AIMC Topic: Deep Learning

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The Classification of Music and Art Genres under the Visual Threshold of Deep Learning.

Computational intelligence and neuroscience
Wireless networks are commonly employed for ambient assisted living applications, and artificial intelligence-enabled event detection and classification processes have become familiar. However, music is a kind of time-series data, and it is challengi...

Efficient Liver Segmentation from Computed Tomography Images Using Deep Learning.

Computational intelligence and neuroscience
Segmentation of a liver in computed tomography (CT) images is an important step toward quantitative biomarkers for a computer-aided decision support system and precise medical diagnosis. To overcome the difficulties that come across the liver segment...

Developing Acute Event Risk Profiles for Older Adults with Dementia in Long-Term Care Using Motor Behavior Clusters Derived from Deep Learning.

Journal of the American Medical Directors Association
OBJECTIVES: This paper uses deep (machine) learning techniques to develop and test how motor behaviors, derived from location and movement sensor tracking data, may be associated with falls, delirium, and urinary tract infections (UTIs) in long-term ...

Deep Learning Achieves Neuroradiologist-Level Performance in Detecting Hydrocephalus Requiring Treatment.

Journal of digital imaging
In large clinical centers a small subset of patients present with hydrocephalus that requires surgical treatment. We aimed to develop a screening tool to detect such cases from the head MRI with performance comparable to neuroradiologists. We leverag...

Automatic Segmentation and Measurement of Choroid Layer in High Myopia for OCT Imaging Using Deep Learning.

Journal of digital imaging
Automatic segmentation and measurement of the choroid layer is useful in studying of related fundus diseases, such as diabetic retinopathy and high myopia. However, most algorithms are not helpful for choroid layer segmentation due to its blurred bou...

Deep learning of birth-related infant clavicle fractures: a potential virtual consultant for fracture dating.

Pediatric radiology
BACKGROUND: In infant abuse investigations, dating of skeletal injuries from radiographs is desirable to reach a clear timeline of traumatic events. Prior studies have used infant birth-related clavicle fractures as a surrogate to develop a framework...

Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study.

Radiology
Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate t...

Deep Learning model-based approach for preoperative prediction of Ki67 labeling index status in a noninvasive way using magnetic resonance images: A single-center study.

Clinical neurology and neurosurgery
OBJECTIVES: Ki67 is an important biomarker of pituitary adenoma (PA) aggressiveness. In this study, PA invasion of surrounding structures is investigated and deep learning (DL) models are established for preoperative prediction of Ki67 labeling index...

Automatic contouring QA method using a deep learning-based autocontouring system.

Journal of applied clinical medical physics
PURPOSE: To determine the most accurate similarity metric when using an independent system to verify automatically generated contours.