@article{59d09fe6a72840b38cfd6bd5d48dd0d9,
title = "Machine learning for next-generation nanotechnology in healthcare",
abstract = "Nanotechnology for healthcare is coming of age, but automating the design of composite materials poses unique challenges. Although machine learning is supporting groundbreaking discoveries in materials science, new initiatives leveraging learned patterns are required to fully realize the promise of nanodelivery systems and accelerate development pipelines.",
author = "Andzelika Lorenc and Mendes, {B{\'a}rbara B.} and Jo{\~a}o Conniot and Sousa, {Diana P.} and Jo{\~a}o Conde and Tiago Rodrigues",
note = "Funding: The authors acknowledge financial support from FCT Portugal in the framework of PhD grant 2020.06638.BD (to D.P.S.), and the European Research Council grant agreement 848325 (J. Conde for the ERC Starting Grant). T.R. is an Investigador Auxiliar supported by FCT Portugal (CEECIND/ 00684/2018).",
year = "2021",
month = oct,
day = "1",
doi = "10.1016/j.matt.2021.09.014",
language = "English",
volume = "4",
pages = "3078--3080",
journal = "Matter",
issn = "2590-2385",
publisher = "Cell Press",
number = "10",
}