AIMC Topic: Neural Networks, Computer

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Explainability of CNN-based Alzheimer's disease detection from online handwriting.

Scientific reports
With over 55 million people globally affected by dementia and nearly 10 million new cases reported annually, Alzheimer's disease is a prevalent and challenging neurodegenerative disorder. Despite significant advancements in machine learning technique...

Length-scale study in deep learning prediction for non-small cell lung cancer brain metastasis.

Scientific reports
Deep learning-assisted digital pathology has demonstrated the potential to profoundly impact clinical practice, even surpassing human pathologists in performance. However, as deep neural network (DNN) architectures grow in size and complexity, their ...

Pattern recognition using spiking antiferromagnetic neurons.

Scientific reports
Spintronic devices offer a promising avenue for the development of nanoscale, energy-efficient artificial neurons for neuromorphic computing. It has previously been shown that with antiferromagnetic (AFM) oscillators, ultra-fast spiking artificial ne...

Predicting standardized uptake value of brown adipose tissue from CT scans using convolutional neural networks.

Nature communications
The standard method for identifying active Brown Adipose Tissue (BAT) is [F]-Fluorodeoxyglucose ([F]-FDG) PET/CT imaging, which is costly and exposes patients to radiation, making it impractical for population studies. These issues can be addressed w...

A novel hybrid deep learning IChOA-CNN-LSTM model for modality-enriched and multilingual emotion recognition in social media.

Scientific reports
In the rapidly evolving field of artificial intelligence, the importance of multimodal sentiment analysis has never been more evident, especially amid the ongoing COVID-19 pandemic. Our research addresses the critical need to understand public sentim...

Hand gesture recognition using sEMG signals with a multi-stream time-varying feature enhancement approach.

Scientific reports
Hand gesture recognition based on sparse multichannel surface electromyography (sEMG) still poses a significant challenge to deployment as a muscle-computer interface. Many researchers have been working to develop an sEMG-based hand gesture recogniti...

Deep learning domain adaptation to understand physico-chemical processes from fluorescence spectroscopy small datasets and application to the oxidation of olive oil.

Scientific reports
Fluorescence spectroscopy is a fundamental tool in life sciences and chemistry, with applications in environmental monitoring, food quality control, and biomedical diagnostics. However, analysis of spectroscopic data with deep learning, in particular...

Detection of breast cancer in digital breast tomosynthesis with vision transformers.

Scientific reports
Digital Breast Tomosynthesis (DBT) has revolutionized more traditional breast imaging through its three-dimensional (3D) visualization capability that significantly enhances lesion discernibility, reduces tissue overlap, and improves diagnostic preci...

Microbe-drug association prediction model based on graph convolution and attention networks.

Scientific reports
The human microbiome plays a key role in drug development and precision medicine, but understanding its complex interactions with drugs remains a challenge. Identifying microbe-drug associations not only enhances our understanding of their mechanisms...

Integrating dynamic models and neural networks to discover the mechanism of meteorological factors on Aedes population.

PLoS computational biology
Aedes mosquitoes, known as vectors of mosquito-borne diseases, pose significant risks to public health and safety. Modeling the population dynamics of Aedes mosquitoes requires comprehensive approaches due to the complex interplay between biological ...