On Learning Cluster Coefficient of Private Networks

Por Wang, Yue, Wu, Xintao, Zhu, Jun, Xiang, Yang
Publicado em 2012

Deep Learning Classification of 3.5 GHz Band Spectrograms with Applications to Spectrum Sensing

Por Lees, W. Max, Wunderlich, Adam, Jeavons, Peter, Hale, Paul D., Souryal, Michael R.
Publicado no IEEE Trans Cogn Commun Netw (2019)

Trends in Medical Imaging During Pregnancy in the United States and Ontario, Canada, 1996 to 2016

Por Kwan, Marilyn L., Miglioretti, Diana L., Marlow, Emily C., Aiello Bowles, E. J., Weinmann, Sheila, Cheng, Stephanie Y., Deosaransingh, Kamala A., Chavan, Prachi, Moy, Lisa M., Bolch, Wesley E., Duncan, James R., Greenlee, Robert T., Kushi, Lawrence H., Pole, Jason D., Rahm, Alanna K., Stout, Natasha K., Smith-Bindman, R.
Publicado no JAMA Netw Open (2019)

Network Diffusion Approach to Predict LncRNA Disease Associations Using Multi-Type Biological Networks: LION

Por Marissa Sumathipala, Marissa Sumathipala, Enrico Maiorino, Scott T. Weiss, Scott T. Weiss, Amitabh Sharma, Amitabh Sharma, Amitabh Sharma
Publicado em 2019-07-01

Connectivity and complex systems: learning from a multi-disciplinary perspective

Por Turnbull, Laura, Hütt, Marc-Thorsten, Ioannides, Andreas A., Kininmonth, Stuart, Poeppl, Ronald, Tockner, Klement, Bracken, Louise J., Keesstra, Saskia, Liu, Lichan, Masselink, Rens, Parsons, Anthony J.
Publicado no Appl Netw Sci (2018)

Association of Estimated Long-term Exposure to Air Pollution and Traffic Proximity With a Marker for Coronary Atherosclerosis in a Nationwide Study in China

Por Wang, Meng, Hou, Zhi-Hui, Xu, Hao, Liu, Yang, Budoff, Matthew J., Szpiro, Adam A., Kaufman, Joel D., Vedal, Sverre, Lu, Bin
Publicado no JAMA Netw Open (2019)

Machine Learning–Based Prediction of Clinical Outcomes for Children During Emergency Department Triage

Por Goto, Tadahiro, Camargo, Carlos A., Faridi, Mohammad Kamal, Freishtat, Robert J., Hasegawa, Kohei
Publicado no JAMA Netw Open (2019)

Assessment of Follow-up Care After Emergency Department Presentation for Mild Traumatic Brain Injury and Concussion: Results From the TRACK-TBI Study

Por Seabury, Seth A., Gaudette, Étienne, Goldman, Dana P., Markowitz, Amy J., Brooks, Jordan, McCrea, Michael A., Okonkwo, David O., Manley, Geoffrey T., Adeoye, Opeolu, Badjatia, Neeraj, Boase, Kim, Bodien, Yelena, Bullock, M. Ross, Chesnut, Randall, Corrigan, John D., Crawford, Karen, Diaz-Arrastia, Ramon, Dikmen, Sureyya, Duhaime, Ann-Christine, Ellenbogen, Richard, Feeser, V. Ramana, Ferguson, Adam, Foreman, Brandon, Gardner, Raquel, Giacino, Joseph, Gonzalez, Luis, Gopinath, Shankar, Gullapalli, Rao, Hemphill, J. Claude, Hotz, Gillian, Jain, Sonia, Korley, Frederick, Kramer, Joel, Kreitzer, Natalie, Levin, Harvey, Lindsell, Chris, Machamer, Joan, Madden, Christopher, Martin, Alastair, McAllister, Thomas, Merchant, Randall, Mukherjee, Pratik, Nelson, Lindsay, Noel, Florence, Palacios, Eva, Perl, Daniel, Puccio, Ava, Rabinowitz, Miri, Robertson, Claudia, Rosand, Jonathan, Sander, Angelle, Satris, Gabriella, Schnyer, David, Sherer, Mark, Stein, Murray, Taylor, Sabrina, Temkin, Nancy, Toga, Arthur, Valadka, Alex, Vassar, Mary, Vespa, Paul, Wang, Kevin, Yue, John, Yuh, Esther, Zafonte, Ross
Publicado no JAMA Netw Open (2018)