Artificial Intelligence in Healthcare

Second International Conference, AIiH 2025, Cambridge, UK, September 8-10, 2025, Proceedings, Part I
Herausgegeben:Cafolla, Daniele; Rittman, Timothy; Ni, Hao

• Broschiertes Buch

Produktbeschreibung

The two-volume set constitutes the proceedings of the Second International Conference on Artificial Intelligence in Healthcare, AIiH 2025, which took place in Cambridge, UK, in September 2025.

The 60 full papers included in this book were carefully reviewed and selected from 83 submissions. They were organized in topical sections as follows: Health informatics, Personalised Healthcare, Robotics, Assisted Living Technology, Computational Medicine, Long-term Health Conditions, Maternity and Women s Health and Wellbeing.

Produktdetails

• Lecture Notes in Computer Science 16038
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 89551588, 978-3-032-00651-6
• Seitenzahl: 421
• Erscheinungstermin: 4. September 2025
• Englisch
• Abmessung: 235mm x 155mm
• ISBN-13: 9783032006516
• ISBN-10: 3032006511
• Artikelnr.: 74723456

Inhaltsangabe

.- Ethics of AI in healthcare

.- Empirical Study of Social Bias in Medical Question Answering via Large Language Models.
.- Prompt Injection is All You Need: A Systemic Framework for Evaluating Healthcare Misinformation in LLMs.
.- Early diagnosis and prevention

.- Beyond Accuracy: Enhancing Parkinson s Diagnosis with Uncertainty Quantification of Machine Learning Models.
.- Feature extraction from medical records to increase the accuracy of intracranial aneurysm rupture likelihood.
.- Automated Gross Tumor Volume Segmentation in Meningioma Using Squeeze and Excitation Residual U-Net for Enhanced Radiotherapy Planning.
.- Ensemble Models for Real-Time Fetal Monitoring Using Discrete Segmentation of Cardiotocography.
.- Knowledge Distillation for Computationally Tractable Brain Tumour Segmentation in Sub-Saharan Africa.
.- MICA: A Multimodal Intelligent Cognitive Assessment Framework Integrating Generative AI and Social Robot for Early Cognitive Intervention.
.- Transfer Learning-Based Classification of Diabetic Retinopathy Using a Pre-trained InceptionResNet Model.
.- Markers of Fibromyalgia: Classification and Subtyping Using Self-Reported Measures.
.- Early objective ASD screening system based on eye tracking and machine learning.

.- Proactive care and predictive intervention

.- Performance comparison of machine learning models for the prediction of dialysis treatment variables.
.- Dynamic and explainable mortality risk prediction for TBI patients in the ICU.
.- Opportunistic Screening of Osteoporosis from Dental Panoramic Radiographs using Deep Learning.
.- Speech Breathing Under Cognitive Load: A Pilot Study of English and Arabic Bilingual Adaptation Using the Helicopter Task.
.- Affective State and Pain Estimation through Facial Emotion Analysis.
.- Adaptive Biofeedback for Digital Physiotherapy Using Sakoe-Chiba Constrained Pose Matching.

.- Predictive analytics in healthcare

.- Translating Genes into Insight: Causal Genomics for Diabetes Risk Prediction.
.- A machine learning-based surrogate model of a hemodialyzer for the prediction of the urea dialyzer clearance.

.- Multimodal generative AI

.- CLAIM: Clinically-Guided LGE Augmentation for Realistic and Diverse Myocardial Scar Synthesis and Segmentation.
.- DiabEye-Q: AI-driven Longitudinal Analysis of Ophthalmoscopic Images for Early Diabetes Prediction in Qatari Adults.

.- Healthcare workflow optimisation and automation

.- Concept Type Prompt Patterns for Automated Medical Reporting in Healthcare.
.- Exploring applicability of Text-to-Image models for generating aphasia rehabilitation material.
.- Evaluating the feasibility of using smaller Large Language Models for generating impressions from findings in radiology reports.

.- Machine and deep learning approaches for health data

.- A Comparison of Potentials and Limitations of Transformer Models for Aspect-based Medical Sentiment Analysis.
.- Intelligent Blood Product Management in Hospital: A Data-Driven Model for Optimizing Platelet Inventory.
.- High-Confidence Labelling of Pathology Reports using LLM-Based Unanimous Ensembles with Limited Data.
.- Physicochemical-Based Deep Learning for Allergenicity Prediction.
.- Multi-Modal Deep Learning with Spatial Transformers for Biparametric MRI Prostate Cancer Classification.
.- BCONDS: Borderline Counterfactual Oversampling with Noise elimination and Density Scoring.