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Applications of Medical Artificial Intelligence: Third International Workshop, AMAI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings [Mīkstie vāki]

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  • Formāts: Paperback / softback, 265 pages, height x width: 235x155 mm, 77 Illustrations, color; 8 Illustrations, black and white; XI, 265 p. 85 illus., 77 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 15384
  • Izdošanas datums: 08-Feb-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031820061
  • ISBN-13: 9783031820069
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Applications of Medical Artificial Intelligence: Third International Workshop, AMAI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, ProceedingsPalielināt
  • Formāts: Paperback / softback, 265 pages, height x width: 235x155 mm, 77 Illustrations, color; 8 Illustrations, black and white; XI, 265 p. 85 illus., 77 illus. in color., 1 Paperback / softback
  • Sērija : Lecture Notes in Computer Science 15384
  • Izdošanas datums: 08-Feb-2025
  • Izdevniecība: Springer International Publishing AG
  • ISBN-10: 3031820061
  • ISBN-13: 9783031820069
Citas grāmatas par šo tēmu:
Permanent link: https://www.kriso.lv/db/9783031820069.html
This book constitutes the refereed proceedings of the Third International Workshop on Applications of Medical Artificial Intelligence, AMAI 2024, held in conjunction with MICCAI 2024, in Marrakesh, Morocco on October 6th, 2024.





The volume includes 24 papers which were carefully reviewed and selected from 59 submissions. The AMAI 2024 workshop created a forum to bring together researchers, clinicians, domain experts, AI practitioners, industry representatives, and students to investigate and discuss various challenges and opportunities related to applications of medical AI.
Exploring CNN and Transformer-based Architectures to Improve Image
Segmentation for Chronic Wound Measurement.- From Pixel Scores to Clinical
Impacts: The Implicit Choices in FROC Metric Design and Their
Consequences.- Head CT Scan Motion Artifact Correction via Diffusion-Based
Generative Models.- SP-NAS: Surgical Phase Recognition-based Navigation
Adjustment System for distal gastrectomy.- Transforming Multimodal Models
into Action Models for Radiotherapy.- Enhanced Interpretability in
Histopathological Images via Combined Tissue and Cell-Level Graph
Analysis.- Targeted Visual Prompting for Medical Visual Question
Answering.- Deep Learning for Resolving 3D Microstructural Changes in the
Fibrotic Liver.- Predicting Falls through Muscle Weakness from a Single Whole
Body Image: A Multimodal Contrastive Learning Framework.- Optimizing ICU
Readmission Prediction: A Comparative Evaluation of AI Tools.- Source
Matters: Source Dataset Impact on Model Robustness in Medical
Imaging.- Evaluating Perceived Workload, Usability and Usefulness of
Artificial Intelligence Systems in Low-Resource Settings: Semi-Automated
Classification and Detection of Community Acquired Pneumonia.- Incremental
Augmentation Strategies for Personalised Continual Learning in Digital
Pathology Contexts.- Assessing Generalization Capabilities of Malaria
Diagnostic Models from Thin Blood Smears.- Automated Feedback System for
Surgical Skill Improvement in Endoscopic Sinus Surgery.- Quantifying Knee
Cartilage Shape and Lesion: From Image to Metrics.- RadImageGAN A
Multi-modal Dataset-Scale Generative AI for Medical Imaging.- Ensemble-KAN:
Leveraging Kolmogorov Arnold Networks to Discriminate Individuals with
Psychiatric Disorders from Controls.- SCIsegV2: A Universal Tool for
Segmentation of Intramedullary Lesions in Spinal Cord Injury.- EHRmonize: A
Framework for Medical Concept Abstraction from Electronic Health Records
using Large Language Models.- Evaluating the Impact of Pulse Oximetry Bias in
Machine Learning under Counterfactual Thinking.- Normative Modeling with
Focal Loss and Adversarial Autoencoders for Alzheimers Disease Diagnosis and
Biomarker Identification.- One-Shot Medical Video Object Segmentation via
Temporal Contrastive Memory Networks.- Data-Efficient Radiology Report
Generation via Similar Report Features Enhancement.