title: Applications of Deep Learning in Biomedicine.
abstract: Increases in throughput and installed base of biomedical research equipment led to a massive accumulation of -omics data known to be highly variable, high-dimensional, and sourced from multiple often incompatible data platforms. While this data may be useful for biomarker identification and drug discovery, the bulk of it remains underutilized. Deep neural networks (DNNs) are efficient algorithms based on the use of compositional layers of neurons, with advantages well matched to the challenges -omics data presents. While achieving state-of-the-art results and even surpassing human accuracy in many challenging tasks, the adoption of deep learning in biomedicine has been comparatively slow. Here, we discuss key features of deep learning that may give this approach an edge over other machine learning methods. We then consider limitations and review a number of applications of deep learning in biomedical studies demonstrating proof of concept and practical utility.
authors.affiliation: Artificial Intelligence Research, Insilico Medicine, Inc, ETC, Johns Hopkins University , Baltimore, Maryland 21218, United States.
authors.forename: Polina
authors.initials: P
authors.lastname: Mamoshina
authors.affiliation: RedZebra Analytics , 1 Quality Court, London, WC2A 1HR, U.K.
authors.forename: Armando
authors.initials: A
authors.lastname: Vieira
authors.affiliation: Artificial Intelligence Research, Insilico Medicine, Inc, ETC, Johns Hopkins University , Baltimore, Maryland 21218, United States.
authors.forename: Evgeny
authors.initials: E
authors.lastname: Putin
authors.affiliation: Artificial Intelligence Research, Insilico Medicine, Inc, ETC, Johns Hopkins University , Baltimore, Maryland 21218, United States.
authors.forename: Alex
authors.initials: A
authors.lastname: Zhavoronkov
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D035843:Biomedical Research; D055808:Drug Discovery / Q000379:methods; D006801:Humans; D000069550:Machine Learning; D009415:Nerve Net / Q000378:metabolism / Q000502:physiology
chemical_list: D015415:Biomarkers
keywords: RBM; artificial intelligence; biomarker development; deep learning; deep neural networks; genomics; transcriptomics