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  1. 1.   Machine learning-augmented molecular dynamics simulations (MD) reveal insights into the disconnect between affinity and activation of ZTP riboswitch ligands
  2. Fullenkamp, Christopher; Mehdi, Shams; Jones, Christopher; Tenney, Logan; Pichling, Patricio; Prestwood, Peri R; Ferré-D'Amaré, Adrian R; Tiwary, Pratyush; Schneekloth,John
  3. Angewandte Chemie (International ed. in English). 2025, May 01; e202505971.
  1. 2.   Artificial Intelligence and Infectious Disease Imaging
  2. Chu, Winston T; Reza, Syed M S; Anibal, James T; Landa, Adam; Crozier,Ian; Bagci, Ulas; Wood, Bradford J; Solomon, Jeffrey
  3. The Journal of Infectious Diseases. 2023, Oct 03; 228(Supplement_4): S322-S336.
  1. 3.   Artificial Immune Cell, AI-cell, a New Tool to Predict Interferon Production by Peripheral Blood Monocytes in Response to Nucleic Acid Nanoparticles
  2. Chandler, Morgan; Jain, Sankalp; Halman, Justin; Hong, Enping; Dobrovolskaia,Marina; Zakharov, Alexey V; Afonin, Kirill A
  3. Small (Weinheim an der Bergstrasse, Germany). 2022, Oct 10; e2204941.
  1. 4.   Exploring approaches for predictive cancer patient digital twins: Opportunities for collaboration and innovation
  2. Stahlberg,Eric; Abdel-Rahman, Mohamed; Aguilar, Boris; Asadpoure, Alireza; Beckman, Robert A; Borkon,Lynn; Bryan, Jeffrey N; Cebulla, Colleen M; Chang, Young Hwan; Chatterjee, Ansu; Deng, Jun; Dolatshahi, Sepideh; Gevaert, Olivier; Greenspan, Emily J; Hao, Wenrui; Hernandez-Boussard, Tina; Jackson, Pamela R; Kuijjer, Marieke; Lee, Adrian; Macklin, Paul; Madhavan, Subha; McCoy, Matthew D; Mohammad Mirzaei, Navid; Razzaghi, Talayeh; Rocha, Heber L; Shahriyari, Leili; Shmulevich, Ilya; Stover, Daniel G; Sun, Yi; Syeda-Mahmood, Tanveer; Wang, Jinhua; Wang, Qi; Zervantonakis, Ioannis
  3. Frontiers in Digital Health. 2022, Oct 6; 4: 1007784.
  1. 5.   Deep Learning Methods for Lung Cancer Segmentation in Whole-Slide Histopathology Images-The ACDC@LungHP Challenge 2019
  2. Li, Zhang; Zhang, Jiehua; Tan, Tao; Teng, Xichao; Sun, Xiaoliang; Zhao, Hong; Liu, Lihong; Xiao, Yang; Lee, Byungjae; Li, Yilong; Zhang, Qianni; Sun, Shujiao; Zheng, Yushan; Yan, Junyu; Li, Ni; Hong, Yiyu; Ko, Junsu; Jung,Hyun; Liu,Yanling; Chen, Yu-cheng; Wang, Ching-wei; Yurovskiy, Vladimir; Maevskikh, Pavel; Khanagha, Vahid; Jiang, Yi; Yu, Li; Liu, Zhihong; Li, Daiqiang; Schueffler, Peter J.; Yu, Qifeng; Chen, Hui; Tang, Yuling; Litjens, Geert
  3. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS. 2021, Feb; 25(2): 429-440.
  1. 6.   Data Augmentation and Transfer Learning to Improve Generalizability of an Automated Prostate Segmentation Model
  2. Sanford, Thomas H.; Zhang, Ling; Harmon,Stephanie; Sackett, Jonathan; Yang, Dong; Roth, Holger; Xu, Ziyue; Kesani, Deepak; Mehralivand, Sherif; Baroni, Ronaldo H.; Barrett, Tristan; Girometti, Rossano; Oto, Aytekin; Purysko, Andrei S.; Xu, Sheng; Pinto, Peter A.; Xu, Daguang; Wood, Bradford J.; Choyke, Peter L.; Turkbey, Baris
