This page shows the publications co-authored by Thomas Cha and Aditya Karhade.
Development of prediction models for clinically meaningful improvement in PROMIS scores after lumbar decompression. Spine J. 2021 03; 21(3):397-404.
Surgeon-level variance in achieving clinical improvement after lumbar decompression: the importance of adequate risk adjustment. Spine J. 2021 03; 21(3):405-410.
Development of machine learning and natural language processing algorithms for preoperative prediction and automated identification of intraoperative vascular injury in anterior lumbar spine surgery. Spine J. 2021 10; 21(10):1635-1642.
Can natural language processing provide accurate, automated reporting of wound infection requiring reoperation after lumbar discectomy? Spine J. 2020 10; 20(10):1602-1609.
Predicting prolonged opioid prescriptions in opioid-naïve lumbar spine surgery patients. Spine J. 2020 06; 20(6):888-895.
Natural language processing for automated detection of incidental durotomy. Spine J. 2020 05; 20(5):695-700.
Discharge Disposition After Anterior Cervical Discectomy and Fusion. World Neurosurg. 2019 Dec; 132:e14-e20.
Development of machine learning algorithms for prediction of prolonged opioid prescription after surgery for lumbar disc herniation. Spine J. 2019 11; 19(11):1764-1771.
Machine learning for prediction of sustained opioid prescription after anterior cervical discectomy and fusion. Spine J. 2019 06; 19(6):976-983.
Development of machine learning algorithms for prediction of discharge disposition after elective inpatient surgery for lumbar degenerative disc disorders. Neurosurg Focus. 2018 11 01; 45(5):E6.
Development of a machine learning algorithm predicting discharge placement after surgery for spondylolisthesis. Eur Spine J. 2019 Aug; 28(8):1775-1782.
The connection strength for co-authors is the sum of the scores for each of their shared publications.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.