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001440128 001__ 1440128
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001440128 019__ $$a1269616565$$a1272854824$$a1272954334
001440128 020__ $$a9783030876029$$q(electronic bk.)
001440128 020__ $$a3030876020$$q(electronic bk.)
001440128 020__ $$z9783030876012
001440128 020__ $$z3030876012
001440128 0247_ $$a10.1007/978-3-030-87602-9$$2doi
001440128 035__ $$aSP(OCoLC)1272997555
001440128 040__ $$aEBLCP$$beng$$epn$$cEBLCP$$dGW5XE$$dYDX$$dEBLCP$$dOCLCF$$dOCLCO$$dOCLCQ$$dCOM$$dOCLCO$$dOCLCQ
001440128 049__ $$aISEA
001440128 050_4 $$aR859.7.A78
001440128 08204 $$a610.285/63$$223
001440128 1112_ $$aPRIME (Workshop)$$n(4th :$$d2021 :$$cOnline)
001440128 24510 $$aPredictive intelligence in medicine :$$b4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /$$cIslem Rekik, Ehsan Adeli, Sang Hyun Park, Julia Schnabel (eds.).
001440128 2463_ $$aPRIME 2021
001440128 260__ $$aCham :$$bSpringer,$$c2021.
001440128 300__ $$a1 online resource (292 pages)
001440128 336__ $$atext$$btxt$$2rdacontent
001440128 337__ $$acomputer$$bc$$2rdamedia
001440128 338__ $$aonline resource$$bcr$$2rdacarrier
001440128 4901_ $$aLecture notes in computer science ;$$v12928
001440128 4901_ $$aLNCS sublibrary, SL 6, Image processing, computer vision, pattern recognition, and graphics
001440128 500__ $$aIncludes author index.
001440128 5050_ $$aSelf-Supervised Learning based CT Denoising using Pseudo-CT Image Pairs -- A Few-shot Learning Graph Multi-Trajectory Evolution Network for Forecasting Multimodal Baby Connectivity Development from a Baseline Timepoint -- One Representative-Shot Learning Using a Population-Driven Template with Application to Brain Connectivity Classification and Evolution Prediction -- Mixing-AdaSIN: Constructing a De-biased Dataset using Adaptive Structural Instance Normalization and Texture Mixing -- Liver Tumor Localization and Characterization from Multi-Phase MR Volumes Using Key-Slice Prediction: A Physician-Inspired Approach -- Improving Tuberculosis Recognition on Bone-Suppressed Chest X-rays Guided by Task-Specific Features -- Template-Based Inter-modality Super-resolution of Brain Connectivity -- Adversarial Bayesian Optimization for Quantifying Motion Artifact within MRI -- False Positive Suppression in Cervical Cell Screening via Attention-Guided Semi-Supervised Learning -- Investigating and Quantifying the Reproducibility of Graph Neural Networks in Predictive Medicine -- Self Supervised Contrastive Learning on Multiple Breast Modalities Boosts Classification Performance -- Self-Guided Multi-Attention Network for Periventricular Leukomalacia Recognition -- Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray -- Multi-Task Deep Segmentation and Radiomics for Automatic Prognosis in Head and Neck Cancer -- Integrating Multimodal MRIs for Adult ADHD Identification with Heterogeneous Graph Attention Convolutional Network -- Probabilistic Deep Learning with Adversarial Training and Volume Interval Estimation Better Ways to Perform and Evaluate Predictive Models for White Matter Hyperintensities Evolution -- A Multi-scale Capsule Network for Improving Diagnostic Generalizability in Breast Cancer Diagnosis using Ultrasonography -- Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy using Multi-scale Patch Learning with Mammography -- The Pitfalls of Sample Selection: A Case Study on Lung Nodule Classification -- Anatomical Structure-aware Pulmonary Nodule Detection via Parallel Multi-Task RoI Head -- Towards Cancer Patients Classification Using Liquid Biopsy -- Foreseeing Survival through `Fuzzy Intelligence': A cognitively-inspired incremental learning based de novo model for Breast Cancer Prognosis by multi-omics data fusion -- Improving Across Dataset Brain Age Predictions using Transfer Learning -- Uncertainty-Based Dynamic Graph Neighborhoods For Medical Segmentation -- FLAT-Net: Longitudinal Brain Graph Evolution Prediction from a Few Training Representative Templates.
001440128 506__ $$aAccess limited to authorized users.
001440128 520__ $$aThis book constitutes the proceedings of the 4th International Workshop on Predictive Intelligence in Medicine, PRIME 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in October 2021.* The 25 papers presented in this volume were carefully reviewed and selected for inclusion in this book. The contributions describe new cutting-edge predictive models and methods that solve challenging problems in the medical field for a high-precision predictive medicine. *The workshop was held virtually.
001440128 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed October 7, 2021).
001440128 650_0 $$aArtificial intelligence$$xMedical applications$$vCongresses.
001440128 650_0 $$aPredictive analytics$$vCongresses.
001440128 650_6 $$aIntelligence artificielle en médecine$$vCongrès.
001440128 655_7 $$aConference papers and proceedings.$$2fast$$0(OCoLC)fst01423772
001440128 655_7 $$aConference papers and proceedings.$$2lcgft
001440128 655_7 $$aActes de congrès.$$2rvmgf
001440128 655_0 $$aElectronic books.
001440128 7001_ $$aRekik, Islem.
001440128 7001_ $$aAdeli, Ehsan.
001440128 7001_ $$aPark, Sang Hyun.
001440128 7001_ $$aSchnabel, Julia.
001440128 7112_ $$aInternational Conference on Medical Image Computing and Computer-Assisted Intervention$$n(24th :$$d2021 :$$cOnline)
001440128 77608 $$iPrint version:$$aRekik, Islem.$$tPredictive Intelligence in Medicine.$$dCham : Springer International Publishing AG, ©2021$$z9783030876012
001440128 830_0 $$aLecture notes in computer science ;$$v12928.
001440128 830_0 $$aLNCS sublibrary.$$nSL 6,$$pImage processing, computer vision, pattern recognition, and graphics.
001440128 852__ $$bebk
001440128 85640 $$3Springer Nature$$uhttps://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-87602-9$$zOnline Access$$91397441.1
001440128 909CO $$ooai:library.usi.edu:1440128$$pGLOBAL_SET
001440128 980__ $$aBIB
001440128 980__ $$aEBOOK
001440128 982__ $$aEbook
001440128 983__ $$aOnline
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