Silva, Luiz H. da Silva, Alexandre K.
Published in
Journal of the Brazilian Society of Mechanical Sciences and Engineering
The present study verifies the possibility of analyzing pollutants in an open-channel stream using deep learning algorithms through image analysis. For that, external flow images with and without pollutant, which were obtained with a water table apparatus that is instrumented with a camera and syringes responsible for disposing dyes of different co...
Kristianingsih, Ruth MacLean, Dan
Published in
BMC Bioinformatics
BackgroundPlant pathogens cause billions of dollars of crop loss every year and are a major threat to global food security. Effector proteins are the tools such pathogens use to infect the cell, predicting effectors de novo from sequence is difficult because of the heterogeneity of the sequences. We hypothesised that deep learning classifiers based...
Zhang, Jianjing Gao, Robert X.
Published in
Chinese Journal of Mechanical Engineering
Characterized by self-monitoring and agile adaptation to fast changing dynamics in complex production environments, smart manufacturing as envisioned under Industry 4.0 aims to improve the throughput and reliability of production beyond the state-of-the-art. While the widespread application of deep learning (DL) has opened up new opportunities to a...
Poirion, Olivier B. Jing, Zheng Chaudhary, Kumardeep Huang, Sijia Garmire, Lana X.
Published in
Genome Medicine
Multi-omics data are good resources for prognosis and survival prediction; however, these are difficult to integrate computationally. We introduce DeepProg, a novel ensemble framework of deep-learning and machine-learning approaches that robustly predicts patient survival subtypes using multi-omics data. It identifies two optimal survival subtypes ...
Kabelac, Zachary Tarolli, Christopher G. Snyder, Christopher Feldman, Blake Glidden, Alistair Hsu, Chen-Yu Hristov, Rumen Dorsey, E. Ray Katabi, Dina
Published in
Digital Biomarkers
We conducted a pilot study using a passive radio-wave-based home monitor in individuals with Parkinson disease (PD) with a focus on gait, home activity, and time in bed. We enrolled 7 ambulatory individuals to have the device installed in the bedroom of their homes over 8 weeks and performed standard PD assessments at baseline. We evaluated the abi...
Guo, Kai Li, Xiongfei Hu, Xiaohan Liu, Jichen Fan, Tiehu
Published in
BMC Medical Imaging
BackgroundIn medical diagnosis of brain, the role of multi-modal medical image fusion is becoming more prominent. Among them, there is no lack of filtering layered fusion and newly emerging deep learning algorithms. The former has a fast fusion speed but the fusion image texture is blurred; the latter has a better fusion effect but requires higher ...
Sundaresan, Avirath Penchina, Brian Cheong, Sean Grace, Victoria Valero-Cabré, Antoni Martel, Adrien
Published in
Brain Informatics
Mental stress is a major individual and societal burden and one of the main contributing factors that lead to pathologies such as depression, anxiety disorders, heart attacks, and strokes. Given that anxiety disorders are one of the most common comorbidities in youth with autism spectrum disorder (ASD), this population is particularly vulnerable to...
Wang, Youdao Zhao, Yifan Addepalli, Sri
Published in
Chinese Journal of Mechanical Engineering
The remaining useful life (RUL) of a system is generally predicted by utilising the data collected from the sensors that continuously monitor different indicators. Recently, different deep learning (DL) techniques have been used for RUL prediction and achieved great success. Because the data is often time-sequential, recurrent neural network (RNN) ...
Sarker, Iqbal H.
Published in
SN Computer Science
The digital world has a wealth of data, such as internet of things (IoT) data, business data, health data, mobile data, urban data, security data, and many more, in the current age of the Fourth Industrial Revolution (Industry 4.0 or 4IR). Extracting knowledge or useful insights from these data can be used for smart decision-making in various appli...
Rill, Róbert-Adrian Faragó, Kinga Bettina
Published in
SN Computer Science
Autonomous driving technologies, including monocular vision-based approaches, are in the forefront of industrial and research communities, since they are expected to have a significant impact on economy and society. However, they have limitations in terms of crash avoidance because of the rarity of labeled data for collisions in everyday traffic, a...
