AIMC Topic: Neural Networks, Computer

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Dynamicasome-a molecular dynamics-guided and AI-driven pathogenicity prediction catalogue for all genetic mutations.

Communications biology
Advances in genomic medicine accelerate the identification of mutations in disease-associated genes, but the pathogenicity of many mutations remains unknown, hindering their use in diagnostics and clinical decision-making. Predictive AI models are ge...

Deep learning-based video analysis for automatically detecting penetration and aspiration in videofluoroscopic swallowing study.

Scientific reports
The videofluoroscopic swallowing study (VFSS) is the gold standard for diagnosing dysphagia, but its interpretation is time-consuming and requires expertise. This study developed a deep learning model for automatically detecting penetration and aspir...

AG-MS3D-CNN multiscale attention guided 3D convolutional neural network for robust brain tumor segmentation across MRI protocols.

Scientific reports
Accurate segmentation of brain tumors from multimodal Magnetic Resonance Imaging (MRI) plays a critical role in diagnosis, treatment planning, and disease monitoring in neuro-oncology. Traditional methods of tumor segmentation, often manual and labou...

Novel 59-layer dense inception network for robust deepfake identification.

Scientific reports
The exponential growth of Artificial Intelligence (AI) has led to the emergence of cutting edge methods and a plethora of new tools for media editing. The use of these tools has also facilitated the spread of false information, propaganda, and harass...

Vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation.

PloS one
This article proposes a novel approach for vibration-based gearbox fault diagnosis using a multi-scale convolutional neural network with depth-wise feature concatenation named MixNet. In industrial environments where equipment reliability directly im...

Estimation of compressive strength of ultra-high performance lightweight concrete (UHPLC) using neural network.

PloS one
High strength and lightweight are key trends in concrete development. Achieving a balance between these properties to produce high structural efficiency (strength-to-weight ratio) concrete is challenging due to the complex relationship between compre...

Application effect of short-term traffic flow prediction method based on CNNBLSTM algorithm.

PloS one
Reduced forecast efficiency and accuracy are the result of traditional traffic flow prediction algorithms' inability to adequately capture the spatiotemporal characteristics and dynamic changes of traffic flow. To address this problem, this study pro...

Developing Hybrid Machine Learning Frameworks for Polymer Property Prediction Based on Composition and Sequence Features.

Journal of chemical information and modeling
Artificial intelligence (AI) plays a significant role in advancing polymer science and engineering. Considering the critical role of the glass transition temperature () in determining the physical properties of polymers, this study systematically inv...

The application of improved AFCNN model for children's psychological emotion recognition.

Scientific reports
Children's mental health has become an increasingly prominent concern in modern education. However, insufficient attention from schools and families to children's psychological and emotional issues has exacerbated the problem. This study proposes a p...

Deep learning-derived optimal annotation strategies to power the systematic mapping of peptide space.

Food chemistry
Rapid and reliable peptide identification techniques are essential for proteomics. High-resolution tandem mass spectrometry acquires a large amount of data through data-dependent acquisition (DDA) and data-independent acquisition (DIA), but tradition...