Publications
Lung-RADS version 1.1: Challenges and a look ahead, from the AJR special series on radiology reporting and data systems
Chelala, L,
Hossain, R,
Kazerooni, EA,
Christensen, JD,
Dyer, DS,
White, CS,
AJR Am J Roentgenol, 2021 Jun; DOI:10.2214/AJR.20.24807 Failure of Cardiovascular Phase 3 Randomized Clinical Trials to Report Pre-trial and Post-trial Parameters a Cross-sectional Analysis of ClinicalTrials.gov
Zheutlin, AR,
Niforatos, JD,
Stulberg, E,
Sussman, JB,
J Gen Intern Med, 2021 Jun; DOI:10.1007/s11606-020-05995-9 Deriving myocardial blood flow reserve from perfusion datasets: Dream or reality?
Poitrasson-Rivière, A,
Murthy, VL,
J Nucl Cardiol, 2021 Jun; DOI:10.1007/s12350-020-02488-4 A Bayesian dose-finding design for outcomes evaluated with uncertainty
Schipper, MJ,
Yuan, Y,
Taylor, JM,
Ten Haken, RK,
Tsien, C,
Lawrence, TS,
Clin Trials, 2021 Jun; DOI:10.1177/17407745211001521 Leveraging Health Information Technology to Collect Family Cancer History: A Systematic Review and Meta-Analysis
Li, X,
Kahn, RM,
Wing, N,
Zhou, ZN,
Lackner, AI,
Krinsky, H,
Badiner, N,
Fogla, R,
Wolfe, I,
Bergeron, H,
Baltich Nelson, B,
Thomas, C,
Christos, PJ,
Sharaf, RN,
Cantillo, E,
Holcomb, K,
Chapman-Davis, E,
Frey, MK,
JCO Clin Cancer Inform, 2021 Jun; DOI:10.1200/CCI.21.00004 Integrative web-based analysis of omics data for study of drugs against SARS-CoV-2
Wang, Z,
He, Y,
Huang, J,
Yang, X,
Sci Rep, 2021 May; DOI:10.1038/s41598-021-89578-6 Developing a Social Media Intervention to Connect Alaska Native People Who Smoke with Resources and Support to Quit Smoking: The Connecting Alaska Native Quit Study
Merculieff, ZT,
Koller, KR,
Sinicrope, PS,
Hughes, CA,
Bock, MJ,
Decker, PA,
Resnicow, K,
Flanagan, CA,
Meade, CD,
McConnell, CR,
Prochaska, JJ,
Thomas, TK,
Patten, CA,
Nicotine Tob Res, 2021 May; DOI:10.1093/ntr/ntaa253 Cross-species analysis defines the conservation of anatomically segregated VMH neuron populations
Affinati, AH,
Sabatini, PV,
True, C,
Tomlinson, AJ,
Kirigiti, M,
Lindsley, SR,
Li, C,
Olson, DP,
Kievit, P,
Myers, MG,
Rupp, AC,
Elife, 2021 May; DOI:10.7554/eLife.69065 MichiGAN: sampling from disentangled representations of single-cell data using generative adversarial networks
Yu, H,
Welch, JD,
Genome Biol, 2021 May; DOI:10.1186/s13059-021-02373-4 Machine Learning-Based Cytokine Microarray Digital Immunoassay Analysis
Song, Y,
Zhao, J,
Cai, T,
Stephens, A,
Su, S-H,
Sandford, E,
Flora, C,
Singer, BH,
Ghosh, M,
Choi, SW,
Tewari, M,
Kurabayashi, K,
Biosens Bioelectron, 2021 May; DOI:10.1016/j.bios.2021.113088 Whole-genome sequencing association analysis of quantitative red blood cell phenotypes: The NHLBI TOPMed program
Hu, Y,
Stilp, AM,
McHugh, CP,
Rao, S,
Jain, D,
Zheng, X,
Lane, J,
Méric de Bellefon, S,
Raffield, LM,
Chen, M-H,
Yanek, LR,
Wheeler, M,
Yao, Y,
Ren, C,
Broome, J,
Moon, J-Y,
de Vries, PS,
Hobbs, BD,
Sun, Q,
Surendran, P,
Am J Hum Genet, 2021 May; DOI:10.1016/j.ajhg.2021.04.003 Perceived utility and characterization of personal google search histories to detect data patterns proximal to a suicide attempt in individuals who previously attempted suicide: Pilot cohort study
Areán, PA,
Pratap, A,
Hsin, H,
Huppert, TK,
Hendricks, KE,
Heagerty, PJ,
Cohen, T,
Bagge, C,
Comtois, KA,
J Med Internet Res, 2021 May; DOI:10.2196/27918 Frequency and Duration of Advertising on Popular Child-Directed Channels on a Video-Sharing Platform
Yeo, SL,
Schaller, A,
Robb, MB,
Radesky, JS,
JAMA Netw Open, 2021 May; DOI:10.1001/jamanetworkopen.2021.9890 Development and Validation of a Deep Learning Model Using Convolutional Neural Networks to Identify Scaphoid Fractures in Radiographs
Yoon, AP,
Lee, Y-L,
Kane, RL,
Kuo, C-F,
Lin, C,
Chung, KC,
JAMA Netw Open, 2021 May; DOI:10.1001/jamanetworkopen.2021.6096 IsoResolve: Predicting splice isoform functions by integrating gene and isoform-level features with domain adaptation
Li, H-D,
Yang, C,
Zhang, Z,
Yang, M,
Wu, F-X,
Omenn, GS,
Wang, J,
Bioinformatics, 2021 May; DOI:10.1093/bioinformatics/btaa829 Does Specimen Type Have an Impact on HER2 Status in Endometrial Serous Carcinoma? Discordant HER2 Status of Paired Endometrial Biopsy and Hysterectomy Specimens in the Presence of Frequent Intratumoral Heterogeneity.
