-collaborative AI model Ensemble for Lung Cancer Early Diagnosis -- Clustering-based Multi-instance Learning Network for Whole Slide Image Classification -- Multi-task Learning-driven Volume and Slice Level Contrastive Learning for 3D Medical Image Classification -- Light Annotation Fine Segmentation: Histology Image Segmentation based on VGG Fusion with Global Normalisation CAM -- Tubular Structure-Aware Convolutional Neural Networks for Organ at Risks Segmentation in Cervical Cancer Radiotherapy -- Automatic Computer-aided Histopathologic Segmentation for Nasopharyngeal Carcinoma using Transformer Framework -- Accurate Breast Tumor Identification UsingComputational Ultrasound Image Features.
Record Nr. UNINA-9910595023903321
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2022
Materiale a stampa
Lo trovi qui: Univ. Federico II
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Mathematical models of cancer and different therapies : unified framework / / Regina Padmanabhan, Nader Meskin, Ala-Eddin Al Moustafa
Mathematical models of cancer and different therapies : unified framework / / Regina Padmanabhan, Nader Meskin, Ala-Eddin Al Moustafa
Autore Padmanabhan Regina
Edizione [1st ed. 2021.]
Pubbl/distr/stampa Gateway East, Singapore : , : Springer, , [2021]
Descrizione fisica 1 online resource (XVI, 256 p. 35 illus., 29 illus. in color.)
Disciplina 616.99400113
Collana Series in BioEngineering
Soggetto topico Cancer - Mathematical models
ISBN 981-15-8640-3
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Background -- Time series data to mathematical model -- Chemotherapy models -- Immunotherapy models -- Anti-angiogenic therapy models -- Radiotherapy Models -- Hormone therapy models -- Miscellaneous therapy models -- Combination therapy models -- Control stratergies used for cancer therapy -- Conclusions.
Record Nr. UNINA-9910483024703321
Padmanabhan Regina  
Gateway East, Singapore : , : Springer, , [2021]
Materiale a stampa
Lo trovi qui: Univ. Federico II
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