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E-book: Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine: First International Workshop, AIPAD 2024 and First International Workshop, PILM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, Proceedings

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  • Format: PDF+DRM
  • Series: Lecture Notes in Computer Science 15197
  • Pub. Date: 02-Oct-2024
  • Publisher: Springer International Publishing AG
  • Language: eng
  • ISBN-13: 9783031734830
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Artificial Intelligence in Pancreatic Disease Detection and Diagnosis, and Personalized Incremental Learning in Medicine: First International Workshop, AIPAD 2024 and First International Workshop, PILM 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 10, 2024, ProceedingsLarger Image
  • Format: PDF+DRM
  • Series: Lecture Notes in Computer Science 15197
  • Pub. Date: 02-Oct-2024
  • Publisher: Springer International Publishing AG
  • Language: eng
  • ISBN-13: 9783031734830
Other books in subject:

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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.
Artificial Intelligence in Pancreatic Disease Detection and
Diagnosis.- Assessing the Efficacy of Foundation Models in Pancreas
Segmentation.- Hybrid Deep Learning Model for Pancreatic Cancer Image
Segmentation.- Leveraging SAM and Learnable Prompts for Pancreatic MRI
Segmentation.- Optimizing Synthetic Data for Enhanced Pancreatic Tumor
Segmentation.- Pancreatic Vessel Landmark Detection in CT Angiography using
Prior Anatomical Knowledge.- Personalized Incremental Learning in
Medicine.-Addressing Catastrophic Forgetting by Modulating Global
Batch Normalization Statistics for Medical Domain
Expansion.- Distribution-Aware Replay for Continual MRI Segmentation.-
Exploring Wearable Emotion Recognition with Transformer-Based Continual
Learning.
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