Towards computational solutions for precision medicine based big data healthcare system using deep learning models: A review

R Thirunavukarasu, R Gnanasambandan… - Computers in Biology …, 2022 - Elsevier
The emergence of large-scale human genome projects, advances in DNA sequencing
technologies, and the massive volume of electronic medical records [EMR] shift the …

Deep learning and big data in healthcare: a double review for critical beginners

L Bote-Curiel, S Munoz-Romero, A Gerrero-Curieses… - Applied Sciences, 2019 - mdpi.com
In the last few years, there has been a growing expectation created about the analysis of
large amounts of data often available in organizations, which has been both scrutinized by …

Medical image analysis based on deep learning approach

M Puttagunta, S Ravi - Multimedia tools and applications, 2021 - Springer
Medical imaging plays a significant role in different clinical applications such as medical
procedures used for early detection, monitoring, diagnosis, and treatment evaluation of …

[HTML][HTML] Facial expression recognition via ResNet-50

B Li, D Lima - International Journal of Cognitive Computing in …, 2021 - Elsevier
As one of the most important directions in the field of computer vision, facial emotion
recognition plays an important role in people's daily work and life. Human emotion …

Artificial intelligence image recognition method based on convolutional neural network algorithm

Y Tian - Ieee Access, 2020 - ieeexplore.ieee.org
As an algorithm with excellent performance, convolutional neural network has been widely
used in the field of image processing and achieved good results by relying on its own local …

A deep transfer convolutional neural network framework for EEG signal classification

G Xu, X Shen, S Chen, Y Zong, C Zhang, H Yue… - IEEE …, 2019 - ieeexplore.ieee.org
Nowadays, motor imagery (MI) electroencephalogram (EEG) signal classification has
become a hotspot in the research field of brain computer interface (BCI). More recently, deep …

A state‐of‐health estimation method considering capacity recovery of lithium batteries

Y Guo, P Yu, C Zhu, K Zhao, L Wang… - International Journal of …, 2022 - Wiley Online Library
At present, the rapid development of new energy sources makes lithium‐ion batteries (LIBs)
widely used, but LIBs will inevitably age during using. State of health (SOH) is a direct …

Hard-rock tunnel lithology prediction with TBM construction big data using a global-attention-mechanism-based LSTM network

Z Liu, L Li, X Fang, W Qi, J Shen, H Zhou… - Automation in …, 2021 - Elsevier
The TBM-constructed rock tunnel often suffers from low comparability of efficiency between
geological condition detection and the TBM real-time operation requirements. This article …

A novel deep learning method for intelligent fault diagnosis of rotating machinery based on improved CNN-SVM and multichannel data fusion

W Gong, H Chen, Z Zhang, M Zhang, R Wang, C Guan… - Sensors, 2019 - mdpi.com
Intelligent fault diagnosis methods based on deep learning becomes a research hotspot in
the fault diagnosis field. Automatically and accurately identifying the incipient micro-fault of …

Advanced deep learning approaches to predict supply chain risks under COVID-19 restrictions

MM Bassiouni, RK Chakrabortty, OK Hussain… - Expert Systems with …, 2023 - Elsevier
The ongoing COVID-19 pandemic has created an unprecedented predicament for global
supply chains (SCs). Shipments of essential and life-saving products, ranging from …