Welcome to the OrthoJOE podcast with Dr. Marc Swiontkowski and Dr. Mohit Bhandari. In this episode of OrthoJOE, Marc and Mo explore both the challenges and opportunities that have risen from the new abundance of online information and what this means for our pursuit of evidence-based medicine in surgery.
If you have any comments, questions, or topics you would like us to cover, please feel free to reach out so we can read your messages and possibly answer your questions during the next episode of OrthoJOE. You can contact us through our respective websites (MyOrthoEvidence and JBJS). We intend on having a mailbag portion of the show where we answer questions posed by our listeners.
- Traditional textbooks and journal articles in digital form look and operate similar to the printed version
- Application of machine learning to scientific research and clinical practice
- Future scientific paper: computational notebooks creating opportunity for a "living journal”
- Point-of-care, data-driven tools of the future
- OrthoEvidence, (February 19, 2021- No 42) OrthoEvidence. The Digital Enterprise: Redefining How Data is Changing Surgery. OE Insight. 2021;2(2):3. Available from: https://myorthoevidence.com/Download/9a6a3a4e-405f-4e40-8970-9ffa1f77480b
- JBJS, Vaid S, Cakan C, Bhandari M. Using Machine Learning to Estimate Unobserved COVID-19 Infections in North America. J Bone Joint Surg Am. 2020 Jul 1;102(13):e70. doi: 10.2106/JBJS.20.00715. PMID: 32618918; PMCID: PMC7396213. https://pubmed.ncbi.nlm.nih.gov/32618918/
Machine Learning Consortium, on behalf of the SPRINT and FLOW Investigators. A Machine Learning Algorithm to Identify Patients with Tibial Shaft Fractures at Risk for Infection After Operative Treatment. J Bone Joint Surg Am. 2020 Dec 29;Publish Ahead of Print. doi: 10.2106/JBJS.20.00903. Epub ahead of print. PMID: 33394819. https://pubmed.ncbi.nlm.nih.gov/33394819/