Artificial intelligence in medicine Part 1
.- Predictive modelling and disease risk prediction..- Applying Gaussian Mixture Model for clustering analysis of emergency room patients based on intubation status..- Bayesian Neural Network to predict antibiotic resistance..- Boosting multitask decomposition: directness, sequentiality, subsampling...
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| Weitere Verfasser: | , , |
| Format: | UnknownFormat |
| Sprache: | eng |
| Veröffentlicht: |
Cham
Springer
2024
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| Schriftenreihe: | Lecture notes in computer science
14844 |
| 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
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| Zusammenfassung: | .- Predictive modelling and disease risk prediction..- Applying Gaussian Mixture Model for clustering analysis of emergency room patients based on intubation status..- Bayesian Neural Network to predict antibiotic resistance..- Boosting multitask decomposition: directness, sequentiality, subsampling, cross-gradients..- Diagnostic Modeling to Identify Unrecognized Inpatient Hypercapnia Using Health Record Data..- Enhancing Hypotension Prediction in Real-time Patient Monitoring Through Deep Learning: A Novel Application of XResNet with Contrastive Learning and Value Attention Mechanisms..- Evaluating the TMR model for multimorbidity decision support using a community-of-practice based methodology..- Frequent patterns of childhood overweight from longitudinal data on parental and early-life of infants health..- Fuzzy neural network model based on uni-nullneuron in extracting knowledge about risk factors of Maternal Health..- Identifying Factors Associated with COVID-19 All-Cause 90-Day Readmission: Machine Learning Approaches..- Mining Disease Progression Patterns for Advanced Disease Surveillance..- Minimizing Survey Questions for PTSD Prediction Following Acute Trauma..- Patient-Centric Approach for Utilising Machine Learning to Predict Health-Related Quality of Life Changes during Chemotherapy..- Predicting Blood Glucose Levels with LMU Recurrent Neural Networks: A Novel Computational Model..- Prediction Modelling and Data Quality Assessment for Nursing Scale in a big hospital: a proposal to save resources and improve data quality..- Process Mining for capacity planning and reconfiguration of a logistics system to enhance the intra-hospital patient transport. Case Study...- Radiotherapy Dose Optimization via Clinical Knowledge Based Reinforcement Learning..- Reinforcement Learning with Balanced Clinical Reward for Sepsis Treatment..- Secure and Private Vertical Federated Learning for Predicting Personalized CVA Outcomes..- Smoking Status Classification: A Comparative Analysis of Machine Learning Techniques with Clinical Real World Data..- The Impact of Data Augmentation on Time Series Classification Models: An In-Depth Study with Biomedical Data..- The Impact of Synthetic Data on Fall Detection Application..- Natural Language Processing..- A Retrieval-Augmented Generation Strategy To Enhance Medical Chatbot Reliability..- Beyond Self-Consistency: Ensemble Reasoning Boosts Consistency and Accuracy of LLMs in Cancer Staging..- Clinical Reasoning over Tabular Data and Text with Bayesian Networks..- Empowering Language Model with Guided Knowledge Fusion for Biomedical Document Re-ranking..- Enhancing Abstract Screening Classification in Evidence-Based Medicine: Incorporating domain knowledge into pre-trained models..- Exploring Pre-trained Language Models for Vocabulary Alignment in the UMLS..- ICU Bloodstream Infection Prediction: A Transformer-Based Approach for EHR Analysis..- Modeling multiple adverse pregnancy outcomes: Learning from diverse data sources..- OptimalMEE: Optimizing Large Language Models for Medical Event Extraction through Fine-tuning and Post-hoc Verification..- Self-Supervised Segment Contrastive Learning for Medical Document Representation 295..- Sentence-aligned Simplification of Biomedical Abstracts..- Sequence-Model-Based Medication Extraction from Clinical Narratives in German..- Social Media as a Sensor: Analyzing Twitter Data for Breast Cancer Medication Effects Using Natural Language Processing..- Bioinformatic 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 |
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| Beschreibung: | Literaturangaben |
| Beschreibung: | xxviii, 418 Seiten Illustrationen, Diagramme |
| ISBN: | 9783031665370 978-3-031-66537-0 |