Zobrazeno 1 - 10
of 54
pro vyhledávání: '"Michael J. Keiser"'
Autor:
Juan C. Vizcarra, Thomas M. Pearce, Brittany N. Dugger, Michael J. Keiser, Marla Gearing, John F. Crary, Evan J. Kiely, Meaghan Morris, Bartholomew White, Jonathan D. Glass, Kurt Farrell, David A. Gutman
Publikováno v:
Acta Neuropathologica Communications, Vol 11, Iss 1, Pp 1-20 (2023)
Abstract Machine learning (ML) has increasingly been used to assist and expand current practices in neuropathology. However, generating large imaging datasets with quality labels is challenging in fields which demand high levels of expertise. Further
Externí odkaz:
https://doaj.org/article/b2678bd5981b4644b024934250897893
Autor:
Daniel R. Wong, Shino D. Magaki, Harry V. Vinters, William H. Yong, Edwin S. Monuki, Christopher K. Williams, Alessandra C. Martini, Charles DeCarli, Chris Khacherian, John P. Graff, Brittany N. Dugger, Michael J. Keiser
Publikováno v:
Communications Biology, Vol 6, Iss 1, Pp 1-9 (2023)
Abstract Precise, scalable, and quantitative evaluation of whole slide images is crucial in neuropathology. We release a deep learning model for rapid object detection and precise information on the identification, locality, and counts of cored plaqu
Externí odkaz:
https://doaj.org/article/c3d3f3daf1b44aed967015946cc7eb2d
Publikováno v:
Cell Genomics, Vol 3, Iss 10, Pp 100410- (2023)
Summary: Natural and experimental genetic variants can modify DNA loops and insulating boundaries to tune transcription, but it is unknown how sequence perturbations affect chromatin organization genome wide. We developed a deep-learning strategy to
Externí odkaz:
https://doaj.org/article/664dcf7d1471438eb189123408b2644a
Autor:
Daniel R. Wong, Ziqi Tang, Nicholas C. Mew, Sakshi Das, Justin Athey, Kirsty E. McAleese, Julia K. Kofler, Margaret E. Flanagan, Ewa Borys, Charles L. White, Atul J. Butte, Brittany N. Dugger, Michael J. Keiser
Publikováno v:
Acta Neuropathologica Communications, Vol 10, Iss 1, Pp 1-22 (2022)
Abstract Pathologists can label pathologies differently, making it challenging to yield consistent assessments in the absence of one ground truth. To address this problem, we present a deep learning (DL) approach that draws on a cohort of experts, we
Externí odkaz:
https://doaj.org/article/e7fb3386bbae4059a6d4c1c8990efffb
Autor:
Albert T. Young, Kristen Fernandez, Jacob Pfau, Rasika Reddy, Nhat Anh Cao, Max Y. von Franque, Arjun Johal, Benjamin V. Wu, Rachel R. Wu, Jennifer Y. Chen, Raj P. Fadadu, Juan A. Vasquez, Andrew Tam, Michael J. Keiser, Maria L. Wei
Publikováno v:
npj Digital Medicine, Vol 4, Iss 1, Pp 1-8 (2021)
Abstract Artificial intelligence models match or exceed dermatologists in melanoma image classification. Less is known about their robustness against real-world variations, and clinicians may incorrectly assume that a model with an acceptable area un
Externí odkaz:
https://doaj.org/article/89fc976ac492433b853698240fbfcfbb
Autor:
Juan C. Vizcarra, Marla Gearing, Michael J. Keiser, Jonathan D. Glass, Brittany N. Dugger, David A. Gutman
Publikováno v:
Acta Neuropathologica Communications, Vol 8, Iss 1, Pp 1-13 (2020)
Abstract Semi-quantitative scoring schemes like the Consortium to Establish a Registry for Alzheimer’s Disease (CERAD) are the most commonly used method in Alzheimer’s disease (AD) neuropathology practice. Computational approaches based on machin
Externí odkaz:
https://doaj.org/article/2b0940b081664ec588da8f7b0109d6be
Autor:
Matthew N. McCarroll, Leo Gendelev, Reid Kinser, Jack Taylor, Giancarlo Bruni, Douglas Myers-Turnbull, Cole Helsell, Amanda Carbajal, Capria Rinaldi, Hye Jin Kang, Jung Ho Gong, Jason K. Sello, Susumu Tomita, Randall T. Peterson, Michael J. Keiser, David Kokel
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-14 (2019)
Some anesthetics despite being generally associated with sedation, can also increase brain activity—a phenomenon called paradoxical excitation. The authors identified dozens of compounds that generally decrease neuronal activity, but increase activ
Externí odkaz:
https://doaj.org/article/800557a8a9ec49a7a80e98ddf53a8be2
Autor:
Ziqi Tang, Kangway V. Chuang, Charles DeCarli, Lee-Way Jin, Laurel Beckett, Michael J. Keiser, Brittany N. Dugger
Publikováno v:
Nature Communications, Vol 10, Iss 1, Pp 1-14 (2019)
Convolutional neural networks have been applied to various areas of medical imaging and histology. Here the authors develop an automated approach using interpretable neural networks to determine Alzheimer’s disease plaque and cerebral amyloid angio
Externí odkaz:
https://doaj.org/article/ba915e392b8548368af02fe9f5bed428
Autor:
Samantha J. Hindle, Roeben N. Munji, Elena Dolghih, Garrett Gaskins, Souvinh Orng, Hiroshi Ishimoto, Allison Soung, Michael DeSalvo, Toshihiro Kitamoto, Michael J. Keiser, Matthew P. Jacobson, Richard Daneman, Roland J. Bainton
Publikováno v:
Cell Reports, Vol 21, Iss 5, Pp 1304-1316 (2017)
Summary: Central nervous system (CNS) chemical protection depends upon discrete control of small-molecule access by the blood-brain barrier (BBB). Curiously, some drugs cause CNS side-effects despite negligible transit past the BBB. To investigate th
Externí odkaz:
https://doaj.org/article/ab536355a3d44a6c8f5909e9d8116224
Publikováno v:
Journal of Chemical Information and Modeling. 60:5957-5970
Multitask deep neural networks learn to predict ligand-target binding by example, yet public pharmacological datasets are sparse, imbalanced, and approximate. We constructed two hold-out benchmarks to approximate temporal and drug-screening test scen