Results 181 to 190 of about 177,947 (196)

Unleashing the Power of Machine Learning in Nanomedicine Formulation Development

Advanced Functional Materials, EarlyView.
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore, Cristiano Pesce, Antonietta Greco, Claudia Pisante, Greta Avancini, Valentina Di Francesco, Yosi Shamay, Paolo Decuzzi   +7 more
wiley   +1 more source

Effects of hip abducted position during eccentric-only resistance exercise on acute changes in passive stiffness of the biarticular hamstring muscles. [PDF]

PLoS One
Kawama R, Takahashi K, Nobukawa R, Wakahara T.   +3 more
europepmc   +1 more source

Gait Biomechanical Differences in the Anterior Cruciate Ligament Reconstructed and Contralateral Limb: A Systematic Review with Meta-Analysis. [PDF]

Healthcare (Basel)
Sajedi H, Aydın E, Güler MŞ, Akpınar S, Esmaeili A, Jafarnezhadgero A, Webster KE.   +6 more
europepmc   +1 more source

Polyethylene Stresses in Lumbar Total Joint Replacement Under Elevated Loading: Insights from an Anatomic Finite Element Model. [PDF]

Bioengineering (Basel)
Rundell SA, Spece H, Yarbrough RV, Kurtz SM.   +3 more
europepmc   +1 more source

The length of lateral radiographs significantly impacts the measurement of the femoral intramedullary axis in patients undergoing total knee arthroplasty. [PDF]

Arthroplasty
El Kayali MKD, Bürck LV, Fahy S, Pichler L.   +3 more
europepmc   +1 more source

Physiologic Medial Meniscal Extrusion With Loading and Flexion Detected by Ultrasound. [PDF]

Orthop J Sports Med
Dey Hazra ME, Dey Hazra RO, Kruse A, Bradshaw A, Hollenbeck J, Millett PJ, Vidal A, Tashman S, Watkins LE.   +8 more
europepmc   +1 more source