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[null,"1.","Record Nr.",null,"UNINA9910878044503321"]
[null,null,"Autore",null,"Finkelstein Joseph"]
[null,null,"Titolo",null,"Artificial Intelligence in Medicine : 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part II / / edited by Joseph Finkelstein, Robert Moskovitch, Enea Parimbelli"]
[null,null,"Pubbl/distr/stampa",null,"Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024"]
[null,null,"ISBN",null,"9783031665356"]
[{"$nulls":4},"9783031665349"]
[null,null,"Edizione",null,"[1st ed. 2024.]"]
[null,null,"Descrizione fisica",null,"1 online resource (387 pages)"]
[null,null,"Collana",null,"Lecture Notes in Artificial Intelligence, , 2945-9141 ; ; 14845"]
[null,null,"Disciplina",null,"006.3"]
[null,null,"Soggetti",null,"Artificial intelligence"]
[{"$nulls":4},"Education - Data processing"]
[{"$nulls":4},"Computer networks"]
[{"$nulls":4},"Database management"]
[{"$nulls":4},"Data mining"]
[{"$nulls":4},"Application software"]
[{"$nulls":4},"Artificial Intelligence"]
[{"$nulls":4},"Computers and Education"]
[{"$nulls":4},"Computer Communication Networks"]
[{"$nulls":4},"Database Management"]
[{"$nulls":4},"Data Mining and Knowledge Discovery"]
[{"$nulls":4},"Computer and Information Systems Applications"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,"Nota di contenuto",null,"-- 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 "]
[{"$nulls":4},"Nodule Detection.  -- Histology Image Artifact Restoration with Lightweight Transformer and Diffusion Model.  -- Improved Glioma Grade Prediction with Mean Image Transformation.  -- 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.  -- 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.  -- 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."]
[null,null,null,"Sommario/riassunto","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."]