| Machine learning approaches for predicting radiation therapy outcomes: a clinician's perspective J Kang, R Schwartz, J Flickinger, S Beriwal International Journal of Radiation Oncology* Biology* Physics 93 (5), 1127-1135, 2015 | 213 | 2015 |
| Machine learning and radiogenomics: lessons learned and future directions J Kang, T Rancati, S Lee, JH Oh, SL Kerns, JG Scott, R Schwartz, S Kim, ... Frontiers in oncology 8, 228, 2018 | 56 | 2018 |
| Response of an actin filament network model under cyclic stretching through a coarse grained Monte Carlo approach J Kang, RL Steward, YT Kim, RS Schwartz, PR LeDuc, KM Puskar Journal of theoretical biology 274 (1), 109-119, 2011 | 56 | 2011 |
| Cervical cancer outcome prediction to high-dose rate brachytherapy using quantitative magnetic resonance imaging analysis of tumor response to external beam radiotherapy D Minkoff, BS Gill, J Kang, S Beriwal Radiotherapy and Oncology 115 (1), 78-83, 2015 | 35 | 2015 |
| Ddc2 mediates Mec1 activation through a Ddc1-or Dpb11-independent mechanism A Bandhu, J Kang, K Fukunaga, G Goto, K Sugimoto PLoS genetics 10 (2), e1004136, 2014 | 33 | 2014 |
| Genomics models in radiotherapy: From mechanistic to machine learning J Kang, JT Coates, RL Strawderman, BS Rosenstein, SL Kerns Medical physics 47 (5), e203-e217, 2020 | 22* | 2020 |
| National cancer institute workshop on artificial intelligence in radiation oncology: training the next generation J Kang, RF Thompson, S Aneja, C Lehman, A Trister, J Zou, C Obcemea, ... Practical radiation oncology 11 (1), 74-83, 2021 | 19 | 2021 |
| Structurally governed cell mechanotransduction through multiscale modeling J Kang, KM Puskar, AJ Ehrlicher, PR LeDuc, RS Schwartz Scientific Reports 5 (1), 8622, 2015 | 15 | 2015 |
| Closing the Gap Between Machine Learning and Clinical Cancer Care—First Steps Into a Larger World J Kang, O Morin, JC Hong JAMA Oncology, 2020 | 10 | 2020 |
| Stereotactic body radiotherapy in patients with multiple lung tumors: a focus on lung dosimetric constraints MT Milano, A Mihai, J Kang, DP Singh, V Verma, H Qiu, Y Chen, FM Kong Expert review of anticancer therapy 19 (11), 959-969, 2019 | 8 | 2019 |
| Integrating artificial intelligence and machine learning into cancer clinical trials J Kang, AK Chowdhry, SL Pugh, JH Park Seminars in Radiation Oncology 33 (4), 386-394, 2023 | 7 | 2023 |
| In regard to Fornacon-Wood et al. AK Chowdhry, D Mayo, SL Pugh, J Park, CD Fuller, J Kang International Journal of Radiation Oncology, Biology, Physics 115 (1), 249-250, 2023 | 2 | 2023 |
| Fellowship Training in Radiation Oncology J Kang, RF Thompson, CD Fuller, KA Camphausen, PE Gabriel, ... INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS 106 (1), 217-218, 2020 | 2* | 2020 |
| Modeling mechanotransduction signaling through actin filament network deformation linked to biochemical response J Kang, KM Puskar, RS Schwartz, PR LeDuc Biophysical Journal 104 (2), 317a-318a, 2013 | 2 | 2013 |
| Machine Learning and Artificial Intelligence in Radiation Oncology: A Guide for Clinicians J Kang, T Rattay, BS Rosenstein Academic Press, 2023 | 1 | 2023 |
| Predicted Inferior Outcomes for Lung SBRT With Treatment Planning Systems That Fail Independent Phantom-Based Audits MD Greer, B Koger, M Glenn, J Kang, R Rengan, J Zeng, E Ford International Journal of Radiation Oncology* Biology* Physics 115 (5), 1301-1308, 2023 | 1 | 2023 |
| A glimmer of hope within the mountain of hype–Reviewing the role of artificial intelligence in radiotherapy R Jena, A Dekker, J Kang Clinical Oncology 34 (2), 71-73, 2022 | 1 | 2022 |
| Extracting knowledge of NCI research directions from funding data using language processing. P Beidler, M Nguyen, J Kang Journal of Clinical Oncology 39 (15_suppl), e13547-e13547, 2021 | 1 | 2021 |
| Comparing the Kattan Nomogram to a Random Forest Model to Predict Post-Prostatectomy Pathology J Kang, CW Doucette, I El Naqa, H Zhang International Journal of Radiation Oncology, Biology, Physics 102 (3), S61-S62, 2018 | 1 | 2018 |
| Long-term CT surveillance after primary lung cancer treatment captures events in all risk groups J Kang, AK Chowdhry, MT Milano Translational Lung Cancer Research 7 (Suppl 1), S49, 2018 | 1 | 2018 |
Russell SchwartzProfessor of Biological Sciences and Computational Biology, Carnegie Mellon UniversityVerified email at andrew.cmu.edu
