AI Medical Compendium Topic

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Electronics

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Instrumental Odour Monitoring System Classification Performance Optimization by Analysis of Different Pattern-Recognition and Feature Extraction Techniques.

Sensors (Basel, Switzerland)
Instrumental odour monitoring systems (IOMS) are intelligent electronic sensing tools for which the primary application is the generation of odour metrics that are indicators of odour as perceived by human observers. The quality of the odour sensor s...

Bio-inspired smart electronic-skin based on inorganic perovskite nanoplates for application in photomemories and mechanoreceptors.

Nanoscale
The development of artificial skin, such as electronic skin, is critical to emerging artificial intelligence systems. Electronic skins reported to date are mechanically flexible, and can detect various stimuli, but lack the ability to regulate themse...

Predicting the DNA Conductance Using a Deep Feedforward Neural Network Model.

Journal of chemical information and modeling
Double-stranded DNA (dsDNA) has been established as an efficient medium for charge migration, bringing it to the forefront of the field of molecular electronics and biological research. The charge migration rate is controlled by the electronic coupli...

Neuromorphic on-chip recognition of saliva samples of COPD and healthy controls using memristive devices.

Scientific reports
Chronic Obstructive Pulmonary Disease (COPD) is a life-threatening lung disease, affecting millions of people worldwide. Implementation of Machine Learning (ML) techniques is crucial for the effective management of COPD in home-care environments. How...

Printed, Wireless, Soft Bioelectronics and Deep Learning Algorithm for Smart Human-Machine Interfaces.

ACS applied materials & interfaces
Recent advances in flexible materials and wearable electronics offer a noninvasive, high-fidelity recording of biopotentials for portable healthcare, disease diagnosis, and machine interfaces. Current device-manufacturing methods, however, still heav...

Prediction of Energetic Material Properties from Electronic Structure Using 3D Convolutional Neural Networks.

Journal of chemical information and modeling
We develop a convolutional neural network capable of directly parsing the 3D electronic structure of a molecule described by spatial point data for charge density and electrostatic potential represented as a 4D tensor. This method effectively bypasse...

Reverse graph self-attention for target-directed atomic importance estimation.

Neural networks : the official journal of the International Neural Network Society
Estimating the importance of each atom in a molecule is one of the most appealing and challenging problems in chemistry, physics, and materials science. The most common way to estimate the atomic importance is to compute the electronic structure usin...

Emerging Memristive Artificial Synapses and Neurons for Energy-Efficient Neuromorphic Computing.

Advanced materials (Deerfield Beach, Fla.)
Memristors have recently attracted significant interest due to their applicability as promising building blocks of neuromorphic computing and electronic systems. The dynamic reconfiguration of memristors, which is based on the history of applied elec...

Machine learning-driven electronic identifications of single pathogenic bacteria.

Scientific reports
A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a poly...

Machine Learning Prediction of Electronic Coupling between the Guanine Bases of DNA.

The journal of physical chemistry. A
Charge transport in deoxyribonucleic acid (DNA) is of immense interest in biology and molecular electronics. Electronic coupling between the DNA bases is an important parameter describing the efficiency of charge transport in DNA. A reasonable estima...