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000 nam5i
001 2210080935782
003 DE-He213
005 20250321105631
007 cr nn 008mamaa
008 250207s2025 sz | s |||| 0|eng d
020 a97830318200769978-3-031-82007-6
024 a10.1007/978-3-031-82007-62doi
040 a221008
050 aTA1634
072 aUYQV2bicssc
072 aCOM0160002bisacsh
072 aUYQV2thema
082 a006.37223
245 00 aApplications of Medical Artificial Intelligenceh[electronic resource] :bThird International Workshop, AMAI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings /cedited by Shandong Wu, Behrouz Shabestari, Lei Xing.
250 a1st ed. 2025.
264 aCham :bSpringer Nature Switzerland :bImprint: Springer,c2025.
300 aXI, 265 p. 85 illus., 77 illus. in color.bonline resource.
336 atextbtxt2rdacontent
337 acomputerbc2rdamedia
338 aonline resourcebcr2rdacarrier
347 atext filebPDF2rda
490 aLecture Notes in Computer Science,x1611-3349 ;v15384
505 aExploring 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 Alzheimer’s 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.
520 aThis 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.
650 aComputer vision.
650 aApplication software.
650 aArtificial intelligence.
650 aEducationxData processing.
650 aSocial sciencesxData processing.
650 aComputer Vision.
650 aComputer and Information Systems Applications.
650 aArtificial Intelligence.
650 aComputers and Education.
650 aComputer Application in Social and Behavioral Sciences.
700 aWu, Shandong.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aShabestari, Behrouz.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
700 aXing, Lei.eeditor.4edt4http://id.loc.gov/vocabulary/relators/edt
710 aSpringerLink (Online service)
773 tSpringer Nature eBook
776 iPrinted edition:z9783031820069
776 iPrinted edition:z9783031820083
830 aLecture Notes in Computer Science,x1611-3349 ;v15384
856 uhttps://doi.org/10.1007/978-3-031-82007-6
912 aZDB-2-SCS
912 aZDB-2-SXCS
912 aZDB-2-LNC
950 aComputer Science (SpringerNature-11645)
950 aComputer Science (R0) (SpringerNature-43710)
Applications of Medical Artificial Intelligence[electronic resource] :Third International Workshop, AMAI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings /edited by Shandong Wu, Behrouz Shabestari, Lei Xing
Material type
전자책
Title
Applications of Medical Artificial Intelligence[electronic resource] :Third International Workshop, AMAI 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings /edited by Shandong Wu, Behrouz Shabestari, Lei Xing
Author's Name
판 사항
1st ed. 2025.
Physical Description
XI, 265 p 85 illus, 77 illus in color online resource.
Keyword
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.
내용주기
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 Alzheimer’s 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.
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