TY  - BOOK
AU  - Finkelstein,Joseph
AU  - Moskovitch,Robert
AU  - Parimbelli,Enea
ED  - SpringerLink (Online service)
TI  - Artificial Intelligence in Medicine: 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9-12, 2024, Proceedings, Part II 
T2  - Lecture Notes in Artificial Intelligence,
SN  - 9783031665356
AV  - Q334-342 
U1  - 006.3 23
PY  - 2024///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Artificial intelligence
KW  - Education
KW  - Data processing
KW  - Computer networks 
KW  - Database management
KW  - Data mining
KW  - Application software
KW  - Artificial Intelligence
KW  - Computers and Education
KW  - Computer Communication Networks
KW  - Database Management
KW  - Data Mining and Knowledge Discovery
KW  - Computer and Information Systems Applications
N1  -  -- 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.  -- 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
N2  - 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
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-66535-6
ER  -