The role of artificial neural network and machine learning in utilizing spatial information
In this age of the fourth industrial revolution 4.0, the digital world has a plethora of data,
including the internet of things, mobile, cybersecurity, social media, forecasts, health data …
including the internet of things, mobile, cybersecurity, social media, forecasts, health data …
Neural networks for computer-aided diagnosis in medicine: a review
This survey makes an overview of the most recent applications on the neural networks for
the computer-aided medical diagnosis (CAMD) over the past decade. CAMD can facilitate …
the computer-aided medical diagnosis (CAMD) over the past decade. CAMD can facilitate …
Lung cancer diagnosis and staging using firefly algorithm fuzzy C-means segmentation and support vector machine classification of lung nodules
Lung nodule segmentation is an important division of automated disease screening systems
in cancer identification. The morphological variations of lung nodules correspond to chances …
in cancer identification. The morphological variations of lung nodules correspond to chances …
Feedforward backpropagation artificial neural networks for predicting mechanical responses in complex nonlinear structures: A study on a long bone
Feedforward backpropagation artificial neural networks (ANNs) have been increasingly
employed in many engineering practices concerning materials modeling. Despite their …
employed in many engineering practices concerning materials modeling. Despite their …
Highly accurate recognition of human postures and activities through classification with rejection
Monitoring of postures and activities is used in many clinical and research applications,
some of which may require highly reliable posture and activity recognition with desired …
some of which may require highly reliable posture and activity recognition with desired …
Formal design methods for reliable computer-aided diagnosis: a review
Physiological signals, medical images, and biosystems can be used to access the health of
a subject and they can support clinicians by improving the diagnosis for treatment purposes …
a subject and they can support clinicians by improving the diagnosis for treatment purposes …
EEG signals analysis using multiscale entropy for depth of anesthesia monitoring during surgery through artificial neural networks
In order to build a reliable index to monitor the depth of anesthesia (DOA), many algorithms
have been proposed in recent years, one of which is sample entropy (SampEn), a commonly …
have been proposed in recent years, one of which is sample entropy (SampEn), a commonly …
Energy absorption prediction for lattice structure based on D2 shape distribution and machine learning
Y Wu, Z Mao, Y Feng - Composite Structures, 2023 - Elsevier
Although lattice structure (LS) has the advantages of light weight, energy absorption, and
high specific strength, exhibiting different mechanical properties with different structural …
high specific strength, exhibiting different mechanical properties with different structural …
Qualitative predictions of bone growth over optimally designed macro-textured implant surfaces obtained using NN-GA based machine learning framework
The surface features on implant surface can improve biologic fixation of the implant with the
host bone leading to improved secondary (biological) implant stability. Application of finite …
host bone leading to improved secondary (biological) implant stability. Application of finite …
Joint angle estimation with wavelet neural networks
This paper presents a wavelet neural network (WNN) based method to reduce reliance on
wearable kinematic sensors in gait analysis. Wearable kinematic sensors hinder real-time …
wearable kinematic sensors in gait analysis. Wearable kinematic sensors hinder real-time …