{"product_id":"advanced-intelligent-computing-technology-and-applications-9789819500321","title":"Advanced Intelligent Computing Technology and Applications","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003e.- Healthcare Informatics Theory and Methods.\u003cbr\u003e\u003c\/strong\u003e.- GaMNet: A Hybrid Network with Gabor Fusion and NMamba for Efficient 3D Glioma Segmentation.\u003cbr\u003e.- RSEF: Enhancing Fairness and Accuracy in Hematopoietic Stem Cell  Transplantation Survival Prediction through Race-Stratified Ensemble Framework.\u003cbr\u003e.- The Cyber-Physical System of Oral Health Monitoring: a Data-Driven Approach for Inference.\u003cbr\u003e.- MSSTDCN: A Multi-Scale Spatiotemporal Deep Convolutional Network Based on Power Spectral Density for Cross-Subject Epileptic Seizure Detection.\u003cbr\u003e.- Ocular Disease Classification based on Heterogeneous Interaction among Visual, Diagnostic Semantics, and Generative Knowledge.\u003cbr\u003e.- Energy Efficiency Evaluation Method Based on CNN-BiGRU-Attention in University Integrated Energy System.\u003cbr\u003e.- Adaptive Balancing and Progressive Self-training: An Effective Semi Supervised Method forHistopathological Image Segmentation.\u003cbr\u003e.- Multi-Modality and Multi-Grained Transformer for Accurate Radiology Report Generation.\u003cbr\u003e.- Fine-Tuning Large Language Models for Early Mental Health Intervention in China: A Culturally Adapted Triage and Therapy Framework.\u003cbr\u003e.- Dynamic Bidirectional Attentional Mamba Model for EEG-Based Motor Imagery Classification.\u003cbr\u003e.- A Review of Non-Invasive Brain-Computer Interface Rehabilitation Research for Stroke.\u003cbr\u003e.- Secure Multicenter Medical Model Inference from Homomorphic Encryption.\u003cbr\u003e.- A 3D Liver and Tumor Segmentation Method Based on U-Mamba and Efficient Paired Attention.\u003cbr\u003e.- Mamba-Enhanced Decoder with Prototype Consistency for Semi-Supervised Medical Image Segmentation.\u003cbr\u003e.- BES-UNet: A Boundary Enhanced Sparse Attention UNet for Skin Lesion Segmentation.\u003cbr\u003e.- Memory and Time: A Psychology-Informed Depression Detection.\u003cbr\u003e.- WMCTCF: A Wavelet and Multi-scale Convolution based Transformer Cross-Modal Framework for Early Diagnosis of Alzheimer's Disease.\u003cbr\u003e.- Cali-rPPG: A Unified Uncertainty-Aware Framework for Remote Photoplethysmography.\u003cbr\u003e\u003cstrong\u003e.- Biomedical Informatics Theory and Methods.\u003cbr\u003e\u003c\/strong\u003e.- Noise-aware Self-supervised Electrocardiogram Anomaly Detection.\u003cbr\u003e.- A multimodal small feature set-based assisted Alzheimer's disease diagnosis.\u003cbr\u003e.- Two-Stage Multi-Stained Cell Analysis with the Segment Anything Model for Pathological Image Segmentation.\u003cbr\u003e.- WTPAN-Net: Epileptic Seizure Prediction Model Based on Wavelet Convolutions and Attention Mechanisms.\u003cbr\u003e.- FCGR-Enhancer: A Lightweight Multi-Scale CNN Model for Super Enhancer Identification via Chaos Game Representation.\u003cbr\u003e.- Predicting Potential Associations Between Microbes and Diseases Using Graph Attention Auto-Encoder and PU Learning.\u003cbr\u003e.- Cancer Subtype Recognition Algorithm Based on Hierarchical Attention and Contrastive Learning.\u003cbr\u003e.- GEPD: GAN-Enhanced Generalizable Model for EEG-Based Detection of Parkinson's Disease.\u003cbr\u003e.- CSDT-Net: Integrating Color Space Normalization and Deformable Transformer for Robust Breast Cancer Diagnosis.\u003cbr\u003e.- A Novel Multichannel EEG Analysis Method Using Multiscale Graph Convolution and Cross Attention Transformer for Depression Detection.\u003cbr\u003e.- Multi-level Feature Enhancement Method for Lung Parenchyma Segmentation.\u003cbr\u003e.- Multilevel Residual Sleep Stage Classification Based on Dual-Stream Spatiotemporal 3D Convolutional Neural Networks.\u003cbr\u003e.- RWNet: A Recursive Wavelet-driven Network for Deformable Medical Image Registration.\u003cbr\u003e.- A Mutually Reinforcing Semi-Supervised Active Learning Framework for \u003cbr\u003eLung Surgical Section Image Classification.\u003cbr\u003e.- FPGS-Net: An Enhanced U-Net-Based Architecture for Retinal Vessel Segmentation Integrating Fusion Pooling and Guided-Attention Skip Modules.\u003cbr\u003e.- A New Method for Detecting Cancer Driver Genes by Constructing a Heterogeneous Network with Test-Time Training from Multi-View.\u003cbr\u003e.- AMKD: Adaptive Multi-Modality Knowledge Distillation for Pathological Survival Analysis.\u003cbr\u003e.- HED-Net: Hybrid Encoder and Decoder Network for Medical image Segmentation.\u003cbr\u003e.- YOSAM: A YOLO and MedSAM-Based Framework for Automatic Measurement of Fetal Head Circumference in Ultrasound Images.\u003cbr\u003e.- SAPS-ViM: Spatial Aggregation Prefix Synergistic Vision Mamba for Wheat Diseases Classification.\u003cbr\u003e.- Multidimensional EEG Signal Analysis and Vision Transformer-Masked Autoencoder-Based Image Processing for Alzheimer's Disease Detection.\u003cbr\u003e.- HeartOx: Efficient Multi-task Learning for Contactless Heart Rate and Blood Oxygen Estimation.\u003cbr\u003e.- PISynergy: A Triplet Interaction and Causal Interpretation Framework for Drug Synergy Prediction.\u003cbr\u003e.- Dense Depth-Supervised Simultaneous Localization and Mapping for Robust Bronchoscopic Navigation.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53212848324951,"sku":"9789819500321","price":66.49,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/advanced-intelligent-computing-technology-and-applications-9789819500321","provider":"Book Curl","version":"1.0","type":"link"}