most citedDetecting total hip replacement prosthesis design on preoperative radiographs using deep convolutional neural network

121 citations · 121 across the 1 of their papers we have counts for

collaborators

5 papers

cs.CV2020

Improved Diagnosis of Tibiofemoral Cartilage Defects on MRI Images Using Deep Learning

Gergo Merkely, Alireza Borjali, Molly Zgoda +5

Background: MRI is the modality of choice for cartilage imaging; however, its diagnostic performance is variable and significantly lower than the gold standard diagnostic knee arth…

eess.SP2020

Is Machine Learning Able to Detect and Classify Failure in Piezoresistive Bone Cement Based on Electrical Signals?

Hamid Ghaednia, Crystal E. Owens, Lily E. Keiderling +4

At an estimated cost of $8 billion annually in the United States, revision surgeries to total joint replacements represent a substantial financial burden to the health care system.…

cs.CL2020

Natural Language Processing with Deep Learning for Medical Adverse Event Detection from Free-Text Medical Narratives: A Case Study of Detecting Total Hip Replacement Dislocation

Alireza Borjali, Martin Magneli, David Shin +3

Accurate and timely detection of medical adverse events (AEs) from free-text medical narratives is challenging. Natural language processing (NLP) with deep learning has already sho…

eess.SP2019

Interfacial Load Monitoring and Failure Detection in Total Joint Replacements via Piezoresistive Bone Cement and Electrical Impedance Tomography

Hamid Ghaednia, Crystal E. Owens, Ricardo Roberts +3

Aseptic loosening, or loss of implant fixation, is a common complication following total joint replacement. Revision surgeries cost the healthcare system over $8 billion annually i…

eess.IV2019121 cited

Detecting total hip replacement prosthesis design on preoperative radiographs using deep convolutional neural network

Alireza Borjali, Antonia F. Chen, Orhun K. Muratoglu +2

Identifying the design of a failed implant is a key step in preoperative planning of revision total joint arthroplasty. Manual identification of the implant design from radiographi…