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Posts by RAYLYTIC
bionection 2022: RAYLYTIC to speak on AI-based data management in medicine
On Friday, May 13, RAYLYTIC presented its AI-powered software solutions on home soil in Leipzig at the bionection 2022, a networking conference facilitating the exchange of technology between science and industry.
Dr. Peter Obid wins AO Spine 2021 Research Start-up Grant in cooperation with RAYLYTIC
With the goal of developing AI-driven analysis of coronal parameters in patients with adolescent idiopathic scoliosis, Dr. Peter Obid, together with RAYLYTIC, was awarded the AO Spine 2021 Research Start-up Grant.
RAYLYTIC & AIQNET partners present interoperable solutions at the DMEA 2022
At the DMEA 2022, RAYLYTIC and AIQNET partners showcased interoperable solutions for challenges facing the digital healthcare industry.
AIQNET: A Simplified Route to MDR Approval
The rapidly changing regulatory landscape in the EU demands compelling technological solutions.
AIQNET, initiated by RAYLYTIC, is aimed at producing a digital ecosystem that simplifies regulatory approval procedures by providing medical device manufacturers with access to ethically and legally collected, highly structured clinical data.
Artificial Intelligence: Whitecloud Award nomination for IMAST abstract
The abstract “Novel AI-based algorithm for automated cervical sagittal balance analysis validated on pre- and postoperative X-rays of 129 patients” submitted to this year’s International Meeting on Advanced Spine Techniques (IMAST) was accepted and is nominated for the Whitecloud Award. The work presents an AI-based algorithm for the automated assessment of cervical sagittal balance parameters, demonstrating excellent reliability and accuracy.
Abstract presenting algorithm for knee wear determination nominated for Wilhelm Roux Award
The abstract “Accurate Wear Determination in Clinical Radiographs after Total Knee Arthroplasty using 2D-3D Registration and Artificial Intelligence: An In Vivo Validation” submitted to this year’s German Congress of Orthopedic and Trauma Surgery (DKOU) was accepted and nominated for the Wilhelm Roux Award. The work presents an automated algorithm for the accurate and precise measurement of wear in total knee arthroplasty using clinical AP radiographs.