Artificial Intelligence in Healthcare

Second International Conference, AIiH 2025, Cambridge, UK, September 8-10, 2025, Proceedings, Part II
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 16039
• Verlag: Springer / Springer Nature Switzerland / Springer, Berlin
• Artikelnr. des Verlages: 89551589, 978-3-032-00655-4
• Seitenzahl: 407
• Erscheinungstermin: 4. September 2025
• Englisch
• Abmessung: 235mm x 155mm
• ISBN-13: 9783032006554
• ISBN-10: 3032006554
• Artikelnr.: 74719298

Inhaltsangabe

.- Machine and deep learning approaches for health data

.- Decoding the Stressed Brain with Geometric Machine Learning
.- Integrating Rule-Based eGFR Labels with Expert GP Annotations: A Multi-Method Framework for CKD Classification.
.- GNN's Uncertainty Quantification using Self-Distillation.
.- Safeguarding Privacy for Medical Data with a Novel Key-Lock Module in Federated Learning.
.- A Bayesian Framework for Multi-Layered Gene Regulation: Integrating Expression Data with Curated Knowledge.

.- Maternity and women s health and wellbeing

.- Leveraging Pretrained Language Models for Maternal Health Monitoring in Online Communities.
.- Patient-Centred Explainability in IVF Outcome prediction.
.- From Clinic to Code: Using Clinician Insights to Develop a Framework for Fair and Representative Datasets in Women's Health AI.

.- Assisted living technology

.- Investigating the Applicability of Gait-based Health Assessment in a Domestic Environment.
.- Evaluating Personalised Beneficial Interventions in the Daily Lives of Older Adults Using a Camera.
.- Enhanced Sparse Point Cloud Data Processing for Privacy-aware Human Action Recognition.

.- AI in mental health

.- Unmasking the Algorithm: Bridging Innovation and Ethics in AI-Enabled Psychological Care.
.- Hybrid Depression Detection from Spontaneous Speech via RFE Majority Voting and WavLM Based Attention.
.- Breathalyzer as a Remote Monitoring and Support System for AUD: Early Findings on Dropout and Relapse Prediction Using Machine Learning.

.- Intelligent systems and robotics

.- Human-centred Design of AI-Driven Robots for Healthcare in a Global Context: a Case Study of AIREC (AI-driven Robot for Embrace and Care).
.- Development of an Adaptive Foot Prosthesis with an Elastic Element and Shock-Absorbing Sole Without the Use of Electric Actuators.
.- A protocol for analysing ankle motion data: a standardized approach to kinematic assessment.

.- AI in echocardiography

.- Spatiotemporal Contrastive Learning for Echocardiography View Classification.
.- Robustness of Human vs. AI Measurements Under Progressive Image Degradation.
.- Deep Learning for Assessing Rotational Misalignment in Echocardiographic Imaging.
.- A Clinician-Centred Interface for AI-Powered Echocardiographic Image Quality Feedback.

.- Medical signal and image processing

.- Domain-Aligned OCT Pre-training: Enhancing Retinal Disease Diagnosis Through Cross-Anatomy Vision Transformers.
.- Graph Convolutional Neural Networks to Model the Brain for Insomnia.
.- Classification-to-Segmentation: Class Activation Mapping for Zero-Shot Skin Lesion Segmentation.
.- Skin Lesion Hybrid Classification and Segmentation based on Extracted Deep Features.
.- Enhancing Cardiac Cell Networks Segmentation via Hybrid Supervised and Zero-Shot Strategies.
.- Detection of multiple cardiac disorders based on heartbeat morphology and time segment analysis of ECG signals.
.- Robust Windowing Harmonisation for Improved Cross-Scanner Generalisation of White Matter Hypoattenuation Segmentation in Brain CT Clinical Scans.
.- Vision Transformers for Interpreting ECG Diagrams.
.- Categorizing acquisition intervals from whole-brain MEG functional connectivity.