AIMC Topic: Datasets as Topic
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Human Locomotion Databases: A Systematic Review.
IEEE journal of biomedical and health informatics
Mar 6, 2024
The analysis of human locomotion is highly dependent on the quantity and quality of available data to obtain reliable evidence, due to the great variability of gait characteristics between subjects. Researchers usually have to make significant effort...
Automatic Tracking of Hyoid Bone Displacement and Rotation Relative to Cervical Vertebrae in Videofluoroscopic Swallow Studies Using Deep Learning.
Journal of imaging informatics in medicine
Feb 21, 2024
The hyoid bone displacement and rotation are critical kinematic events of the swallowing process in the assessment of videofluoroscopic swallow studies (VFSS). However, the quantitative analysis of such events requires frame-by-frame manual annotatio...
Differential privacy preserved federated learning for prognostic modeling in COVID-19 patients using large multi-institutional chest CT dataset.
Medical physics
Feb 9, 2024
BACKGROUND: Notwithstanding the encouraging results of previous studies reporting on the efficiency of deep learning (DL) in COVID-19 prognostication, clinical adoption of the developed methodology still needs to be improved. To overcome this limitat...
A macro-micro FE and ANN framework to assess site-specific bone ingrowth around the porous beaded-coated implant: an example with BOX® tibial implant for total ankle replacement.
Medical & biological engineering & computing
Feb 7, 2024
The use of mechanoregulatory schemes based on finite element (FE) analysis for the evaluation of bone ingrowth around porous surfaces is a viable approach but requires significant computational time and effort. The aim of this study is to develop a c...
Multicentric clinical evaluation of a computed tomography-based fully automated deep neural network for aortic maximum diameter and volumetric measurements.
Journal of vascular surgery
Feb 5, 2024
OBJECTIVE: This study aims to evaluate a fully automatic deep learning-based method (augmented radiology for vascular aneurysm [ARVA]) for aortic segmentation and simultaneous diameter and volume measurements.
Artificial intelligence in the risk prediction models of cardiovascular disease and development of an independent validation screening tool: a systematic review.
BMC medicine
Feb 5, 2024
BACKGROUND: A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identify, descr...
OPG-based dental age estimation using a data-technical exploration of deep learning techniques.
Journal of forensic sciences
Jan 30, 2024
Dental age estimation, a cornerstone in forensic age assessment, has been extensively tried and tested, yet manual methods are impeded by tedium and interobserver variability. Automated approaches using deep transfer learning encounter challenges lik...
Rule-based deep learning method for prognosis of neonatal hypoxic-ischemic encephalopathy by using susceptibility weighted image analysis.
Magma (New York, N.Y.)
Jan 22, 2024
OBJECTIVE: Susceptibility weighted imaging (SWI) of neonatal hypoxic-ischemic brain injury can provide assistance in the prognosis of neonatal hypoxic-ischemic encephalopathy (HIE). We propose a convolutional neural network model to classify SWI imag...
Deep Learning Auto-Segmentation Network for Pediatric Computed Tomography Data Sets: Can We Extrapolate From Adults?
International journal of radiation oncology, biology, physics
Jan 19, 2024
PURPOSE: Artificial intelligence (AI)-based auto-segmentation models hold promise for enhanced efficiency and consistency in organ contouring for adaptive radiation therapy and radiation therapy planning. However, their performance on pediatric compu...
Modelling dataset bias in machine-learned theories of economic decision-making.
Nature human behaviour
Jan 12, 2024
Normative and descriptive models have long vied to explain and predict human risky choices, such as those between goods or gambles. A recent study reported the discovery of a new, more accurate model of human decision-making by training neural networ...
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