Machine Learning in Nano-Scale Biomedical Engineering

Machine learning (ML) empowers biomedical systems with the capability to optimize their performance through modeling of available data extremely well, without using strong assumptions about modeled system. Especially in nano-scale biosystems, where generated sets are too vast and complex mentally parse computational assist, ML is instrumental analyzing extracting new insights, accelerating material structure discoveries designing experience as well supporting communications networks. However, despite these efforts, use engineering remains still under-explored certain areas research challenges open fields such design simulations, signal processing, bio-medicine applications. In this article, we review existing regarding engineering. more detail, first identify discuss main that can be formulated problems. These classified three categories: simulation, processing biomedicine Next, state art methodologies used countermeasure aforementioned challenges. For each presented methodologies, special emphasis given its principles, applications limitations. Finally, conclude article insightful discussions, reveal gaps highlight possible future directions.