AIMC Topic: Neural Networks, Computer

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Finger Vein Recognition Based on Unsupervised Spiking Convolutional Neural Network with Adaptive Firing Threshold.

Sensors (Basel, Switzerland)
Currently, finger vein recognition (FVR) stands as a pioneering biometric technology, with convolutional neural networks (CNNs) and Transformers, among other advanced deep neural networks (DNNs), consistently pushing the boundaries of recognition acc...

Early prediction of neoadjuvant therapy response in breast cancer using MRI-based neural networks: data from the ACRIN 6698 trial and a prospective Chinese cohort.

Breast cancer research : BCR
BACKGROUND: Early prediction of treatment response to neoadjuvant therapy (NAT) in breast cancer patients can facilitate timely adjustment of treatment regimens. We aimed to develop and validate a MRI-based enhanced self-attention network (MESN) for ...

CausalCervixNet: convolutional neural networks with causal insight (CICNN) in cervical cancer cell classification-leveraging deep learning models for enhanced diagnostic accuracy.

BMC cancer
Cervical cancer is a significant global health issue affecting women worldwide, necessitating prompt detection and effective management. According to the World Health Organization (WHO), approximately 660,000 new cases of cervical cancer and 350,000 ...

An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion.

Scientific reports
Classical approaches to diagnosis frequently rely on self-reported symptoms or clinician observations, which can make it difficult to examine mental health illnesses due to their subjective and complicated nature. In this work, we offer an innovative...

Machine learning models to predict osteoporosis in patients with chronic kidney disease stage 3-5 and end-stage kidney disease.

Scientific reports
Chronic kidney disease-mineral bone disorder is a common complication in patients with chronic kidney disease (CKD) and end-stage kidney disease (ESKD), and it increases the risk of osteoporosis and fractures. This study aimed to develop predictive m...

CodonTransformer: a multispecies codon optimizer using context-aware neural networks.

Nature communications
Degeneracy in the genetic code allows many possible DNA sequences to encode the same protein. Optimizing codon usage within a sequence to meet organism-specific preferences faces combinatorial explosion. Nevertheless, natural sequences optimized thro...

GCN-BBB: Deep Learning Blood-Brain Barrier (BBB) Permeability PharmacoAnalytics with Graph Convolutional Neural (GCN) Network.

The AAPS journal
The Blood-Brain Barrier (BBB) is a selective barrier between the Central Nervous System (CNS) and the peripheral system, regulating the distribution of molecules. BBB permeability has been crucial in CNS-targeting drug development, such as glioblasto...

LGFormer: integrating local and global representations for EEG decoding.

Journal of neural engineering
Electroencephalography (EEG) decoding is challenging because of its temporal variability and low signal-to-noise ratio, which complicate the extraction of meaningful information from signals. Although convolutional neural networks (CNNs) effectively ...

Statistical analysis and prediction via neural networks of water quality in the Middle Paraíba do Sul (Rio de Janeiro State, Brazil) region in the period (2012-2022).

Environmental science and pollution research international
The aim of this study is to accurately predict the water quality at these points over a decade through the combined use of statistical tools and artificial intelligence. This study brings the innovative use of neural networks implemented with the GRN...

An Energy-Efficient Configurable 1-D CNN-Based Multi-Lead ECG Classification Coprocessor for Wearable Cardiac Monitoring Devices.

IEEE transactions on biomedical circuits and systems
Many electrocardiogram (ECG) processors have been widely used for cardiac monitoring. However, most of them have relatively low energy efficiency, and lack configurability in classification leads number and inference algorithm models. A multi-lead EC...