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An adaptive threshold neuron for recurrent spiking neural networks with nanodevice hardware implementation.

Nature communications
We propose a Double EXponential Adaptive Threshold (DEXAT) neuron model that improves the performance of neuromorphic Recurrent Spiking Neural Networks (RSNNs) by providing faster convergence, higher accuracy and a flexible long short-term memory. We...

A human-computer collaboration for COVID-19 differentiation: combining a radiomics model with deep learning and human auditing.

Annals of palliative medicine
BACKGROUND: This study aimed to build a radiomics model with deep learning (DL) and human auditing and examine its diagnostic value in differentiating between coronavirus disease 2019 (COVID-19) and community-acquired pneumonia (CAP).

Evaluation of Open-Source and Pre-Trained Deep Convolutional Neural Networks Suitable for Player Detection and Motion Analysis in Squash.

Sensors (Basel, Switzerland)
In sport science, athlete tracking and motion analysis are essential for monitoring and optimizing training programs, with the goal of increasing success in competition and preventing injury. At present, contact-free, camera-based, multi-athlete dete...

A Low-Power Spiking Neural Network Chip Based on a Compact LIF Neuron and Binary Exponential Charge Injector Synapse Circuits.

Sensors (Basel, Switzerland)
To realize a large-scale Spiking Neural Network (SNN) on hardware for mobile applications, area and power optimized electronic circuit design is critical. In this work, an area and power optimized hardware implementation of a large-scale SNN for real...

Schizophrenia: A Survey of Artificial Intelligence Techniques Applied to Detection and Classification.

International journal of environmental research and public health
Artificial Intelligence in healthcare employs machine learning algorithms to emulate human cognition in the analysis of complicated or large sets of data. Specifically, artificial intelligence taps on the ability of computer algorithms and software w...

A hybrid quantum-classical neural network with deep residual learning.

Neural networks : the official journal of the International Neural Network Society
Inspired by the success of classical neural networks, there has been tremendous effort to develop classical effective neural networks into quantum concept. In this paper, a novel hybrid quantum-classical neural network with deep residual learning (Re...

DeepFrag: An Open-Source Browser App for Deep-Learning Lead Optimization.

Journal of chemical information and modeling
Lead optimization, a critical step in early stage drug discovery, involves making chemical modifications to a small-molecule ligand to improve properties such as binding affinity. We recently developed DeepFrag, a deep-learning model capable of recom...

Dual energy CT image prediction on primary tumor of lung cancer for nodal metastasis using deep learning.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Lymph node metastasis (LNM) identification is the most clinically important tasks related to survival and recurrence from lung cancer. However, the preoperative prediction of nodal metastasis remains a challenge to determine surgical plans and pretre...