Deep Learning–Assisted Diagnosis of Cerebral Aneurysms Using the HeadXNet Model
Sign Up to like & getrecommendations! Published in 2019 at "JAMA Network Open"
DOI: 10.1001/jamanetworkopen.2019.5600
Abstract: Key Points Question How does augmentation with a deep learning segmentation model influence the performance of clinicians in identifying intracranial aneurysms from computed tomographic angiography examinations? Findings In this diagnostic study of intracranial aneurysms, a… read more here.
Keywords: learning; intracranial aneurysms; deep learning; assisted diagnosis ... See more keywords
Evaluating machine learning enhanced intelligent-optimization-engine (IOE) performance for ethos head-and-neck (HN) plan generation.
Sign Up to like & getrecommendations! Published in 2023 at "Journal of applied clinical medical physics"
DOI: 10.1002/acm2.13950
Abstract: PURPOSE Varian Ethos utilizes novel intelligent-optimization-engine (IOE) designed to automate the planning. However, this introduced a black box approach to plan optimization and challenge for planners to improve plan quality. This study aims to evaluate… read more here.
Keywords: ioe; ethos; learning; rtog ... See more keywords
Introduction to artificial intelligence and deep learning using interactive electronic programming notebooks.
Sign Up to like & getrecommendations! Published in 2023 at "Archiv der Pharmazie"
DOI: 10.1002/ardp.202200628
Abstract: Artificial intelligence (AI), or deep learning (DL), approaches have already found their way into our everyday lives. Furthermore, these methods are a central part of research in the life and natural sciences and have been… read more here.
Keywords: introduction artificial; learning; artificial intelligence; deep learning ... See more keywords
Anatomical sciences: A foundation for a solid learning experience in dental technology and dental prosthetics
Sign Up to like & getrecommendations! Published in 2017 at "Anatomical Sciences Education"
DOI: 10.1002/ase.1650
Abstract: Basic science courses are extremely important as a foundation for scaffolding knowledge and then applying it in future courses, clinical situations as well as in a professional career. Anatomical sciences, which include tooth morphology, oral… read more here.
Keywords: learning; dental technology; foundation; dental technicians ... See more keywords
Auditory perceptual learning in autistic adults
Sign Up to like & getrecommendations! Published in 2022 at "Autism Research"
DOI: 10.1002/aur.2778
Abstract: The automatic retuning of phoneme categories to better adapt to the speech of a novel talker has been extensively documented across various (neurotypical) populations, including both adults and children. However, no studies have examined auditory… read more here.
Keywords: perceptual learning; auditory perceptual; learning; learning autistic ... See more keywords
Toward effectiveness and authenticity in PBL: A proposal based on a virtual learning environment in computing education
Sign Up to like & getrecommendations! Published in 2019 at "Computer Applications in Engineering Education"
DOI: 10.1002/cae.22088
Abstract: Problem‐Based Learning (PBL) has gained widespread approval as a constructive, student‐centered approach to teaching, and learning. Advocating the use of real‐life problems to initiate and motivate the learning process, PBL is an inductive strategy promoting… read more here.
Keywords: learning environment; learning; process; virtual learning ... See more keywords
Wildlife surveillance using deep learning methods
Sign Up to like & getrecommendations! Published in 2019 at "Ecology and Evolution"
DOI: 10.1002/ece3.5410
Abstract: Abstract Wildlife conservation and the management of human–wildlife conflicts require cost‐effective methods of monitoring wild animal behavior. Still and video camera surveillance can generate enormous quantities of data, which is laborious and expensive to screen… read more here.
Keywords: learning; surveillance using; deep learning; binary classification ... See more keywords
Federated learning‐based colorectal cancer classification by convolutional neural networks and general visual representation learning
Sign Up to like & getrecommendations! Published in 2023 at "International Journal of Imaging Systems and Technology"
DOI: 10.1002/ima.22875
Abstract: Colorectal cancer is the fourth fatal disease in the world, and the massive burden on the pathologists related to the classification of precancerous and cancerous colorectal lesions can be decreased by deep learning (DL) methods.… read more here.
Keywords: visual representation; representation learning; federated learning; learning ... See more keywords
Effect of shift to virtual teaching on active learning: A snapshot.
Sign Up to like & getrecommendations! Published in 2022 at "Journal of dental education"
DOI: 10.1002/jdd.12910
Abstract: PURPOSE Active learning engages students via interaction for deeper understanding and retention. A global pandemic resulted in an abrupt mid-semester transition from in-person to virtual learning. This study examined student reporting on active learning before… read more here.
Keywords: active learning; frequency; learning; person ... See more keywords
Rapid estimation of patient-specific organ doses using a deep learning network.
Sign Up to like & getrecommendations! Published in 2023 at "Medical physics"
DOI: 10.1002/mp.16356
Abstract: BACKGROUND Patient-specific organ-dose estimation in diagnostic CT examinations can provide useful insights on individualized secondary cancer risks, protocol optimization and patient management. Current dose estimation techniques mainly rely on time-consuming Monte Carlo methods or/and generalized… read more here.
Keywords: specific organ; network; organ doses; patient specific ... See more keywords
Quantification of MR spectra by deep learning in an idealized setting: Investigation of forms of input, network architectures, optimization by ensembles of networks, and training bias
Sign Up to like & getrecommendations! Published in 2022 at "Magnetic Resonance in Medicine"
DOI: 10.1002/mrm.29561
Abstract: The aims of this work are (1) to explore deep learning (DL) architectures, spectroscopic input types, and learning designs toward optimal quantification in MR spectroscopy of simulated pathological spectra; and (2) to demonstrate accuracy and… read more here.
Keywords: spectra deep; quantification spectra; learning; learning idealized ... See more keywords