AIMC Topic: Neural Networks, Computer

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Substrate Activation Efficiency in Active Sites of Hydrolases Determined by QM/MM Molecular Dynamics and Neural Networks.

International journal of molecular sciences
The active sites of enzymes are able to activate substrates and perform chemical reactions that cannot occur in solutions. We focus on the hydrolysis reactions catalyzed by enzymes and initiated by the nucleophilic attack of the substrate's carbonyl ...

High-fidelity in silico generation and augmentation of TCR repertoire data using generative adversarial networks.

Scientific reports
Engineered T-cell receptor (eTCR) systems rely on accurately generated T-cell receptor (TCR) sequences to enhance immunotherapy predictability and efficacy. The most variable and crucial part of the TCR receptor is the CDR3 sequence region. Current m...

Prediction of reproductive and developmental toxicity using an attention and gate augmented graph convolutional network.

Scientific reports
Due to the diverse molecular structures of chemical compounds and their intricate biological pathways of toxicity, predicting their reproductive and developmental toxicity remains a challenge. Traditional Quantitative Structure-Activity Relationship ...

Task-specific differentiation of patellofemoral pain in women using a neural network analysis of joint angle subsets.

Gait & posture
BACKGROUND: Individuals with patellofemoral pain (PFP) present mechanical disorders during functional tests and activities. Studies often evaluate this population to understand the relationship between mechanical factors and pain/malalignment. This s...

Mobile applications for skin cancer detection are vulnerable to physical camera-based adversarial attacks.

Scientific reports
Skin cancer is one of the most prevalent malignant tumors, and early detection is crucial for patient prognosis, leading to the development of mobile applications as screening tools. Recent advances in deep neural networks (DNNs) have accelerated the...

PDS-UKAN: Subdivision hopping connected to the U-KAN network for medical image segmentation.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Accurate and efficient segmentation of medical images plays a vital role in clinical tasks, such as diagnostic procedures and planning treatments. Traditional U-shaped encoder-decoder architectures, built on convolutional and transformer-based networ...

Automated depression detection via cloud based EEG analysis with transfer learning and synchrosqueezed wavelet transform.

Scientific reports
Post-COVID-19, depression rates have risen sharply, increasing the need for early diagnosis using electroencephalogram (EEG) and deep learning. To tackle this, we developed a cloud-based computer-aided depression diagnostic (CCADD) system that utiliz...

ASLDetect: Arabic sign language detection using ResNet and U-Net like component.

Scientific reports
Sign languages are essential for communication among over 430 million deaf and hard-of-hearing individuals worldwide. However, recognizing Arabic Sign Language (ArSL) in real-world settings remains challenging due to issues like background noise, lig...

Cell-TRACTR: A transformer-based model for end-to-end segmentation and tracking of cells.

PLoS computational biology
Deep learning-based methods for identifying and tracking cells within microscopy images have revolutionized the speed and throughput of data analysis. These methods for analyzing biological and medical data have capitalized on advances from the broad...

Quantifying the roles of visual, linguistic, and visual-linguistic complexity in noun and verb acquisition.

PloS one
Children often learn the meanings of nouns before they grasp the meanings of verbs. This discrepancy could arise from differences in the complexity of visual characteristics for categories that language describes, the inherent structure of language, ...