Search Results - "Nick Bryan, R"

Emerging Applications of Artificial Intelligence in Neuro-Oncology by Rudie, Jeffrey D, Rauschecker, Andreas M, Bryan, R Nick, Davatzikos, Christos, Mohan, Suyash

“…Due to the exponential growth of computational algorithms, artificial intelligence (AI) methods are poised to improve the precision of diagnostic and…”
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Machine Learning Applied to Alzheimer Disease by Bryan, R Nick

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Artificial Intelligence System Approaching Neuroradiologist-level Differential Diagnosis Accuracy at Brain MRI by Rauschecker, Andreas M, Rudie, Jeffrey D, Xie, Long, Wang, Jiancong, Duong, Michael Tran, Botzolakis, Emmanuel J, Kovalovich, Asha M, Egan, John, Cook, Tessa C, Bryan, R Nick, Nasrallah, Ilya M, Mohan, Suyash, Gee, James C

“…Background Although artificial intelligence (AI) shows promise across many aspects of radiology, the use of AI to create differential diagnoses for rare and…”
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MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide by Bashyam, Vishnu M, Erus, Guray, Doshi, Jimit, Habes, Mohamad, Nasrallah, Ilya, Truelove-Hill, Monica, Srinivasan, Dhivya, Mamourian, Liz, Pomponio, Raymond, Fan, Yong, Launer, Lenore J, Masters, Colin L, Maruff, Paul, Zhuo, Chuanjun, Völzke, Henry, Johnson, Sterling C, Fripp, Jurgen, Koutsouleris, Nikolaos, Satterthwaite, Theodore D, Wolf, Daniel, Gur, Raquel E, Gur, Ruben C, Morris, John, Albert, Marilyn S, Grabe, Hans J, Resnick, Susan, Bryan, R Nick, Wolk, David A, Shou, Haochang, Davatzikos, Christos

“…Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes…”
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Artificial intelligence for precision education in radiology by Duong, Michael Tran, Rauschecker, Andreas M, Rudie, Jeffrey D, Chen, Po-Hao, Cook, Tessa S, Bryan, R Nick, Mohan, Suyash

“…In the era of personalized medicine, the emphasis of health care is shifting from populations to individuals. Artificial intelligence (AI) is capable of…”
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DEEPMIR: a deep neural network for differential detection of cerebral microbleeds and iron deposits in MRI by Rashid, Tanweer, Abdulkadir, Ahmed, Nasrallah, Ilya M., Ware, Jeffrey B., Liu, Hangfan, Spincemaille, Pascal, Romero, J. Rafael, Bryan, R. Nick, Heckbert, Susan R., Habes, Mohamad

“…Lobar cerebral microbleeds (CMBs) and localized non-hemorrhage iron deposits in the basal ganglia have been associated with brain aging, vascular disease and…”
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The Brain Chart of Aging: Machine‐learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans by Habes, Mohamad, Pomponio, Raymond, Shou, Haochang, Doshi, Jimit, Mamourian, Elizabeth, Erus, Guray, Nasrallah, Ilya, Launer, Lenore J., Rashid, Tanweer, Bilgel, Murat, Fan, Yong, Toledo, Jon B., Yaffe, Kristine, Sotiras, Aristeidis, Srinivasan, Dhivya, Espeland, Mark, Masters, Colin, Maruff, Paul, Fripp, Jurgen, Völzk, Henry, Johnson, Sterling C., Morris, John C., Albert, Marilyn S., Miller, Michael I., Bryan, R. Nick, Grabe, Hans J., Resnick, Susan M., Wolk, David A., Davatzikos, Christos

“…Introduction Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology…”
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Deep Generative Medical Image Harmonization for Improving Cross‐Site Generalization in Deep Learning Predictors by Bashyam, Vishnu M., Doshi, Jimit, Erus, Guray, Srinivasan, Dhivya, Abdulkadir, Ahmed, Singh, Ashish, Habes, Mohamad, Fan, Yong, Masters, Colin L., Maruff, Paul, Zhuo, Chuanjun, Völzke, Henry, Johnson, Sterling C., Fripp, Jurgen, Koutsouleris, Nikolaos, Satterthwaite, Theodore D., Wolf, Daniel H., Gur, Raquel E., Gur, Ruben C., Morris, John C., Albert, Marilyn S., Grabe, Hans J., Resnick, Susan M., Bryan, Nick R., Wittfeld, Katharina, Bülow, Robin, Wolk, David A., Shou, Haochang, Nasrallah, Ilya M., Davatzikos, Christos

“…Background In the medical imaging domain, deep learning‐based methods have yet to see widespread clinical adoption, in part due to limited generalization…”
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Long Term Effect of Intensive Lifestyle Intervention on Cerebral Blood Flow by Espeland, Mark A., Luchsinger, Jose A., Neiberg, Rebecca H., Carmichael, Owen, Laurienti, Paul J., Pi‐Sunyer, Xavier, Wing, Rena R., Cook, Delilah, Horton, Edward, Casanova, Ramon, Erickson, Kirk, Nick Bryan, R.

