Artificial Intelligence in Medicine
Springer International Publishing (Verlag)
978-3-031-09341-8 (ISBN)
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.
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.
| Erscheinungsdatum | 13.07.2022 |
|---|---|
| Reihe/Serie | Lecture Notes in Artificial Intelligence | Lecture Notes in Computer Science |
| Zusatzinfo | XX, 456 p. 150 illus., 120 illus. in color. |
| Verlagsort | Cham |
| Sprache | englisch |
| Maße | 155 x 235 mm |
| Gewicht | 730 g |
| Themenwelt | Mathematik / Informatik ► Informatik ► Datenbanken |
| Informatik ► Theorie / Studium ► Algorithmen | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| Schlagworte | Applications • Artificial Intelligence • Communication Systems • Computer Hardware • Computer Networks • Computer Science • Computer systems • computer vision • conference proceedings • Databases • Data Mining • Education • Engineering • Image Analysis • Image Processing • Informatics • Internet • learning • machine learning • Mathematics • Neural networks • Research • Signal Processing • Telecommunication Systems |
| ISBN-10 | 3-031-09341-0 / 3031093410 |
| ISBN-13 | 978-3-031-09341-8 / 9783031093418 |
| Zustand | Neuware |
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