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Artificial Intelligence Applied to Medical Imaging and Computational Biology

Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that general...

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Salvato in:
Natura: Online
Lingua:inglese
Pubblicazione: MDPI - Multidisciplinary Digital Publishing Institute 2023
Soggetti:
distribution patterns
fibroblast cells
HCT-8 colon-cancer cells
nature-inspired techniques
quantification
segmentation
myocardial infarction
vectorcardiogram
multivariate VMD
deep CNN
accuracy
deep learning
image segmentation
brain tumors
radiosurgery
magnetic resonance imaging
age-related macular degeneration
choroidal neovascularization
convolutional neural networks
image classification
optical coherence tomography angiography
brain metastasis
glioblastoma
machine learning
oxygenation
tumor infiltration
breast cancer detection
microwave breast imaging
computer-aided diagnosis (CAD)
first-in-human (FiH) study
semantic segmentation
triceps surae muscle
medical image segmentation
breast cancer
pattern recognition
clinical feasibility
computer-assisted segmentation
artificial intelligence
orthopedics
neural network
mandible
craniomaxillofacial bone
multi-center
histopathology
lung cancer
supervised segmentation
unsupervised segmentation
stroke
fine tactile sensation
electroencephalography
evaluation
n/a
thema EDItEUR::G Reference, Information and Interdisciplinary subjects::GP Research and information: general
thema EDItEUR::P Mathematics and Science::PS Biology, life sciences
thema EDItEUR::T Technology, Engineering, Agriculture, Industrial processes::TB Technology: general issues
Accesso online:ONIX_20230405_9783036564876_90
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Riassunto:Medical imaging and computational biology continuously pose new fundamental medical and biological questions that often give rise to novel challenges in Artificial Intelligence. These research fields present an increasing need for the application of cutting-edge computational approaches that generally involve machine learning or computational intelligence techniques, which can effectively perform bioimage and biosignal processing in different clinical areas.

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