Novel Treatment Based on Acceptance and Commitment Therapy Versus Cognitive Behavioral Therapy for Insomnia: A Randomized Comparative Effectiveness Trial in Women Veterans von Martin, Jennifer L., Carlson, Gwendolyn C., Kelly, Monica R., Song, Yeonsu, Mitchell, Michael N., Josephson, Karen R., McGowan, Sarah Kate, Culver, Najwa C., Kay, Morgan A., Erickson, Alexander J., Saldana, Katie S., May, Kimiko J., Fiorentino, Lavinia, Alessi, Cathy A., Washington, Donna L., Yano, Elizabeth M.

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The effectiveness of cognitive behavioral therapy for insomnia on sleep outcomes in the context of pain among older adult veterans von Erickson, Alexander J., Rodriguez, Juan Carlos, Ravyts, Scott G., Dzierzewski, Joseph M., Fung, Constance H., Kelly, Monica R., Ryden, Armand M., Carlson, Gwendolyn C., Josephson, Karen, Mitchell, Michael N., Martin, Jennifer L., Alessi, Cathy A.

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Pain in your day? Get sleep treatment anyway! The role of pain in insomnia treatment efficacy in women veterans von Erickson, Alexander J., Ravyts, Scott G., Dzierzewski, Joseph M., Carlson, Gwendolyn C., Kelly, Monica R., Song, Yeonsu, McGowan, Sarah Kate, Mitchell, Michael N., Washington, Donna L., Yano, Elizabeth M., Alessi, Cathy A., Martin, Jennifer L.

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A non-inferiority randomized controlled trial comparing behavioral sleep interventions in women veterans: An examination of pain outcomes von Ravyts, Scott G, Erickson, Alexander J, Washington, Donna L, Yano, Elizabeth M, Carlson, Gwendolyn C, Mitchell, Michael N, Kelly, Monica, Alessi, Cathy A, McGowan, Sarah Kate, Song, Yeonsu, Martin, Jennifer L, Dzierzewski, Joseph M

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Toy aircraft von ERICKSON ADAM G, ERICKSON RANDALL T, ERICKSON ALEXANDER J

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Automated Abdominal Segmentation of CT Scans for Body Composition Analysis Using Deep Learning von Weston, Alexander D, Korfiatis, Panagiotis, Kline, Timothy L, Philbrick, Kenneth A, Kostandy, Petro, Sakinis, Tomas, Sugimoto, Motokazu, Takahashi, Naoki, Erickson, Bradley J

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The RSNA Pediatric Bone Age Machine Learning Challenge von Halabi, Safwan S, Prevedello, Luciano M, Kalpathy-Cramer, Jayashree, Mamonov, Artem B, Bilbily, Alexander, Cicero, Mark, Pan, Ian, Pereira, Lucas Araújo, Sousa, Rafael Teixeira, Abdala, Nitamar, Kitamura, Felipe Campos, Thodberg, Hans H, Chen, Leon, Shih, George, Andriole, Katherine, Kohli, Marc D, Erickson, Bradley J, Flanders, Adam E

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A Survey of Deep-Learning Applications in Ultrasound: Artificial Intelligence–Powered Ultrasound for Improving Clinical Workflow von Akkus, Zeynettin, Cai, Jason, Boonrod, Arunnit, Zeinoddini, Atefeh, Weston, Alexander D., Philbrick, Kenneth A., Erickson, Bradley J.

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Congophilic Fibrillary Glomerulonephritis: A Case Series von Alexander, Mariam P., Dasari, Surendra, Vrana, Julie A., Riopel, Julie, Valeri, Anthony M., Markowitz, Glen S., Hever, Aviv, Bijol, Vanesa, Larsen, Christopher P., Cornell, Lynn D., Fidler, Mary E., Said, Samar M., Sethi, Sanjeev, Herrera Hernandez, Loren Paola, Grande, Joseph P., Erickson, Stephen B., Fervenza, Fernando C., Leung, Nelson, Kurtin, Paul J., Nasr, Samih H.

