Natural language processing for automated quantification of bone metastases reported in free-text bone scintigraphy reports
Background The widespread use of electronic patient-generated health data has led to
unprecedented opportunities for automated extraction of clinical features from free-text …
unprecedented opportunities for automated extraction of clinical features from free-text …
Worldwide epidemiology of foot and ankle injuries during military training: a systematic review
BP Fenn, J Song, J Casey, GR Waryasz… - BMJ Mil …, 2021 - militaryhealth.bmj.com
Introduction Musculoskeletal foot and ankle injuries are commonly experienced by soldiers
during military training. We performed a systematic review to assess epidemiological …
during military training. We performed a systematic review to assess epidemiological …
[PDF][PDF] Does the SORG machine-learning algorithm for extremity metastases generalize to a contemporary cohort of patients? Temporal validation from 2016 to 2020
Background The ability to predict survival accurately in patients with osseous metastatic
disease of the extremities is vital for patient counseling and guiding surgical intervention …
disease of the extremities is vital for patient counseling and guiding surgical intervention …
Survival in Patients With Spinal Metastatic Disease Treated Nonoperatively With Radiotherapy: Are the SORG-ML Algorithms Relevant?
BP Fenn, AV Karhade, OQ Groot, AK Collins… - Clinical Spine …, 2024 - journals.lww.com
Objective: To externally validate the SORG-ML algorithms for survival in spinal metastatic
disease in patients managed nonoperatively with radiation. Study Design: Retrospective …
disease in patients managed nonoperatively with radiation. Study Design: Retrospective …