His main research concerns Audiology, Endoscopic ear surgery, Surgery, Cochlear implant and Middle ear. His Audiology research includes themes of Auditory Brain Stem Implants, Auditory brainstem implant, Inferior colliculus and Neuroscience. His Endoscopic ear surgery study results in a more complete grasp of Endoscope.
As a part of the same scientific study, Daniel J. Lee usually deals with the Endoscope, concentrating on Endoscopy and frequently concerns with Temporal bone, Round window and Suction. His Cochlear implant research is multidisciplinary, incorporating elements of Speech perception, Inner ear and Implant. His Dysplasia research incorporates elements of Head and neck cancer, Carcinoma in situ, Carcinoma, Field cancerization and Tumor progression.
Daniel J. Lee focuses on Surgery, Audiology, Endoscopic ear surgery, Superior canal dehiscence and Cochlear implant. In his research on the topic of Audiology, Cochlear nerve and Electrode array is strongly related with Auditory brainstem implant. His Endoscopic ear surgery research integrates issues from Endoscopy and Otology.
Daniel J. Lee combines subjects such as General surgery and Neurotology with his study of Otology. His Superior canal dehiscence study combines topics from a wide range of disciplines, such as Bone conduction and Etiology. His Cochlear implant study which covers Cochlea that intersects with Brainstem and Inner ear.
His scientific interests lie mostly in Surgery, Endoscopic ear surgery, Otology, Endoscope and Radiology. His Surgery study incorporates themes from Cochlear implantation, Cochlear implant and Significant difference. In Significant difference, Daniel J. Lee works on issues like Radiological weapon, which are connected to Audiology.
Daniel J. Lee is investigating Endoscopic ear surgery as part of his inquiry into Cholesteatoma and Middle ear. His Otology research is multidisciplinary, relying on both Cochlear nerve, Tinnitus, Mastoidectomy, Neurotology and Otorhinolaryngology. Daniel J. Lee focuses mostly in the field of Endoscope, narrowing it down to topics relating to General surgery and, in certain cases, Tympanic cavity.
Daniel J. Lee spends much of his time researching Surgery, Auditory brainstem implant, Mastoidectomy, Otology and Endoscopic ear surgery. He integrates Surgery and Qualitative analysis in his studies. Daniel J. Lee interconnects Fractional anisotropy, Diffusion MRI and Electrode array in the investigation of issues within Auditory brainstem implant.
Daniel J. Lee has included themes like Biomedical engineering and Microscopy in his Mastoidectomy study. His Otology research includes elements of Neurotology, Otorhinolaryngology, Best practice and Medical emergency. Endoscopic ear surgery is a subfield of Cholesteatoma that Daniel J. Lee tackles.
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Learning the parts of objects by non-negative matrix factorization
Daniel D. Lee;H. Sebastian Seung;H. Sebastian Seung.
Nature (1999)
Learning the parts of objects by non-negative matrix factorization
Daniel D. Lee;H. Sebastian Seung;H. Sebastian Seung.
Nature (1999)
Stan: A Probabilistic Programming Language
Bob Carpenter;Andrew Gelman;Matthew D. Hoffman;Daniel Lee.
Journal of Systems and Software (2017)
Stan: A Probabilistic Programming Language
Bob Carpenter;Andrew Gelman;Matthew D. Hoffman;Daniel Lee.
Journal of Systems and Software (2017)
Algorithms for Non-negative Matrix Factorization
Daniel D. Lee;H. Sebastian Seung.
neural information processing systems (2000)
Algorithms for Non-negative Matrix Factorization
Daniel D. Lee;H. Sebastian Seung.
neural information processing systems (2000)
The manifold ways of perception
H. Sebastian Seung;Daniel D. Lee.
Science (2000)
A kernel view of the dimensionality reduction of manifolds
Jihun Ham;Daniel D. Lee;Sebastian Mika;Bernhard Schölkopf.
international conference on machine learning (2004)
A kernel view of the dimensionality reduction of manifolds
Jihun Ham;Daniel D. Lee;Sebastian Mika;Bernhard Schölkopf.
international conference on machine learning (2004)
Grassmann discriminant analysis: a unifying view on subspace-based learning
Jihun Hamm;Daniel D. Lee.
international conference on machine learning (2008)
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