Exactech Grows AI Expertise with Exclusive Machine-Learning Based Software Licensing Agreement and Team of Data Scientists
Expanded partnership with Advata will drive more powerful predictive artificial intelligence research and development applications for shoulder, hip, knee and ankle patients
March 27, 2023
GAINESVILLE, Fla.–(BUSINESS WIRE)–Exactech, a developer and producer of innovative implants, instrumentation, and smart technologies for joint replacement surgery, announced today it has exclusively licensed new software from Advata that will extend the capabilities of its innovative machine learning (ML)-based clinical decision support tool, Predict+®. This newly licensed software is a powerful addition to the company’s Active Intelligence® platform that will further facilitate Predict+ integration with the Equinoxe® Planning App and will also encourage integration with other software and databases.
Developed in partnership with Advata in 2019 and released in November 2020, Predict+ is a data-driven, clinical decision support tool and the first software of its kind to use ML to generate personalized risk-benefit analyses to help predict patient outcomes after shoulder replacement surgery.1-7 This software was designed to better inform surgeons regarding the expected outcomes that can be achieved after shoulder arthroplasty, based on the clinical experience documented within the world’s largest single-shoulder prosthesis outcomes database of more than 15,000 patients. These personalized predictions quantify the risk and benefit that an individual patient may experience after anatomic and reverse shoulder replacement.
“Advata is proud of the productive research and development collaboration with Exactech over the past several years. With the help of Advata’s exclusively licensed software for orthopaedic applications, Exactech now hosts Predict+ and can steward the continued development of this innovative ML-based product. This licensed software will encourage new innovations and improvements in usability of Predict+ and other future applications,” said Sudarshan Chitre, Advata’s Chief Technology Officer.
Additionally, Exactech is pleased to announce that it has hired an established team of machine learning researchers and engineers that will further accelerate Exactech’s ML research and development capabilities and improve its ability to produce additional innovative artificial intelligence-based software for various orthopaedic applications.
“Exactech is leading the orthopaedic industry in ML research and software applications.1-7 I am proud of Exactech’s vision to utilize enabling technologies with the goal of improving clinical outcomes and for making this investment to expand our in-house artificial intelligence capabilities,” said Chris Roche, Exactech’s Senior Vice President of Extremities. “This investment in new software and the hiring of this amazing machine learning team will serve as a catalyst for even more powerful and predictive artificial intelligence research and development applications for the Equinoxe shoulder, and also for other Exactech hip, knee and ankle products.”
“My team and I share Exactech’s vision that machine learning has the potential to transform healthcare decision making,” said Vikas Kumar, Exactech’s new Vice President of Machine Learning. “When paired with high quality healthcare data, novel ML applications will provide orthopaedic surgeons with valuable new data to help them make more informed, evidence-based decisions through which we aim to optimize clinical outcomes after arthroplasty. My team and I are proud of what we have developed with Exactech since 2019, and we are excited about what we will develop and deploy in the years to come at Exactech.”
Predict+ is built upon previously published, peer-reviewed research and is accessible through the Equinoxe Planning App preoperative planning software, which can be used with the ExactechGPS® navigation system in the operating room, connecting the preoperative plan with implant placement. Predict+ is available to surgeons globally on a limited basis. Please contact your Exactech representative for additional information and to explore all our Active Intelligence products.
Exactech is a global medical device company that develops and markets orthopaedic implant devices, related surgical instruments and the Active Intelligence® platform of smart technologies to hospitals and physicians. Headquartered in Gainesville, Fla., Exactech markets its products in the United States, in addition to more than 30 markets in Europe, Latin America, Asia and the Pacific. Visit http://www.exac.com for more information and connect with us on LinkedIn, VuMedi, YouTube, Twitter and Instagram.
Advata provides advanced data analytics software to improve decision-making and optimize administrative efficiencies in healthcare. Advata’s SaaS product offerings help healthcare providers capture more revenue and improve productivity by leveraging business intelligence, optimizing workflows, and reducing the time and cost to collect. The company’s solutions are powered by predictive analytics, actionable artificial intelligence (AI), machine learning (ML), and automation. To learn more, visit https://advata.com/.
- Kumar, V. et al. What Is the Accuracy of Three Different Machine Learning Techniques to Predict Clinical Outcomes After Shoulder Arthroplasty? Clin Orthop Relat Res. 2020 Oct;478(10):2351-2363.
- Kumar, V. et al. Using Machine Learning to Predict Clinical Outcomes After Shoulder Arthroplasty with a Minimal Feature Set. J Shoulder Elbow Surg. 2021 May;30(5):e225-e236.
- Kumar, V. et al. Use of Machine Learning to Assess the Predictive Value of 3 Commonly Used Clinical Measures to Quantify Outcomes After Total Shoulder Arthroplasty. Seminars in Arthroplasty: JSES. #31 (2): P.263-271. 2021.
- Roche, C. et al. Validation of a Machine Learning Derived Clinical Metric to Quantify Outcomes after TSA. J Shoulder Elbow Surg. 2021 Feb 16:S1058-2746(21)00101-4.
- Kumar, V. et al. Using Machine Learning to Predict Internal Rotation after Anatomic and Reverse Total Shoulder Arthroplasty. JSES. 2022 May;31(5):e234-e245.
- Kumar, V. et al. Development of a Predictive Model for a Machine Learning Derived Shoulder Arthroplasty Clinical Outcome Score. Seminars in Arthroplasty: JSES. #32 (2): P226-237. 2022.
- Simmons, C. et al. Surgeon Confidence in Planning Total Shoulder Arthroplasty Improves After Consulting Clinical Decision Support Tool. European Journal of Orthopaedic Surgery & Traumatology. 2022.
Sr. Director, Marketing Communications