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240801 ||| eng |
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|a 9783031665356
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| 100 |
1 |
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|a Finkelstein, Joseph
|e [editor]
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| 245 |
0 |
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|a Artificial Intelligence in Medicine
|h Elektronische Ressource
|b 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part II
|c edited by Joseph Finkelstein, Robert Moskovitch, Enea Parimbelli
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| 250 |
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|a 1st ed. 2024
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| 260 |
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|a Cham
|b Springer Nature Switzerland
|c 2024, 2024
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| 300 |
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|a XXVII, 366 p. 121 illus., 110 illus. in color
|b online resource
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| 505 |
0 |
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|a -- Medical imaging analysis. -- 3T to 7T Whole Brain + Skull MRI Translation with Densely Engineered U-Net Network. -- A Sparse Convolutional Autoencoder for Joint Feature Extraction and Clustering of Metastatic Prostate Cancer Images. -- AI in Neuro-Oncology: Predicting EGFR Amplification in Glioblastoma from Whole Slide Images using Weakly Supervised Deep Learning. -- An Exploration of Diabetic Foot Osteomyelitis X-ray Data for Deep Learning Applications. -- Automated Detection and Characterization of Small Cell Lung Cancer Liver Metastases on CT. -- Content-Based Medical Image Retrieval for Medical Radiology Images. -- Cross-Modality Synthesis of T1c MRI from Non-Contrast Images Using GANs: Implications for Brain Tumor Research. -- Harnessing the Power of Graph Propagation in Lung Nodule Detection. -- Histology Image Artifact Restoration with Lightweight Transformer and Diffusion Model. -- Improved Glioma Grade Prediction with Mean Image Transformation. --
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| 505 |
0 |
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|a Explainable AI for Fair Sepsis Mortality Predictive Model. -- Explanations of Augmentation Methods For Deep Learning ECG Classification. -- Exploring the possibility of arrhythmia interpretation of time domain ECG using XAI: a preliminary study. -- Improving XAI Explanations for Clinical Decision-Making – Physicians’ Perspective on Local Explanations in Healthcare. -- Manually-Curated Versus LLM-Generated Explanations for Complex Patient Cases: An Exploratory Study with Physicians. -- On Identifying Effective Investigations with Feature Finding using Explainable AI: an Ophthalmology Case Study. -- Towards Interactive and Interpretable Image Retrieval-Based Diagnosis: Enhancing Brain Tumor Classification with LLM Explanations and Latent Structure Preservation. -- Towards Trustworthy AI in Cardiology: A Comparative Analysis of Explainable AI Methods for Electrocardiogram Interpretation
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| 505 |
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|a Enhancing Anti-VEGF Response Prediction in Diabetic Macular Edema through OCT Features and Clinical Data Integration based on Deep Learning. -- Expert Insight-Enhanced Follow-up Chest X-Ray Summary Generation. -- Integrating multimodal patient data into attention-based graph networks for disease risk prediction. -- Integrative analysis of amyloid imaging and genetics reveals subtypes of Alzheimer progression in early stage. -- Modular Quantitative Temporal Transformer for Biobank-scale Unified Representations. -- Multimodal Fusion of Echocardiography and Electronic Health Records for the Detection of Cardiac Amyloidosis. -- Multi-View $k$-Nearest Neighbor Graph Contrastive Learning on Multi-Modal Biomedical Data. -- Quasi-Orthogonal ECG-Frank XYZ Transformation with Energy-based models and clinical text. -- Explainable AI. -- Do you trust your model explanations? An analysis of XAI performance under dataset shift. --
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| 505 |
0 |
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|a Learning to Predict the Optimal Template in Stain Normalization For Histology Image Analysis. -- MRI Brain Cancer Image Detection Application of an Integrated U-Net and ResNet50 Architecture. -- MRI Scan Synthesis Methods based on Clustering and Pix2Pix. -- Supervised Pectoral Muscle Removal in Mammography Images. -- TinySAM-Med3D: A Lightweight Segment Anything Model for Volumetric Medical Imaging with Mixture of Experts. -- Towards a Formal Description of Artificial Intelligence Models and Datasets in Radiology. -- Towards Aleatoric and Epistemic Uncertainty in Medical Image Classification. -- Ultrasound Image Segmentation via a Multi-Scale Salient Network. -- Data integration and multimodal analysis. -- A 360-Degree View for Large Language Models: Early Detection of Amblyopia in Children using Multi-View Eye Movement Recordings. --
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| 653 |
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|a Computer Communication Networks
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| 653 |
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|a Education / Data processing
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| 653 |
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|a Artificial Intelligence
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| 653 |
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|a Database Management
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| 653 |
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|a Computers and Education
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| 653 |
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|a Data mining
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| 653 |
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|a Application software
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|a Computer networks
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| 653 |
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|a Artificial intelligence
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| 653 |
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|a Data Mining and Knowledge Discovery
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| 653 |
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|a Computer and Information Systems Applications
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| 653 |
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|a Database management
|
| 700 |
1 |
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|a Moskovitch, Robert
|e [editor]
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| 700 |
1 |
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|a Parimbelli, Enea
|e [editor]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a Lecture Notes in Artificial Intelligence
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| 028 |
5 |
0 |
|a 10.1007/978-3-031-66535-6
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| 856 |
4 |
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|u https://doi.org/10.1007/978-3-031-66535-6?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
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|a 006.3
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| 520 |
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|a This two-volume set LNAI 14844-14845 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Medicine, AIME 2024, held in Salt Lake City, UT, USA, during July 9-12, 2024. The 54 full papers and 22 short papers presented in the book were carefully reviewed and selected from 335 submissions. The papers are grouped in the following topical sections: Part I: Predictive modelling and disease risk prediction; natural language processing; bioinformatics and omics; and wearable devices, sensors, and robotics. Part II: Medical imaging analysis; data integration and multimodal analysis; and explainable AI.
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