Artificial Intelligence in Medicine

22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part II

Häftad, Engelska, 2024

Av Joseph Finkelstein, Robert Moskovitch, Enea Parimbelli

979 kr

Beställningsvara. Skickas inom 10-15 vardagar

Fri frakt för medlemmar vid köp för minst 249 kr.

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.

Produktinformation

Utgivningsdatum2024-07-27
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieLecture Notes in Artificial Intelligence
Antal sidor366
FörlagSpringer International Publishing AG
ISBN9783031665349

Tillhör följande kategorier

Tillämpad datateknik inom Data och it
Hårdvara inom Data och it
Samhällsmedicin och preventiv medicin inom Medicin
Material och digital teknik i undervisningen inom Psykologi och pedagogik
Medicinsk utrustning och medicinska tekniker inom Medicin
Artificiell intelligens inom Data och it
Databaser inom Data och it

.- 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.