Pallavi Tiwari (120 results)

Paperback. Condition: Brand New. 1st edition. 272 pages. 9.00x6.00x0.62 inches. In Stock.

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Paperback. Condition: new. Paperback. This volume constitutes the refereed proceedings of the First International Workshop on Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, AIPAD 2024 and the First International Workshop on Personalized Incremental Learning in Medicine, PILM 2024, held in conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024.The 8 full papers included in these proceedings were carefully reviewed and selected from 9 submissions. They were organized in topical sections as follows: artificial intelligence in pancreatic disease detection and diagnosis; and personalized incremental learning in medicine. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Paperback. Condition: Brand New. 116 pages. 6.14x0.25x9.21 inches. In Stock.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This volume constitutes the refereed proceedings of the First International Workshop on Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, AIPAD 2024 and the First International Workshop on Personalized Incremental Learning in Medicine, PILM 2024, held in conjunction with MICCAI 2024, in Marrakesh, Morocco, in October 2024.The 8 full papers included in these proceedings were carefully reviewed and selected from 9 submissions.They were organized in topical sections as follows:artificial intelligence in pancreatic disease detection and diagnosis; andpersonalized incremental learning in medicine.…

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Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The 19-volume set LNCS 16878 - 16896 constitutes the refereed proceedings of the 29th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2026, which took place in Strasbourg, France, during September 27 - October 1, 2026.The 1167 full papers included in the proceedings was carefully reviewed and selected from a total of 4601 submissions. The papers were organized in topical parts as follows:Part I, LNCS Volume 16878: Adapting Foundation Models for Medical Imaging: Large Vision and Language Models (I)Part II, LNCS Volume 16879: Adapting Foundation Models for Medical Imaging: Large Vision and Language Models (II)Part III, LNCS Volume 16880: Efficient Learning Strategies in Medical ImagingPart IV, LNCS Volume 16881: Domain Adaptation and Generalization in Medical ImagingPart V, LNCS Volume 16882: Trustworthy, Explainable, and Responsible Medical AIPart VI, LNCS Volume 16883: Medical Image Segmentation (I)Part VII, LNCS Volume 16884: Medical Image Segmentation (II)Part VIII, LNCS Volume 16885: Computer-Aided Diagnosis (I)Part IX, LNCS Volume 16886: Computer-Aided Diagnosis (II)Part X, LNCS Volume 16887: Longitudinal Modeling, Staging, and PrognosisPart XI, LNCS Volume 16888: Image Reconstruction and Image EnhancementPart XII, LNCS Volume 16889: Medical Image Registration; Shape AnalysisPart XIII, LNCS Volume 16890: Medical Image Synthesis and Super-resolutionPart XIV, LNCS Volume 16891: Computational Pathology; Microscopic ImagingPart XV, LNCS Volume 16892: Surgical Data Science and Scene UnderstandingPart XVI, LNCS Volume 16893: Image-Guided Surgery and InterventionPart XVII, LNCS Volume 16894: Neuroimaging and Brain-Computer InterfacesPart XVIII, LNCS Volume 16895: Benchmarking Datasets and Methods; Clinical ApplicationsPart XIX, LNCS Volume 16896: Emerging Techniques and Applications. …

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - The 19-volume set LNCS 16878 - 16896 constitutes the refereed proceedings of the 29th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2026, which took place in Strasbourg, France, during September 27 - October 1, 2026.The 1167 full papers included in the proceedings was carefully reviewed and selected from a total of 4601 submissions. The papers were organized in topical parts as follows:Part I, LNCS Volume 16878: Adapting Foundation Models for Medical Imaging: Large Vision and Language Models (I)Part II, LNCS Volume 16879: Adapting Foundation Models for Medical Imaging: Large Vision and Language Models (II)Part III, LNCS Volume 16880: Efficient Learning Strategies in Medical ImagingPart IV, LNCS Volume 16881: Domain Adaptation and Generalization in Medical ImagingPart V, LNCS Volume 16882: Trustworthy, Explainable, and Responsible Medical AIPart VI, LNCS Volume 16883: Medical Image Segmentation (I)Part VII, LNCS Volume 16884: Medical Image Segmentation (II)Part VIII, LNCS Volume 16885: Computer-Aided Diagnosis (I)Part IX, LNCS Volume 16886: Computer-Aided Diagnosis (II)Part X, LNCS Volume 16887: Longitudinal Modeling, Staging, and PrognosisPart XI, LNCS Volume 16888: Image Reconstruction and Image EnhancementPart XII, LNCS Volume 16889: Medical Image Registration; Shape AnalysisPart XIII, LNCS Volume 16890: Medical Image Synthesis and Super-resolutionPart XIV, LNCS Volume 16891: Computational Pathology; Microscopic ImagingPart XV, LNCS Volume 16892: Surgical Data Science and Scene UnderstandingPart XVI, LNCS Volume 16893: Image-Guided Surgery and InterventionPart XVII, LNCS Volume 16894: Neuroimaging and Brain-Computer InterfacesPart XVIII, LNCS Volume 16895: Benchmarking Datasets and Methods; Clinical ApplicationsPart XIX, LNCS Volume 16896: Emerging Techniques and Applications. …

Paperback. Condition: Brand New. 200 pages. 9.26x6.10x0.43 inches. In Stock.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book constitutes the proceedings of the First International Workshop on Machine Learning for Multimodal Healthcare Date, ML4MHD 2023, held in Honolulu, Hawaii, USA, in July 2023.The 18 full papers presented were carefully reviewed and selected from 30 submissions. The workshop's primary objective was to bring together experts from diverse fields such as medicine, pathology, biology, and machine learning. With the aim to present novel methods and solutions that address healthcare challenges, especially those that arise from the complexity and heterogeneity of patient data.…

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