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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, Proceedings / edited by Federica Proietto Salanitri, Serestina Viriri, Ulaş Bağcı, Pallavi Tiwari, Boqing Gong, Concetto Spampinato, Simone Palazzo, Giovanni Bellitto, Nancy Zlatintsi, Panagiotis Filntisis, Cecilia S. Lee, Aaron Y. Lee.

Springer Nature - Springer Computer Science (R0) eBooks 2025 English International Available online

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Format:
Book
Author/Creator:
Proietto Salanitri, Federica.
Contributor:
Viriri, Serestina.
Bağcı, Ulaş.
Tiwari, Pallavi.
Gong, Boqing.
Spampinato, Concetto.
Palazzo, Simone.
Bellitto, Giovanni.
Zlatintsi, Nancy.
Filntisis, Panagiotis.
Series:
Lecture Notes in Computer Science, 1611-3349 ; 15197
Language:
English
Subjects (All):
Machine learning.
Machine Learning.
Local Subjects:
Machine Learning.
Physical Description:
1 online resource (113 pages)
Edition:
1st ed. 2025.
Place of Publication:
Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Summary:
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.
Contents:
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.
Notes:
Description based on publisher supplied metadata and other sources.
ISBN:
3-031-73483-1
OCLC:
1460463276

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