Loftus, T. J., Shickel, B., Balch, J. A., Tighe, P. J., Abbott, K. L., Fazzone, B., Anderson, E. M., Rozowsky, J., Ozrazgat-Baslanti, T., Ren, Y., Berceli, S. A., Hogan, W. R., Efron, P. A., Moorman, J. R., Rashidi, P., Upchurch, G. R., & Bihorac, A. (2022). Phenotype clustering in health care: A narrative review for clinicians. Frontiers in Artificial Intelligence, 5.  https://www.frontiersin.org/articles/10.3389/frai.2022.842306 Key takeaways Human pathophysiology is highly complex and often requires flexible analytic methods

Araujo, C. G., e Silva, C. G. D. S., Laukkanen, J. A., Singh, M. F., Kunutsor, S. K., Myers, J., … & Castro, C. L. (2022). Successful 10-second one-legged stance performance predicts survival in middle-aged and older individuals. British Journal of Sports Medicine. https://doi.org/10.1136/bjsports-2021-105360 Key takeaways: The ability to complete a 10-second one-legged stance (10-s OLS) is related to a higher risk of all cause-mortality and a shorter life expectancy. The ability to complete a 10-s

Ramkumar PN, Luu BC, Haeberle HS, Karnuta JM, Nwachukwu BU, Williams RJ. Sports Medicine and Artificial Intelligence: A Primer. The American Journal of Sports Medicine. 2022;50(4):1166-1174. https://doi.org/10.1177/03635465211008648 Key takeaways: AI has revolutionized the technology sector and is poised to transform sports medicine.  This technology should be viewed as an aid to augment a clinician’s capabilities rather than replace their responsibilities. It is important that sports medicine specialists not consider this area of research (AI/ML) outside

Bird MB, Mi Q, Koltun KJ, Lovalekar M, Martin BJ, Fain A, Bannister A, Vera Cruz A, Doyle TLA and Nindl BC (2022) Unsupervised Clustering Techniques Identify Movement Strategies in the Countermovement Jump Associated with Musculoskeletal Injury Risk During US Marine Corps Officer Candidates School. Front. Physiol. 13:868002. https://doi.org/10.3389/fphys.2022.868002 Key takeaways: Countermovement jump data can be used to predict risk of musculoskeletal injuries in military trainees More efficient CMJ movement strategies, characterized by greater kinetics

Turner, J.; Wagner, T.; Langhals, B. Biomechanical and Psychological Predictors of Failure in the Air Force Physical Fitness Test. Sports 2022, 10, 54. https://doi.org/10.3390/sports10040054 Key takeaways A combination of biomechanical and psychosocial factors can be used to predict the result of Air Force Physical Fitness Tests in active-duty airmen with a high degree of accuracy Airmen who reported poor sleep quality, a recent injury resulting in physical restriction, or low fitness satisfaction and those with

Because of the high costs and burden of injuries, even small reductions in injury rates can be extremely valuable. Knowledge of which individuals in a group are most at risk can enable targeted injury rate reduction efforts. Though we can’t predict specific injury events without supernatural foresight—who will be injured and when— for a given population of people and period of time, some people are predictably more likely to be injured than others. Rapidly expanding

Hewett TE, Olsen G, Atkinson M. The Use of Big Data to Improve Human Health: How Experience From other Industries Will Shape the Future. IJSPT. 2021;16(6):1590-1594. doi:10.26603/001c.29858   Click here to read the accompanying editorial by Tim Hewett and Kate Webster Introduction ‘Data science’ represents a set of mathematical and software development related techniques that are applied across a wide range of problems and industries. Practitioners of data science in human health-related domains typically see a world

Pontillo, M, Hines SM, & Sennett, BJ. (2021). Prediction of ACL Injuries from Vertical Jump Kinetics in Division 1 Collegiate Athletes. The International Journal of Sports Physical Therapy, 16(1), 156-161, DOI: 10.26603/001c.18819. Key takeaways:   EXPLODE is significantly lower in the ACL Injury group when compared to the Healthy group. DRIVE is significantly higher in the ACL Injury group when compared to the Healthy group. The LOAD to EXPLODE ratio is significantly higher in the ACL Injury group (meaning

Mayberry, JK, Patterson, B, and Wagner, P. Improving vertical jump profiles through prescribed movement plans. The Journal of Strength & Conditioning Research, 32(6), 1619-1626. KEY TAKEAWAYS Changes to Scan Jump Variables (LOAD, EXPLODE, and DRIVE) were highly correlated with different strength movement assignments and appear to be consistent across genders, sports, and level of competitiveness. Split Squats and Split Squats and 1-Leg Deadlift were found to significantly increase DRIVE and decrease LOAD and EXPLODE. Deadlift