16 papers · ranked by Valyu relevance
Laith Alzubaidi, Jinglan Zhang, Amjad J. Humaidi, Ayad Al-Dujaili + 6 more
In the last few years, the deep learning (DL) computing paradigm has been deemed the Gold Standard in the machine learning (ML) community. Moreover, it has gradually become the most widely used computational approach in the field of ML, thus achieving outstanding results on several complex cognitive tasks, matching or…
Athanasios Voulodimos, Nikolaos Doulamis, Anastasios Doulamis, Eftychios Protopapadakis
'Eftychios Protopapadakis'] Over the last years deep learning methods have been shown to outperform previous state-of-the-art machine learning techniques in several fields, with computer vision being one of the most prominent cases. This review paper provides a brief overview of some of the most significant deep…
Travers Ching, Daniel S. Himmelstein, Brett K. Beaulieu-Jones, Alexandr A. Kalinin + 32 more
Deep learning describes a class of machine learning algorithms that are capable of combining raw inputs into layers of intermediate features. These algorithms have recently shown impressive results across a variety of domains. Biology and medicine are data-rich disciplines, but the data are complex and often…
Chensi Cao, Feng Liu, Hai Tan, Deshou Song + 5 more
'Weizhong Li' 'Yiming Zhou' 'Xiaochen Bo' 'Zhi Xie'] Advances in biological and medical technologies have been providing us explosive volumes of biological and physiological data, such as medical images, electroencephalography, genomic and protein sequences. Learning from these data facilitates the understanding of…
Frank Emmert-Streib, Zhen Yang, Han Feng, Shailesh Tripathi + 1 more
'Matthias Dehmer'] Deep learning models stand for a new learning paradigm in artificial intelligence (AI) and machine learning. Recent breakthrough results in image analysis and speech recognition have generated a massive interest in this field because also applications in many other domains providing big data seem…
Binhua Tang, Zixiang Pan, Kang Yin, Asif Khateeb
Extracting inherent valuable knowledge from omics big data remains as a daunting problem in bioinformatics and computational biology. Deep learning, as an emerging branch from machine learning, has exhibited unprecedented performance in quite a few applications from academia and industry. We highlight the difference…
Sijie Yang, Fei Zhu, Xinghong Ling, Quan Liu + 1 more
With the progress of medical technology, biomedical field ushered in the era of big data, based on which and driven by artificial intelligence technology, computational medicine has emerged. People need to extract the effective information contained in these big biomedical data to promote the development of precision…
Malik YOUSEF, Jens ALLMER
Deep learning is a powerful machine learning technique that can learn from large amounts of data using multiple layers of artificial neural networks. This paper reviews some applications of deep learning in bioinformatics, a field that deals with analyzing and interpreting biological data. We first introduce the basic…
Osval Antonio Montesinos‐López, Abelardo Montesinos‐López, Carlos Moises Hernandez‐Suarez, José Alberto Barrón‐López + 1 more
Deep learning (DL) is revolutionizing the development of artificial intelligence systems. For example, before 2015, humans were better than artificial machines at classifying images and solving many problems of computer vision (related to object localization and detection using images), but nowadays, artificial…
Evgeniy Bart, Jay Hegdé
Deep learning is a branch of machine learning in which statistical representations of the input data, as opposed to task-specific algorithms, are learned. Deep learning may be supervised, unsupervised, or semi-supervised (Lecun et al., ; Schmidhuber, ; Goodfellow et al., ). Deep learning techniques are behind many…
Lara Lloret Iglesias, Pablo Sanz Bellón, Amaia Pérez del Barrio, Pablo Menéndez Fernández-Miranda + 4 more
Deep learning is nowadays at the forefront of artificial intelligence. More precisely, the use of convolutional neural networks has drastically improved the learning capabilities of computer vision applications, being able to directly consider raw data without any prior feature extraction. Advanced methods in the…
HOSSEIN MORADIMOKHLES, GWO-JEN HWANG, HOSSEIN ZANGENEH, MARYAM POURJAMSHIDI + 1 more
The term “deep learning” has incorrect interpretations in education and technology disciplines. It describes a method of learning in which the objective is to achieve an in-depth understanding of topic rather than succumb to surface learning. "Non-surface learning" is undeniably related to deep information…
Ping Gong, Chaoyang Zhang, Minjun Chen
Deep learning (DL), alsocalled deep structured learning or hierarchical learning, is an important subset of machine learning (ML). The distinction between DL and conventional “shallow” ML is that DL algorithms allow computational models composed of multiple processing layers to be fed with raw data and automatically…
Tehreem Qamar, Narmeen Zakaria Bawany, Rong Qu
Deep learning (DL) has revolutionized the field of artificial intelligence by providing sophisticated models across a diverse range of applications, from image and speech recognition to natural language processing and autonomous driving. However, deep learning models are typically black-box models where the reason for…
Bradley J. Erickson, Panagiotis Korfiatis, Timothy L. Kline, Zeynettin Akkus + 2 more
'Zeynettin Akkus' 'Kenneth Philbrick' 'Alexander D. Weston'] Deep learning (DL) is a popular method that is used to perform many important tasks in radiology and medical imaging. Some forms of DL are able to accurately segment organs (essentially, trace the boundaries, enabling volume measurements or calculation of…
Fazle Rabbi, Sajjad Rahmani Dabbagh, Pelin Angin, Ali Kemal Yetisen + 2 more
'Savas Tasoglu' 'Shohei Yamamura'] Deep learning (DL) is a subfield of machine learning (ML), which has recently demonstrated its potency to significantly improve the quantification and classification workflows in biomedical and clinical applications. Among the end applications profoundly benefitting from DL, cellular…