LEADER 01764nam 2200373 n 450 001 996395347203316 005 20200824121406.0 035 $a(CKB)4330000000318243 035 $a(EEBO)2248549448 035 $a(UnM)99849545e 035 $a(UnM)99849545 035 $a(EXLCZ)994330000000318243 100 $a19920205d1603 uy | 101 0 $aeng 135 $aurbn||||a|bb| 200 14$aThe first part of the resolution of religion$b[electronic resource] $edivided into two bookes, conteyning a demonstration of the necessitie of a divine and supernaturall worshippe. In the first, against all atheists, and epicures: in the seconde, that Christian Catholic religion is the same in particuler, and more certaine in euery article thereof, then any humane or experimented knowledge, against Iewes, Mahumetans, Pagans, and other external enemies of Christ. Manifestly convincing al their sects and professions, of intollerable errors, and irreligious abuses 205 $aNevvly printed and amended. 210 $aPrinted at Antwerp $cBy Richard Vestegan [i.e. English secret press]$dM.DI. III. [1603] 215 $a[4], 103, [1] p 300 $a"The epistle of the author to the reader" signed: R.B. (i.e. Richard Broughton). 300 $aActual printer and publication date from STC. 300 $aFormerly STC 3896. 300 $aIdentified as STC 3896 on UMI microfilm. 300 $aReproduction of the original in Cambridge University Library. 330 $aeebo-0021 700 $aBroughton$b Richard$01002966 801 0$bCu-RivES 801 1$bCu-RivES 801 2$bCStRLIN 801 2$bWaOLN 906 $aBOOK 912 $a996395347203316 996 $aThe first part of the resolution of religion$92313150 997 $aUNISA LEADER 06129nam 22006735 450 001 996673175103316 005 20250819130242.0 010 $a3-032-00656-2 024 7 $a10.1007/978-3-032-00656-1 035 $a(CKB)40378356600041 035 $a(MiAaPQ)EBC32266796 035 $a(Au-PeEL)EBL32266796 035 $a(OCoLC)1534194856 035 $a(DE-He213)978-3-032-00656-1 035 $a(EXLCZ)9940378356600041 100 $a20250819d2026 u| 0 101 0 $aeng 135 $aur||||||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aArtificial Intelligence in Healthcare $eSecond International Conference, AIiH 2025, Cambridge, UK, September 8?10, 2025, Proceedings, Part II /$fedited by Daniele Cafolla, Timothy Rittman, Hao Ni 205 $a1st ed. 2026. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2026. 215 $a1 online resource (591 pages) 225 1 $aLecture Notes in Computer Science,$x1611-3349 ;$v16039 311 08$a3-032-00655-4 327 $a -- 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. . 330 $aThe two-volume set constitutes the proceedings of the Second International Conference on Artificial Intelligence in Healthcare, AIiH 2025, which took place in Cambridge, UK, in September 2025. The 60 full papers included in this book were carefully reviewed and selected from 83 submissions. They were organized in topical sections as follows: Health informatics, Personalised Healthcare, Robotics, Assisted Living Technology, Computational Medicine, Long-term Health Conditions, Maternity and Women?s Health and Wellbeing. . 410 0$aLecture Notes in Computer Science,$x1611-3349 ;$v16039 606 $aMachine learning 606 $aImage processing$xDigital techniques 606 $aComputer vision 606 $aInformation technology$xManagement 606 $aArtificial intelligence 606 $aMachine Learning 606 $aComputer Imaging, Vision, Pattern Recognition and Graphics 606 $aComputer Application in Administrative Data Processing 606 $aArtificial Intelligence 615 0$aMachine learning. 615 0$aImage processing$xDigital techniques. 615 0$aComputer vision. 615 0$aInformation technology$xManagement. 615 0$aArtificial intelligence. 615 14$aMachine Learning. 615 24$aComputer Imaging, Vision, Pattern Recognition and Graphics. 615 24$aComputer Application in Administrative Data Processing. 615 24$aArtificial Intelligence. 676 $a006.31 700 $aCafolla$b Daniele$01845144 701 $aRittman$b Timothy$01845145 701 $aNi$b Hao$01845146 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996673175103316 996 $aArtificial Intelligence in Healthcare$94428616 997 $aUNISA