Artificial Intelligence Medical Compendium

Explore the latest research on artificial intelligence and machine learning in medicine.

Showing 55,771 to 55,780 of 226,731 articles

A Sparse-Integrated Filtering Residual Spiking Neural Network for High-Accuracy Spike Sorting and Co-Optimization on Memristor Platforms.

IEEE transactions on biomedical circuits and systems Feb 1, 2026
Brain-computer interfaces rely on precise decoding of neural signals, where spike sorting is a critical step to extract individual neuronal activities from complex neural data. This work presents a spiking neural network (SNN) framework for efficient... read more 

Inferring tephritid fly pupal development stage using non-invasive near infrared imaging and machine learning classification.

Bulletin of entomological research Feb 1, 2026
Insect pupae change morphologically (e.g., pigmentation of eyes, wings, setae and legs) during the intrapuparial period. Knowledge on the physiological age of pupae and their emergence are important parameters for the control of agriculturally import... read more 

EVALUATING POSTERIOR VITREOUS DETACHMENT ANNOTATION CONSISTENCY ON OPTICAL COHERENCE TOMOGRAPHY SCANS IN PATIENTS WITH DISEASE OF THE VITREOMACULAR INTERFACE.

Retina (Philadelphia, Pa.) Feb 1, 2026
PURPOSE: To evaluate intergrader variability in posterior vitreous detachment (PVD) classification in patients with epiretinal membrane and macular hole on spectral-domain optical coherence tomography (SD-OCT) and identify challenges in defining a re... read more 

Adaptive Batch Size Time Evolving Stochastic Gradient Descent for Federated Learning.

IEEE transactions on pattern analysis and machine intelligence Feb 1, 2026
Variance reduction has been shown to improve the performance of Stochastic Gradient Descent (SGD) in centralized machine learning. However, when it is extended to federated learning systems, many issues may arise, including (i) mega-batch size settin... read more 

An Energy-Efficient ECG Classifier With On-Chip Learning Using Binarized Convolutional Neural Network.

IEEE transactions on biomedical circuits and systems Feb 1, 2026
In ECG classification applications, binarized convolutional neural networks (bCNNs) show great potential to achieve extremely low power consumption through 1-bit quantization. Existing bCNN approaches typically extract spatial features from the full ... read more 

M3C: Resist Agnostic Attacks by Mitigating Consistent Class Confusion Prior.

IEEE transactions on pattern analysis and machine intelligence Feb 1, 2026
Adversarial attack is a major obstacle to the deployment of deep neural networks (DNNs) for security-sensitive applications. To address these adversarial perturbations, various adversarial defense strategies have been developed, with Adversarial Trai... read more 

Specific Emitter Identification by Edge Pattern Detection and Incremental Open-World Learning.

IEEE transactions on pattern analysis and machine intelligence Feb 1, 2026
Specific emitter identification (SEI) refers to the technique of identifying different individuals from the signals emitted by wireless devices. Recent studies have focused mainly on deep learning (DL) models that automatically learn valid inherent f... read more 

A 192-Channel 1D CNN-Based Neural Feature Extractor in 65nm CMOS for Brain-Machine Interfaces.

IEEE transactions on biomedical circuits and systems Feb 1, 2026
We present a 192-channel 1D convolutional neural network (1D CNN) based neural feature extractor for Brain-Machine Interfaces (BMI) that achieves state-of-the-art decoding stability at $\mathbf{1.8\ \mu W}$ and 12801 $\mathbf{\mu m^{2}}$ per channel ... read more 

AI-Driven Smart Sportswear for Real-Time Fitness Monitoring Using Textile Strain Sensors.

IEEE transactions on bio-medical engineering Feb 1, 2026
Wearable biosensors have revolutionized human performance monitoring by enabling real-time assessment of physiological and biomechanical parameters. However, existing solutions lack the ability to simultaneously capture breath-force coordination and ... read more 

Sparse Optoacoustic Sensing With Convolutional Dictionary Learning.

IEEE transactions on bio-medical engineering Feb 1, 2026
OBJECTIVE: Sparse optoacoustic sensing (SOS) enhances tomographic imaging by enabling high frame rates and reducing system complexity through partial data acquisition. However, its performance depends on advanced algorithms that compensate for under-... read more 
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