Del 15197 - Lecture Notes in Computer Science

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

Häftad, Engelska, 2024

Av 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, Ulas Bagci, Ula¿ Ba¿C¿

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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.

Produktinformation

Utgivningsdatum2024-10-03
Mått155 x 235 x 7 mm
Vikt189 g
FormatHäftad
SpråkEngelska
SerieLecture Notes in Computer Science
Antal sidor104
FörlagSpringer International Publishing AG
ISBN9783031734823

Tillhör följande kategorier

Systemvetenskap och AI inom Data och it

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.