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AI for health equity and fairnessleveraging AI to address social determinants of health /

Record Type:	Electronic resources : Monograph/item
Title/Author:	AI for health equity and fairnessedited by Arash Shaban-Nejad, Martin Michalowski, Simone Bianco.
Reminder of title:	leveraging AI to address social determinants of health /
other author:	Shaban-Nejad, Arash.
Published:	Cham :Springer Nature Switzerland :2024.
Description:	xix, 306 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Artificial intelligenceCongresses.Medical applications
Online resource:	https://doi.org/10.1007/978-3-031-63592-2
ISBN:	9783031635922$q(electronic bk.)

AI for health equity and fairnessleveraging AI to address social determinants of health /
AI for health equity and fairnessleveraging AI to address social determinants of health /[electronic resource] :edited by Arash Shaban-Nejad, Martin Michalowski, Simone Bianco. - Cham :Springer Nature Switzerland :2024. - xix, 306 p. :ill., digital ;24 cm. - Studies in computational intelligence,v. 11641860-9503 ;. - Studies in computational intelligence ;v. 216..

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.

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.

ISBN: 9783031635922$q(electronic bk.)

Standard No.: 10.1007/978-3-031-63592-2doiSubjects--Topical Terms:

442992
Artificial intelligence
--Medical applications--Congresses.

LC Class. No.: R859.7.A78

Dewey Class. No.: 610.28563

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520 $a 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.
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