Artificial intelligence in medicine Part 2
.- 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 Gli...
Gespeichert in:
| Körperschaft: | |
|---|---|
| Weitere Verfasser: | , , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Cham
Springer
2024
|
| Schriftenreihe: | Lecture notes in computer science
14845 |
| Schlagworte: |
Angewandte Informatik
> Artificial intelligence
> COMPUTERS / Artificial Intelligence
> COMPUTERS / Computer Science
> COMPUTERS / Database Management / Data Mining
> COMPUTERS / Database Management / General
> COMPUTERS / Expert Systems
> COMPUTERS / Hardware / Network Hardware
> Data Mining
> Data mining
> Databases
> Datenbanken
> EDU029090
> EDUCATION / Computers & Technology
> Educational equipment & technology, computer-aided learning (CAL)
> Expert systems / knowledge-based systems
> Information technology: general issues
> Künstliche Intelligenz
> Lehrmittel, Lerntechnologien, E-Learning
> MED120000
> Konferenzschrift
|
| Online Zugang: | Cover |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Tag hinzufügen 
| Zusammenfassung: | .- 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 Interpre 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 |
|---|---|
| Beschreibung: | Literaturangaben |
| Beschreibung: | xxvii, 366 Seiten Illustrationen, Diagramme |
| ISBN: | 9783031665349 978-3-031-66534-9 |