Bulletin of the American Physical Society
APS March Meeting 2024
Monday–Friday, March 4–8, 2024; Minneapolis & Virtual
Session Z18: Data science, AI, and machine learning in physics II
11:30 AM–2:18 PM,
Friday, March 8, 2024
Room: M100I
Sponsoring
Units:
GDS GMED
Chair: Neha Goswami, University of Illinois Urbana-Champaign
Abstract: Z18.00005 : Radiomics assisted machine learning model for predication of prostate specific antigen levels*
12:18 PM–12:30 PM
Presenter:
Saad Bin Saeed Ahmed
(Florida Atlantic University)
Authors:
Saad Bin Saeed Ahmed
(Florida Atlantic University)
Agha Hammad Khan
(McGill University)
Wazir Muhammad
(Florida Atlantic University)
For this purpose, a data set consists of 100 localized prostate cancer patients treated with a combination of radiation therapy and Androgen Deprivation Therapy (ADT). Pretreatment imaging data including Magnetic Resonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET/CT), and Prostate Specific Antigen (PSMA) scans were used to extract the radiomic features with reference to follow-up PSA levels.
Patient's demographics, tumor stage, Gleason score, histopathology, radiation therapy dose, immunotherapy dose, pre and post treatment PSA levels along with significant radiomic features are used in training of machine learning model.
We expect this model will help clinicians in predicting early prognosis along with treatment intensification options (if required) for localized prostate cancer patients.
*This research conducted without any external funding
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