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Traffic, transport, and vegetation drive VOC concentrations in a major urban area in Texas von Shrestha, Sujan, Yoon, Subin, Erickson, Matthew H., Guo, Fangzhou, Mehra, Manisha, Bui, Alexander A.T., Schulze, Benjamin C., Kotsakis, Alexander, Daube, Conner, Herndon, Scott C., Yacovitch, Tara I., Alvarez, Sergio, Flynn, James H., Griffin, Robert J., Cobb, George P., Usenko, Sascha, Sheesley, Rebecca J.

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What Does Deep Learning See? Insights From a Classifier Trained to Predict Contrast Enhancement Phase From CT Images von Philbrick, Kenneth A, Yoshida, Kotaro, Inoue, Dai, Akkus, Zeynettin, Kline, Timothy L, Weston, Alexander D, Korfiatis, Panagiotis, Takahashi, Naoki, Erickson, Bradley J

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Sedentary behavior and lifespan brain health von Zou, Liye, Herold, Fabian, Cheval, Boris, Wheeler, Michael J., Pindus, Dominika M., Erickson, Kirk I., Raichlen, David A., Alexander, Gene E., Müller, Notger G., Dunstan, David W., Kramer, Arthur F., Hillman, Charles H., Hallgren, Mats, Ekelund, Ulf, Maltagliati, Silvio, Owen, Neville

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A Deep Learning Tool for Automated Radiographic Measurement of Acetabular Component Inclination and Version After Total Hip Arthroplasty von Rouzrokh, Pouria, Wyles, Cody C., Philbrick, Kenneth A., Ramazanian, Taghi, Weston, Alexander D., Cai, Jason C., Taunton, Michael J., Lewallen, David G., Berry, Daniel J., Erickson, Bradley J., Maradit Kremers, Hilal

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Microstructural constraints on the mechanisms of the transformation to reidite in naturally shocked zircon von Erickson, Timmons M., Pearce, Mark A., Reddy, Steven M., Timms, Nicholas E., Cavosie, Aaron J., Bourdet, Julien, Rickard, William D. A., Nemchin, Alexander A.

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Electric Field Modulation of Semiconductor Quantum Dot Photoluminescence: Insights Into the Design of Robust Voltage-Sensitive Cellular Imaging Probes von Rowland, Clare E, Susumu, Kimihiro, Stewart, Michael H, Oh, Eunkeu, Mäkinen, Antti J, O’Shaughnessy, Thomas J, Kushto, Gary, Wolak, Mason A, Erickson, Jeffrey S, L. Efros, Alexander, Huston, Alan L, Delehanty, James B

