activity
20192022
most citedDetecting total hip replacement prosthesis design on preoperative radiographs using deep convolutional neural network

121 citations · 261 across the 7 of their papers we have counts for

collaborators

7 papers

eess.IV2022★ 15 cited

The use of deep learning enables high diagnostic accuracy in detecting syndesmotic instability on weight-bearing CT scanning

Alireza Borjali, Soheil Ashkani-Esfahani, Rohan Bhimani +5

Delayed diagnosis of syndesmosis instability can lead to significant morbidity and accelerated arthritic change in the ankle joint. Weight-bearing computed tomography (WBCT) has sh…

cs.CV2020★ 8 cited

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★ 6 cited

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★ 78 cited

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★ 23 cited

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.IV2019★ 10 cited

Detecting mechanical loosening of total hip replacement implant from plain radiograph using deep convolutional neural network

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

Plain radiography is widely used to detect mechanical loosening of total hip replacement (THR) implants. Currently, radiographs are assessed manually by medical professionals, whic…

eess.IV2019★ 121 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…