Rottmann, D,
Assem, H,
Matsumoto, N,
Wong, S,
Hui, P,
Buza, N,
Int J Gynecol Pathol, 2021 May; DOI:10.1097/PGP.0000000000000690 Following the Breadcrumbs of Palliative Care Financial Sustainability to Big Data
Kittelson, S,
Cassel, B,
Rodgers, P,
Macieira, T,
Salloum, RG,
Cogle, CR,
Yao, Y,
Shenkman, EA,
Wilkie, D,
J Palliat Med, 2021 May; DOI:10.1089/jpm.2021.0018 Response to Tang, et al.
Shah, ED,
Amann, ST,
Karlitz, JJ,
Am J Gastroenterol, 2021 May; DOI:10.14309/ajg.0000000000001070 Local Control After Stereotactic Body Radiation Therapy for Stage I Non-Small Cell Lung Cancer
Lee, P,
Loo, BW,
Biswas, T,
Ding, GX,
El Naqa, IM,
Jackson, A,
Kong, F-M,
LaCouture, T,
Miften, M,
Solberg, T,
Tome, WA,
Tai, A,
Yorke, E,
Li, XA,
Int J Radiat Oncol Biol Phys, 2021 May; DOI:10.1016/j.ijrobp.2019.03.045 Dermatologist Perceptions of Teledermatology Implementation and Future Use After COVID-19: Demographics, Barriers, and Insights
Kennedy, J,
Arey, S,
Hopkins, Z,
Tejasvi, T,
Farah, R,
Secrest, AM,
Lipoff, JB,
JAMA Dermatol, 2021 May; DOI:10.1001/jamadermatol.2021.0195 Ovarian-Adnexal Reporting Lexicon for MRI: A White Paper of the ACR Ovarian-Adnexal Reporting and Data Systems MRI Committee
Reinhold, C,
Rockall, A,
Sadowski, EA,
Siegelman, ES,
Maturen, KE,
Vargas, HA,
Forstner, R,
Glanc, P,
Andreotti, RF,
Thomassin-Naggara, I,
J Am Coll Radiol, 2021 May; DOI:10.1016/j.jacr.2020.12.022 The prevalence of self-reported medical comorbidities in patients with vulvar lichen sclerosus: A single-center retrospective study
Hu, J,
Hesson, A,
Haefner, HK,
Rominski, S,
Int J Gynaecol Obstet, 2021 May; DOI:10.1002/ijgo.13480 scHiCTools: A computational toolbox for analyzing single-cell Hi-C data
Li, X,
Feng, F,
Pu, H,
Leung, WY,
Liu, J,
PLoS Comput Biol, 2021 May; DOI:10.1371/journal.pcbi.1008978 #ILookLikeASurgeon: Or do I? The local and global impact of a hashtag.
Ansari, H,
Pitt, SC,
Am J Surg, 2021 May; DOI:10.1016/j.amjsurg.2020.10.020 Predicting future cognitive decline with hyperbolic stochastic coding
Zhang, J,
Dong, Q,
Shi, J,
Li, Q,
Stonnington, CM,
Gutman, BA,
Chen, K,
Reiman, EM,
Caselli, RJ,
Thompson, PM,
Ye, J,
Wang, Y,
Med Image Anal, 2021 May; DOI:10.1016/j.media.2021.102009 