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Artificial Intelligence in Medicine : 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9-12, 2024, Proceedings, Part I
Artificial Intelligence in Medicine : 22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9-12, 2024, Proceedings, Part I
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ISBN No.: 9783031665370
Pages: xxviii, 418
Year: 202407
Format: Trade Paper
Price: $ 103.49
Dispatch delay: Dispatched between 7 to 15 days
Status: Available

- 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.- Bioinformatics and omics.- Breast cancer subtype prediction model integrating domain adaptation with semi-supervised learning on DNA methylation profiles.- CI-VAE for Single-Cell: Leveraging Generative-AI to Enhance Disease Understanding.


- ProteinEngine: Empower LLM with Domain Knowledge for Protein Engineering.- Wearable devices, sensors, and robotics.- Advancements in Non-Invasive AI-Powered Glucose Monitoring: Leveraging Multispectral Imaging Across Diverse Wavelengths.- Anticipating Stress: Harnessing Biomarker Signals from a Wrist-worn Device for Early Prediction.- Improving Reminder Apps for Home Voice Assistants.


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