AI for Health Equity and Fairness

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Details

This book aims to highlight the latest achievements in the use of AI for improving Health Equity and Fairness. The edited volume contains selected papers presented at the 2024 Health Intelligence workshop, co-located with the Thirty-Eight Association for the Advancement of Artificial Intelligence (AAAI) conference, and presents an overview of the issues, challenges, and potentials in the field, along with new research results. This book provides information for researchers, students, industry professionals, clinicians, and public health agencies interested in the applications of AI in medicine and public health.


Highlights the latest achievements in the use of AI in improving healthy equity Includes revised versions of selected papers presented at the 2024 AAAI Workshop on Health Intelligence Interconnects three major fields: artificial intelligence, medicine and clinical and public health informatics

Inhalt

Artificial Intelligence for Personalized Care, Wellness and Longevity Research.- Towards Personalised Patient Risk Prediction Using Temporal Hospital Data Trajectories.- Ambulance Routing for Optimizing Stroke Patient Outcomes.- Navigating the Synthetic Realm Harnessing Diffusion based Models for Laparoscopic Text to Image Generation.- Generation of Clinical Skin Images with Pathology with Scarce Data.- MILFORMER Weighted Dual Stream Class Centered Random Attention Multiple Instance Learning for Whole Slide Image Classification.- Multi-Prompt Fine Tuning of Foundation Models for Enhanced Biomedical Image Segmentation.- A Transformer Approach for Cognitive Impairment Classification.- Deep Learning Approach to Identify Diabetic Retinopathy Severity and Progression Using Ultra Wide Field Retinal Images.- DOST Domain Obedient Self supervision for Trustworthy Multi Label Classification with Noisy Labels.- Using Large Language Models for Generating Smart Contracts for Health Insurance from Textual Policies.- Can GPT Improve the State of Prior Authorization via Guideline Based Automated Question Answering.- Designing Retrieval Augmented Language Models for Clinical Decision Support.- Co morbidity Representation in Artificial Intelligence Tapping into Unused Clinical Knowledge.- MedBlindTuner Towards Privacy preserving Fine tuning on Biomedical Images with Transformers and Fully Homomorphic Encryption.- Knowledge Grounded Medical Dialogue Generation.- Interpretable Classification of Early Stage Parkinson's Disease from EEG.- Semantic and Visual Attention Driven Multi LSTM Network for Automated Clinical Report Generation.- Hierarchical Multi Label Classification of Online Vaccine Concerns.- A Semantic Architecture for Continuous Health Monitoring, Risk Prediction, and Proactive Decision Making.- On the Feasibility of Multimodal Dialog Based Remote Balance Assessment.- SAIC Integration of Speech Anonymization and Identity Classification.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031635915
    • Genre Technology Encyclopedias
    • Editor Arash Shaban-Nejad, Martin Michalowski, Simone Bianco
    • Lesemotiv Verstehen
    • Anzahl Seiten 328
    • Herausgeber Springer
    • Größe H241mm x B160mm x T24mm
    • Jahr 2024
    • EAN 9783031635915
    • Format Fester Einband
    • ISBN 3031635914
    • Veröffentlichung 23.08.2024
    • Titel AI for Health Equity and Fairness
    • Untertitel Leveraging AI to Address Social Determinants of Health
    • Gewicht 658g
    • Sprache Englisch

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