Ali Ajdari

Publication

PUBLISHED JOURNAL ARTICLES

  1. Ajdari, A, Niyazi, M., Nicolay, N et al (2019). Towards optimal stopping in radiation therapy. Radiotherapy and Oncology, May 2019, vol. 134, 96–100.

  2. Ajdari, A, Saberian, F, Ghate, A. (2018). A theoretical framework for learning tumor dose-response uncertainty in individualized spatiobiologically integrated radiotherapy, INFORMS Journal on Computing (accepted for publication).

  3. Ajdari, A, Ghate, A, Kim, M. (2018). Adaptive treatment-length optimization in spatiobiologically integrated radiotherapy, Physics in Medicine & Biology 63(7):075009.

  4. Ajdari, A, Boyle, L.N., Kannan, N et al. (2017). Simulation of the Emergency Department Care Process for Pediatric Traumatic Brain Injury. Journal for Healthcare Quality 40(2):110-118.

  5. Ajdari, A, Boyle, L.N., Kannan, N et al. (2017). Examining Emergency Department Treatment Processes in Severe Pediatric Traumatic Brain Injury. Journal for Healthcare Quality 39(6):334-344.

  6. Ajdari, A., Ghate, A. (2016). Robust spatiotemporally integrated fractionation in radiotherapy. Operations Research Letter. 44(4): 544-549.

  7. Ajdari, A., Mahlooji, H. (2014). An adaptive exploration-exploitation algorithm for constructing metamodels in random simulation using a novel sequential experimental design. Communication in Statistics: Simulation and Computations. 43(5): 943-968.

SUBMITTED MANUSCRIPTS

  1. Eikelder, SCM, Ajdari, A, Bortfeld, T, den Hertog, D. (2019). Adjustable robust treatment-length optimization in radiation therapy. INFORMS Journal on Computing.

  2. Hall, D, McNamara, A, Shusharina, N, Liu, A, Wei, X, Ajdari, A, Mohan, R, Liao, Z, Paganetti, H. (2019). Perspectives on the model-based approach to proton therapy trials: a retrospective study of a lung cancer trial. Radiation Therapy and Oncology (under 2nd revision).

WORKING MANUSCRIPTS

  1. Mid-treatment adaptation of radiation treatment using [18]F-FDG PET radiobiological imaging (with T. Bortfeld, R. Mohan, and Z. Liao).

  2. A hybrid Random Forest-Bayesian Network predictive model of chemo-radiation toxicity in non-small cell lung cancer (with T. Bortfeld and D. Craft).

  3. A distributed Bayesian Network model for multi-outcome modeling of liver metastasis radiotherapy (with Y. Xie, C. Richter, T. Hong, D. Duda, and T. Bortfeld).

  4. Adaptive treatment planning using mid-treatment [18]-FLT PET imaging in head-and-neck cancer (with S. Eikelder, D. Hertog, R. Jeraj, P. Ferjancic, and T. Bortfeld).

PUBLISHED CONFERENCE PREECEDINGS

  1. Ajdari, A, Shusharina N, Liao, Z, Mohan, R, Bortfeld, T. A novel machine learning-Bayesian network model for prediction of radiation pneumonitis: Importance of mid-treatment information. International Conference on the Use of Computers in Radiation Therapy. Montreal, Canada, June 17-21, 2019.

  2. Ajdari, A. Ghate, A. (2016). A model predictive control approach for discovering nonstationary fluence-maps in radiotherapy, Winter Simulation Conference, Washington D.C. 2065-2075.

INVITED TALKS

  1. OCTOBER 2019 | 2019 INFORMS Annual Conference | Seattle, WA

  2. SEPTEMBER 2019 | 2019 ASTRO Annual Conference | Chicago, IL

  3. JULY 2019 | 2019 INFORMS Healthcare Conference | MIT, Cambridge, MA

  4. JULY 2019 | 2019 AAPM Annual Conference | San Antonio, TX

  5. JUNE 2019 | 2019 ICCR Conference | Montreal, Canada

  6. NOVEMBER 2018 | 2018 INFORMS Annual Meeting | Phoenix, AZ

  7. NOVEMBER 2017 | 2017 Pediatric Trauma Society Annual Meeting | Charleston, SC

  8. NOVEMBER 2016 | 2016 INFORMS Annual Meeting | Houston, TX

  9. DECEMBER 2016 | 2016 Winter Simulation Conference | Washington, D.C.

  10. NOVEMBER 2015 | 2015 INFORMS Annual Meeting | Philadelphia, PA

  11. AUGUST 2015 | 2015 ISMP Annual Conference | Pittsburgh, PA

UNPUBLISHED MANUSCRIPTS

  1. Ajdari, A, Ghate, A. (2016). Robust spatiobiologically separated fractionation (Chapter 1 in doctoral thesis). Download from here.