AIMC Topic: Neural Networks, Computer

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Using Advanced Convolutional Neural Network Approaches to Reveal Patient Age, Gender, and Weight Based on Tongue Images.

BioMed research international
The human tongue has been long believed to be a window to provide important insights into a patient's health in medicine. The present study introduced a novel approach to predict patient age, gender, and weight inferences based on tongue images using...

Uncertainty quantification in neural-network based pain intensity estimation.

PloS one
Improper pain management leads to severe physical or mental consequences, including suffering, a negative impact on quality of life, and an increased risk of opioid dependency. Assessing the presence and severity of pain is imperative to prevent such...

Improving human activity classification based on micro-doppler signatures of FMCW radar with the effect of noise.

PloS one
Nowadays, classifying human activities is applied in many essential fields, such as healthcare, security monitoring, and search and rescue missions. Radar sensor-based human activity classification is regarded as a superior approach in comparison to ...

Brain MRI detection and classification: Harnessing convolutional neural networks and multi-level thresholding.

PloS one
Brain tumor detection in clinical applications is a complex and challenging task due to the intricate structures of the human brain. Magnetic Resonance (MR) imaging is widely preferred for this purpose because of its ability to provide detailed image...

A Hybrid GNN Approach for Improved Molecular Property Prediction.

Journal of computational biology : a journal of computational molecular cell biology
The development of new drugs is a vital effort that has the potential to improve human health, well-being and life expectancy. Molecular property prediction is a crucial step in drug discovery, as it helps to identify potential therapeutic compounds....

Adversarial EM for variational deep learning: Application to semi-supervised image quality enhancement in low-dose PET and low-dose CT.

Medical image analysis
In positron emission tomography (PET) and X-ray computed tomography (CT), reducing radiation dose can cause significant degradation in image quality. For image quality enhancement in low-dose PET and CT, we propose a novel theoretical adversarial and...

A two-stream decision fusion network for cervical pap-smear image classification tasks.

Tissue & cell
Deep learning, especially Convolution Neural Networks (CNNs), has demonstrated superior performance in image recognition and classification tasks. They make complex pattern recognition possible by extracting image features through layers of abstracti...

Partial coherence enhances parallelized photonic computing.

Nature
Advancements in optical coherence control have unlocked many cutting-edge applications, including long-haul communication, light detection and ranging (LiDAR) and optical coherence tomography. Prevailing wisdom suggests that using more coherent light...

Neural waves and computation in a neural net model II: Data-like structures and the dynamics of episodic memory.

Journal of computational neuroscience
The computational resources of a neuromorphic network model introduced earlier were investigated in the first paper of this series. It was argued that a form of ubiquitous spontaneous local convolution enabled logical gate-like neural motifs to form ...

Label-Free Surface-Enhanced Raman Spectroscopy with Machine Learning for the Diagnosis of Thyroid Cancer by Using Fine-Needle Aspiration Liquid Samples.

Biosensors
The incidence of thyroid cancer is increasing worldwide. Fine-needle aspiration (FNA) cytology is widely applied with the use of extracted biological cell samples, but current FNA cytology is labor-intensive, time-consuming, and can lead to the risk ...