Search Results - "Teo, P Troy"

GlioPredictor: a deep learning model for identification of high-risk adult IDH-mutant glioma towards adjuvant treatment planning by Zheng, Shuhua, Rammohan, Nikhil, Sita, Timothy, Teo, P. Troy, Wu, Yilin, Lesniak, Maciej, Sachdev, Sean, Thomas, Tarita O.

“…Identification of isocitrate dehydrogenase ( IDH )-mutant glioma patients at high risk of early progression is critical for radiotherapy treatment planning…”
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Evaluating a potential technique with local optical flow vectors for automatic organ-at-risk (OAR) intrusion detection and avoidance during radiotherapy by Troy Teo, P, Guo, Kaiming, Ahmed, Bilal, Alayoubi, Nadia, Kehler, Katherine, Fontaine, Gabrielle, Sasaki, David, Pistorius, Stephen

“…Various techniques of deep inspiration breath hold (DIBH) have been used to mitigate the likelihood and risk of exposing the heart, an organ-at-risk (OAR) for…”
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Reducing the tracking drift of an uncontoured tumor for a portal-image-based dynamically adapted conformal radiotherapy treatment by Teo, P. Troy, Guo, Kaiming, Fontaine, Gabriel, Ahmed, Bilal, Alayoubi, Nadia, Kehler, Katherine, Sasaki, David, Pistorius, Stephen

“…Accurate tracking of organ motion during treatment is needed to improve the efficacy of radiation therapy. This work investigates the feasibility of tracking…”
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Application of TG‐100 risk analysis methods to the acceptance testing and commissioning process of a Halcyon linear accelerator by Teo, P. Troy, Hwang, Min‐Sig, Shields, William (Gary), Kosterin, Pavel, Jang, Si Young, Heron, Dwight E., Lalonde, Ronald J., Huq, M. Saiful

“…Purpose A new type of linear accelerator (linac) was recently introduced into the market by a major manufacturer. Our institution is one of the early users of…”
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Determining risk and predictors of head and neck cancer treatment-related lymphedema: A clinicopathologic and dosimetric data mining approach using interpretable machine learning and ensemble feature selection by Teo, P. Troy, Rogacki, Kevin, Gopalakrishnan, Mahesh, Das, Indra J, Abazeed, Mohamed E, Mittal, Bharat B, Gentile, Michelle

“…•External & internal lymphedema prediction for entire HN & oropharyngeal cohorts.•Pioneering inclusion of dosimetric predictors offers holistic lymphedema…”
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Deterministic small‐scale undulations of image‐based risk predictions from the deep learning of lung tumors in motion by Teo, P. Troy, Bajaj, Amishi, Randall, James, Lou, Bin, Shah, Jainil, Gopalakrishnan, Mahesh, Kamen, Ali, Abazeed, Mohamed E.

“…Introduction Deep learning (DL) models that use medical images to predict clinical outcomes are poised for clinical translation. For tumors that reside in…”
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Feasibility of predicting tumor motion using online data acquired during treatment and a generalized neural network optimized with offline patient tumor trajectories by Teo, Troy P., Ahmed, Syed Bilal, Kawalec, Philip, Alayoubi, Nadia, Bruce, Neil, Lyn, Ethan, Pistorius, Stephen

“…Purpose The accurate prediction of intrafraction lung tumor motion is required to compensate for system latency in image‐guided adaptive radiotherapy systems…”
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A dosimetric evaluation of the IAEA‐AAPM TRS483 code of practice for dosimetry of small static fields used in conventional linac beams and comparison with IAEA TRS‐398, AAPM TG51, and TG51 Addendum protocols by Huq, M. Saiful, Hwang, Min‐Sig, Teo, Troy P., Jang, Si Young, Heron, Dwight E., Lalonde, Ronald J.

“…Purpose The International Atomic Energy Agency (IAEA) and the American Association of Physicists in Medicine (AAPM) have jointly published a new code of…”
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Quality of Large Language Model Responses to Radiation Oncology Patient Care Questions by Yalamanchili, Amulya, Sengupta, Bishwambhar, Song, Joshua, Lim, Sara, Thomas, Tarita O, Mittal, Bharat B, Abazeed, Mohamed E, Teo, P Troy

“…Artificial intelligence (AI) large language models (LLMs) demonstrate potential in simulating human-like dialogue. Their efficacy in accurate patient-clinician…”
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Clinical, Pathologic, and Dosimetric Predictors of Head and Neck Lymphedema Following Definitive or Adjuvant Radiation Therapy for Head and Neck Cancer by Rogacki, Kevin R., Teo, P. Troy, Gopalakrishnan, Mahesh, Pachigolla, Suvidya Lakshmi, Lyons, Clayton E., Abazeed, Mohamed E., Das, Indra, Mittal, Bharat B., Gentile, Michelle

“…Head and neck lymphedema (HNL) following radiation therapy for head and neck cancer (HNC) causes patient morbidity. Predicting individual patients’ risk of HNL…”
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Image-Based Deep Neural Network for Individualizing Radiotherapy Dose Is Transportable Across Health Systems by Randall, James, Teo, P Troy, Lou, Bin, Shah, Jainil, Patel, Jyoti, Kamen, Ali, Abazeed, Mohamed E

“…We developed a deep neural network that queries the lung computed tomography-derived feature space to identify radiation sensitivity parameters that can…”
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A dosimetric evaluation of the IAEA ‐ AAPM TRS 483 code of practice for dosimetry of small static fields used in conventional linac beams and comparison with IAEA TRS ‐398, AAPM TG 51, and TG 51 Addendum protocols by Huq, M. Saiful, Hwang, Min‐Sig, Teo, Troy P., Jang, Si Young, Heron, Dwight E., Lalonde, Ronald J.

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