  3. AMERICAN JOURNAL OF ROENTGENOLOGY. 2020, DEC; 215(6): 1403-1410.
  1. 7.   Multicenter Multireader Evaluation of an Artificial Intelligence-Based Attention Mapping System for the Detection of Prostate Cancer With Multiparametric MRI
  2. Mehralivand, Sherif; Harmon,Stephanie; Shih, Joanna H; Smith, Clayton P; Lay, Nathan; Argun, Burak; Bednarova, Sandra; Baroni, Ronaldo Hueb; Canda, Abdullah Erdem; Ercan, Karabekir; Girometti, Rossano; Karaarslan, Ercan; Kural, Ali Riza; Pursyko, Andrei S; Rais-Bahrami, Soroush; Tonso, Victor Martins; Magi-Galluzzi, Cristina; Gordetsky, Jennifer B; Macarenco, Ricardo Silvestre E Silva; Merino, Maria J; Gumuskaya, Berrak; Saglican, Yesim; Sioletic, Stefano; Warren, Anne Y; Barrett, Tristan; Bittencourt, Leonardo; Coskun, Mehmet; Knauss, Chris; Law, Yan Mee; Malayeri, Ashkan A; Margolis, Daniel J; Marko, Jamie; Yakar, Derya; Wood, Bradford J; Pinto, Peter A; Choyke, Peter L; Summers, Ronald M; Turkbey, Baris
  3. AJR. American journal of roentgenology. 2020, OCT; 215(4): 903-912.
  1. 8.   Accelerating Therapeutics for Opportunities in Medicine: A Paradigm Shift in Drug Discovery
  2. Hinkson, Izumi V; Madej,Benjamin; Stahlberg,Eric
  3. Frontiers in pharmacology. 2020, Jun 30; 11: 770.
  1. 9.   Deep-Learning-Based Artificial Intelligence for PI-RADS Classification to Assist Multiparametric Prostate MRI Interpretation: A Development Study
  2. Sanford, Thomas; Harmon,Stephanie; Turkbey, Evrim B; Kesani, Deepak; Tuncer, Sena; Madariaga, Manuel; Yang, Chris; Sackett, Jonathan; Mehralivand, Sherif; Yan, Pingkun; Xu, Sheng; Wood, Bradford J; Merino, Maria J; Pinto, Peter A; Choyke, Peter L; Turkbey, Baris
  3. Journal of magnetic resonance imaging : JMRI. 2020, Jun 01;
  1. 10.   Society of Toxicologic Pathology Digital Pathology and Image Analysis Special Interest Group Article*: Opinion on the Application of Artificial Intelligence and Machine Learning to Digital Toxicologic Pathology
  2. Turner, Oliver C; Aeffner, Famke; Bangari, Dinesh S; High, Wanda; Knight, Brian; Forest, Tom; Cossic, Brieuc; Himmel, Lauren E; Rudmann, Daniel G; Bawa, Bhupinder; Muthuswamy, Anantharaman; Aina, Olulanu H; Edmondson,Elijah; Saravanan, Chandrassegar; Brown, Danielle L; Sing, Tobias; Sebastian, Manu M
  3. Toxicologic pathology. 2019, Oct 23; 192623319881401.
  1. 11.   AI Meets Exascale Computing: Advancing Cancer Research With Large-Scale High Performance Computing
  2. Bhattacharya, Tanmoy; Brettin, Thomas; Doroshow, James H.; Evrard,Yvonne; Greenspan, Emily J.; Gryshuk, Amy L.; Hoang, Thuc T.; Lauzon, Carolyn B. Vea; Nissley,Dwight; Penberthy, Lynne; Stahlberg,Eric; Stevens, Rick; Streitz, Fred; Tourassi, Georgia; Xia, Fangfang; Zaki,George
  3. Frontiers in oncology. 2019, Oct 2; 9
  1. 12.   Innovative Technologies for Advancement of WHO Risk Group 4 Pathogens Research
  2. Logue, James; Solomon,Jeffrey; Niemeyer, Brian F.; Benam, Kambez H.; Lin, Aaron E.; Bjornson, Zach; Jiang, Sizun; McIlwain, David R.; Nolan, Garry P.; Palacios, Gustavo; Kuhn, Jens H.
  3. 2019; 437-469.
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