Michalowski / Abidi Artificial Intelligence in Medicine

20th International Conference on Artificial Intelligence in Medicine, AIME 2022, Halifax, NS, Canada, June 14–17, 2022, Proceedings
1. Auflage 2022
ISBN: 978-3-031-09342-5
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, Band 13263, 456 Seiten, eBook

Reihe: Lecture Notes in Computer Science

This book constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Medicine, AIME 2022, held in Halifax, NS, Canada, in June 2022. The 39 full papers presented together with 7 short papers were selected from 113 submissions. The papers are grouped in topical sections on knowledge-based system; machine learning; medical image processing; predictive modeling; natural language processing.

Zielgruppe

Research

Autoren/Hrsg.

Michalowski, Martin

Abidi, Syed Sibte Raza

Abidi, Samina

Inhaltsverzeichnis

Knowledge-Based Systems Explainable Decision Support Using Task Network Models in Notation.- Computerizing Lipid Management Clinical Guidelines as Interactive Task Networks.- Towards an AI planning-based pipeline for the management of multimorbid patients.- A Knowledge Graph Completion Method Applied to Literature-Based Discovery for Predicting Missing Links Targeting Cancer Drug Repurposing.- Ontological Representation of Causal Relations for a Deep Understanding of Associations between Variables in Epidemiology.- Explainable Clinical Decision Support: Towards Patient-Facing Explanations for Education and Long-term Behavior Change.- Machine Learning Assessing Knee Biomechanical Osteoarthritis Severity and Biomechanical Changes After Total Knee Arthroplasty Using Self-Organizing Maps.- NeuralSympCheck: A Symptom Checking and Disease Diagnostic Neural Model with Extracting Surrogate Decision Trees from Black-box Models to Explain the Temporal Importance of Clinical Features in Predicting Kidney Graft Survival.- Recurrence and Self-Attention vs the Transformer for Time-Series Classification: A Comparative Study.- Integrating Graph Convolutional Neural Networks and Long Short-Term Memory for Efficient Diagnosis of Autism.- Hierarchical Deep Multi-task learning for Classification of Patient Diagnoses.- TTS-GAN: A Transformer-based Time-Series Generative Adversarial Network.- Predicting Next Kidney Offer for Transplant Candidate Declining Current One.- Wrist Ultrasound Segmentation by Deep Learning.- Early Detection and Classification of Patient-Ventilator Asynchrony using Machine Learning.- On graph construction for classification of clinical trials protocols using Graph Neural Networks.- Medical Image Processing Malignant Mesothelioma Subtyping of Tissue Images via Sampling Driven Multiple Instance Prediction.- Calibrating Histopathology Image Classifiers using Label Smoothing.- InvUNET: Involuted UNET for Breast Tumor Segmentation from Ultrasound.- MRI reconstructionwith LassoNet and compressed sensing.- Predictive Modeling A 3-window-based framework for the discovery of predictive functional dependencies from clinical data.- When can I expect the mHealth user to return? Prediction meets time series with gaps.- A novel survival analysis approach to predict the need for intubation in intensive care units.- Awareness of being tested and its effect on reading behaviour.- Natural Language Processing Generating extremely short summaries from the scientific literature to support decisions in primary healthcare: a human evaluation study.- A Russian Medical Language Understanding Benchmark.- Biomedical Semantic Textual Similarity: Evaluation of Sentence Representations Enhanced With Principal Component Reduction and Word Frequency Weighting.