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Suppressing quantum errors by scaling a surface code logical qubit von Acharya, Rajeev, Aleiner, Igor, Allen, Richard, Andersen, Trond I., Ansmann, Markus, Arute, Frank, Arya, Kunal, Asfaw, Abraham, Atalaya, Juan, Babbush, Ryan, Bacon, Dave, Bardin, Joseph C., Basso, Joao, Bengtsson, Andreas, Boixo, Sergio, Bortoli, Gina, Bourassa, Alexandre, Bovaird, Jenna, Brill, Leon, Broughton, Michael, Buckley, Bob B., Buell, David A., Burger, Tim, Burkett, Brian, Bushnell, Nicholas, Chen, Yu, Chen, Zijun, Chiaro, Ben, Cogan, Josh, Collins, Roberto, Conner, Paul, Courtney, William, Crook, Alexander L., Curtin, Ben, Debroy, Dripto M., Del Toro Barba, Alexander, Demura, Sean, Dunsworth, Andrew, Eppens, Daniel, Erickson, Catherine, Faoro, Lara, Farhi, Edward, Fatemi, Reza, Flores Burgos, Leslie, Forati, Ebrahim, Fowler, Austin G., Foxen, Brooks, Giang, William, Gidney, Craig, Gilboa, Dar, Giustina, Marissa, Grajales Dau, Alejandro, Gross, Jonathan A., Habegger, Steve, Hamilton, Michael C., Harrigan, Matthew P., Harrington, Sean D., Higgott, Oscar, Hilton, Jeremy, Hoffmann, Markus, Hong, Sabrina, Huang, Trent, Huff, Ashley, Huggins, William J., Ioffe, Lev B., Isakov, Sergei V., Iveland, Justin, Jeffrey, Evan, Jiang, Zhang, Jones, Cody, Juhas, Pavol, Kafri, Dvir, Kechedzhi, Kostyantyn, Kelly, Julian, Khattar, Tanuj, Khezri, Mostafa, Kieferová, Mária, Kim, Seon, Kitaev, Alexei, Klimov, Paul V., Klots, Andrey R., Korotkov, Alexander N., Kostritsa, Fedor, Kreikebaum, John Mark, Landhuis, David, Laptev, Pavel, Lau, Kim-Ming, Laws, Lily, Lee, Joonho, Lee, Kenny, Lester, Brian J., Lill, Alexander, Liu, Wayne, Locharla, Aditya, Lucero, Erik, Malone, Fionn D., Marshall, Jeffrey, Martin, Orion, McClean, Jarrod R., McCourt, Trevor

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Deep Learning in Radiology: Does One Size Fit All? von Erickson, Bradley J., Korfiatis, Panagiotis, Kline, Timothy L., Akkus, Zeynettin, Philbrick, Kenneth, Weston, Alexander D.

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Roadmap on emerging hardware and technology for machine learning von Berggren, Karl, Xia, Qiangfei, Likharev, Konstantin K, Strukov, Dmitri B, Jiang, Hao, Mikolajick, Thomas, Querlioz, Damien, Salinga, Martin, Erickson, John R, Pi, Shuang, Xiong, Feng, Lin, Peng, Li, Can, Chen, Yu, Xiong, Shisheng, Hoskins, Brian D, Daniels, Matthew W, Madhavan, Advait, Liddle, James A, McClelland, Jabez J, Yang, Yuchao, Rupp, Jennifer, Nonnenmann, Stephen S, Cheng, Kwang-Ting, Gong, Nanbo, Lastras-Montaño, Miguel Angel, Talin, A Alec, Salleo, Alberto, Shastri, Bhavin J, de Lima, Thomas Ferreira, Prucnal, Paul, Tait, Alexander N, Shen, Yichen, Meng, Huaiyu, Roques-Carmes, Charles, Cheng, Zengguang, Bhaskaran, Harish, Jariwala, Deep, Wang, Han, Shainline, Jeffrey M, Segall, Kenneth, Yang, J Joshua, Roy, Kaushik, Datta, Suman, Raychowdhury, Arijit

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Automated segmentation of endometrial cancer on MR images using deep learning von Hodneland, Erlend, Dybvik, Julie A., Wagner-Larsen, Kari S., Šoltészová, Veronika, Munthe-Kaas, Antonella Z., Fasmer, Kristine E., Krakstad, Camilla, Lundervold, Arvid, Lundervold, Alexander S., Salvesen, Øyvind, Erickson, Bradley J., Haldorsen, Ingfrid

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Generative Adversarial Networks to Synthesize Missing T1 and FLAIR MRI Sequences for Use in a Multisequence Brain Tumor Segmentation Model von Conte, Gian Marco, Weston, Alexander D., Vogelsang, David C., Philbrick, Kenneth A., Cai, Jason C., Barbera, Maurizio, Sanvito, Francesco, Lachance, Daniel H., Jenkins, Robert B., Tobin, W. Oliver, Eckel-Passow, Jeanette E., Erickson, Bradley J.

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