Artificial Intelligence in Medicine

22nd International Conference, AIME 2024, Salt Lake City, UT, USA, July 9–12, 2024, Proceedings, Part I

AvJoseph Finkelstein,Robert Moskovitch

Häftad, Engelska, 2024

Del 14844 i serien Lecture Notes in Computer Science

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2024-07-26
Mått:155 x 235 x 25 mm
Vikt:674 g
Format:Häftad
Språk:Engelska
Serie:Lecture Notes in Computer Science
Antal sidor:418
Förlag:Springer International Publishing AG
ISBN:9783031665370

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Innehållsförteckning

.- 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.