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024	7		_a10.1007/978-3-030-87602-9 _2doi
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245	1	0	_aPredictive Intelligence in Medicine _h[electronic resource] : _b4th International Workshop, PRIME 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings / _cedited by Islem Rekik, Ehsan Adeli, Sang Hyun Park, Julia Schnabel.
250			_a1st ed. 2021.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2021.
300			_aXIII, 280 p. 80 illus., 68 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aImage Processing, Computer Vision, Pattern Recognition, and Graphics, _x3004-9954 ; _v12928
505	0		_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 SampleSelection: 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.
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.
650		0	_aArtificial intelligence.
650		0	_aImage processing _xDigital techniques.
650		0	_aComputer vision.
650		0	_aComputer engineering.
650		0	_aComputer networks .
650		0	_aBioinformatics.
650	1	4	_aArtificial Intelligence.
650	2	4	_aComputer Imaging, Vision, Pattern Recognition and Graphics.
650	2	4	_aComputer Engineering and Networks.
650	2	4	_aComputational and Systems Biology.
700	1		_aRekik, Islem. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aAdeli, Ehsan. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aPark, Sang Hyun. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
700	1		_aSchnabel, Julia. _eeditor. _4edt _4http://id.loc.gov/vocabulary/relators/edt
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9783030876012
776	0	8	_iPrinted edition: _z9783030876036
830		0	_aImage Processing, Computer Vision, Pattern Recognition, and Graphics, _x3004-9954 ; _v12928
856	4	0	_uhttps://doi.org/10.1007/978-3-030-87602-9
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