Results 281 to 290 of about 1,127,640 (351)
Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
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 +7 more
wiley +1 more source
European Code Against Cancer, 5th edition - diet, excess body weight, physical activity, sedentary behavior, breastfeeding, and cancer. [PDF]
Leitzmann MF +19 more
europepmc +1 more source
The combination of formamidinium thiocyanate and 1,3‐propane diammonium iodide for bulk and top‐surface passivation, and a ternary fullerene blend to improve energy band alignment, suppresses energy losses in wide‐bandgap FAPbBr3 perovskite solar cells.
Laura Bellini +9 more
wiley +1 more source
European Code Against Cancer, 5th edition - a tool for enhancing cancer prevention. [PDF]
Schüz J +3 more
europepmc +1 more source
Europe's Ecological Debt: Mapping Freshwater Restoration Needs. [PDF]
Duarte G +9 more
europepmc +1 more source
Mapping Slovenia's global health engagement: alignment with European Union and national global health strategies. [PDF]
Kelhar SS +5 more
europepmc +1 more source
<i>Listeria monocytogenes</i> in Ready-to-Eat Foods: Risk Perspectives Across Different Regulatory Systems. [PDF]
D'Ambrosio G, Schirone M, Paparella A.
europepmc +1 more source
Digital medicine's international race for regulatory sandboxes and voluntary alternative pathways picks up tempo. [PDF]
Gilbert S.
europepmc +1 more source