“…Objectives To determine whether long‐term behavioral intervention targeting weight loss through increased physical activity and reduced caloric intake would…”
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Effects of intensive glucose lowering on brain structure and function in people with type 2 diabetes (ACCORD MIND): a randomised open-label substudy by Launer, Lenore J, Dr, Miller, Michael E, PhD, Williamson, Jeff D, MD, Lazar, Ron M, PhD, Gerstein, Hertzel C, MD, Murray, Anne M, MD, Sullivan, Mark, MD, Horowitz, Karen R, MD, Ding, Jingzhong, PhD, Marcovina, Santica, PhD, Lovato, Laura C, MS, Lovato, James, MS, Margolis, Karen L, MD, O'Connor, Patrick, MD, Lipkin, Edward W, MD, Hirsch, Joy, MD, Coker, Laura, PhD, Maldjian, Joseph, MD, Sunshine, Jeffrey L, MD, Truwit, Charles, MD, Davatzikos, Christos, PhD, Bryan, R Nick, MD

“…Summary Background People with type 2 diabetes are at risk of cognitive impairment and brain atrophy. We aimed to compare the effects on cognitive function and…”
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Vascular factors and multiple measures of early brain health: CARDIA brain MRI study by Launer, Lenore J, Lewis, Cora E, Schreiner, Pamela J, Sidney, Steve, Battapady, Harsha, Jacobs, David R, Lim, Kelvin O, D'Esposito, Mark, Zhang, Qian, Reis, Jared, Davatzikos, Christos, Bryan, R Nick

“…To identify early changes in brain structure and function that are associated with cardiovascular risk factors (CVRF). Cross-sectional brain Magnetic Resonance…”
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Influence of Type 2 Diabetes on Brain Volumes and Changes in Brain Volumes: Results from the Women's Health Initiative Magnetic Resonance Imaging Studies by ESPELAND, Mark A, NICK BRYAN, R, MASAKI, Kamal, ROSSOM, Rebecca, RESNICK, Susan M, GOVEAS, Joseph S, ROBINSON, Jennifer G, SIDDIQUI, Mustafa S, LIU, Simin, HOGAN, Patricia E, CASANOVA, Ramon, COKER, Laura H, YAFFE, Kristine

“…To study how type 2 diabetes adversely affects brain volumes, changes in volume, and cognitive function. Regional brain volumes and ischemic lesion volumes in…”
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Cigarette smoking and gray matter brain volumes in middle age adults: the CARDIA Brain MRI sub-study by Elbejjani, Martine, Auer, Reto, Jacobs, David R., Haight, Thaddeus, Davatzikos, Christos, Goff, David C., Bryan, R. Nick, Launer, Lenore J.

“…Cigarette smoking has been associated with dementia and dementia-related brain changes, notably gray matter (GM) volume atrophy. These associations are thought…”
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Multiscale functional connectivity patterns of the aging brain learned from harmonized rsfMRI data of the multi-cohort iSTAGING study by Zhou, Zhen, Li, Hongming, Srinivasan, Dhivya, Abdulkadir, Ahmed, Nasrallah, Ilya M., Wen, Junhao, Doshi, Jimit, Erus, Guray, Mamourian, Elizabeth, Bryan, Nick R., Wolk, David A., Beason-Held, Lori, Resnick, Susan M., Satterthwaite, Theodore D., Davatzikos, Christos, Shou, Haochang, Fan, Yong

“…•Multiscale functional connectivity pattern of the aging brain were learned from a large-scale multisite fMRI datasets.•A machine learning model built on the…”
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Vascular risk factors, cerebrovascular reactivity, and the default-mode brain network by Haight, Thaddeus J., Bryan, R. Nick, Erus, Guray, Davatzikos, Christos, Jacobs, David R., D'Esposito, Mark, Lewis, Cora E., Launer, Lenore J.

“…Cumulating evidence from epidemiologic studies implicates cardiovascular health and cerebrovascular function in several brain diseases in late life. We…”
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Association of Brain Volumes and White Matter Injury With Race, Ethnicity, and Cardiovascular Risk Factors: The Multi-Ethnic Study of Atherosclerosis by Austin, Thomas R, Nasrallah, Ilya M, Erus, Guray, Desiderio, Lisa M, Chen, Lin Y, Greenland, Philip, Harding, Barbara N, Hughes, Timothy M, Jensen, Paul N, Longstreth, Jr, W T, Post, Wendy S, Shea, Steven J, Sitlani, Colleen M, Davatzikos, Christos, Habes, Mohamad, Nick Bryan, R, Heckbert, Susan R

“…Background Cardiovascular risk factors are associated with cognitive decline and dementia. Magnetic resonance imaging provides sensitive measurement of brain…”
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Comparison of non-invasive MRI measurements of cerebral blood flow in a large multisite cohort by Dolui, Sudipto, Wang, Ze, Wang, Danny JJ, Mattay, Raghav, Finkel, Mack, Elliott, Mark, Desiderio, Lisa, Inglis, Ben, Mueller, Bryon, Stafford, Randall B, Launer, Lenore J, Jacobs, David R, Bryan, R Nick, Detre, John A

“…Arterial spin labeling and phase contrast magnetic resonance imaging provide independent non-invasive methods for measuring cerebral blood flow. We compared…”
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Effect of diabetes on brain structure: the action to control cardiovascular risk in diabetes MR imaging baseline data by Bryan, R Nick, Bilello, Michel, Davatzikos, Christos, Lazar, Ronald M, Murray, Anne, Horowitz, Karen, Lovato, James, Miller, Michael E, Williamson, Jeff, Launer, Lenore J

“…To investigate the association of characteristics of type 2 diabetes mellitus (duration and biochemical severity of diabetes) to brain structure measured on…”
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Computer-Assisted Segmentation of White Matter Lesions in 3D MR Images Using Support Vector Machine by Lao, Zhiqiang, Shen, Dinggang, Liu, Dengfeng, Jawad, Abbas F, Melhem, Elias R, Launer, Lenore J, Bryan, R. Nick, Davatzikos, Christos

“…Rationale and Objectives Brain lesions, especially white matter lesions (WMLs), are associated with cardiac and vascular disease, but also with normal aging…”
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Science to practice: is t2 enough to assess oxygenation? by Bryan, R Nick

“…As initially reported by Ogawa et al (1), the magnetic resonance (MR) imaging T2* blood oxygen level–dependent (BOLD) signal is sensitive to blood oxygen…”
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