AIMC Topic: Neural Networks, Computer

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3D-MRI brain glioma intelligent segmentation based on improved 3D U-net network.

PloS one
PURPOSE: To enhance glioma segmentation, a 3D-MRI intelligent glioma segmentation method based on deep learning is introduced. This method offers significant guidance for medical diagnosis, grading, and treatment strategy selection.

NeuroEmo: A neuroimaging-based fMRI dataset to extract temporal affective brain dynamics for Indian movie video clips stimuli using dynamic functional connectivity approach with graph convolution neural network (DFC-GCNN).

Computers in biology and medicine
FMRI, a non-invasive neuroimaging technique, can detect emotional brain activation patterns. It allows researchers to observe functional changes in the brain, making it a valuable tool for emotion recognition. For improved emotion recognition systems...

Advancing Direct Tablet Compression with AI: A multi-task framework for quality control, batch acceptance, and causal analysis.

European journal of pharmaceutical sciences : official journal of the European Federation for Pharmaceutical Sciences
Pharmaceutical manufacturing has surged in drug development with the rise of Pharma 4.0, leveraging artificial intelligence (AI) to improve efficiency, optimize resource use, and reduce production times. Direct Tablet Compression (DTC), a key manufac...

Soft-tissue prediction based on 3D photographs for virtual surgery planning of orthognathic surgery.

Computers in biology and medicine
OBJECTIVES: In orthognathic surgery, preoperative three-dimensional soft-tissue simulations are frequently used to determine the desired jaw displacements to enhance the facial soft tissue. This study aimed to develop and validate a deep learning-bas...

Enhancing drug-drug interaction classification by leveraging textual drug arguments.

Computers in biology and medicine
BACKGROUND: The accurate identification and classification of drug-drug interactions (DDIs) are critical for ensuring patient safety and optimizing treatment outcomes in modern healthcare. Traditional methods for DDI classification primarily focus on...

Implementation of biomedical segmentation for brain tumor utilizing an adapted U-net model.

Computers in biology and medicine
Using radio signals from a magnetic field, magnetic resonance imaging (MRI) represents a medical procedure that produces images to provide more information than typical scans. Diagnosing brain tumors from MRI is difficult because of the wide range of...

Integrated Intelligent Material Recognition and Information Exchange Platform Based on a Highly Sensitive Flexible Pressure Sensor and Electroluminescent Display.

ACS sensors
Flexible pressure sensors have become a research hotspot in human-computer interaction and material recognition due to their flexibility and high sensitivity. However, the identified information relies on traditional displays and cannot be dynamicall...

Multivariate and Machine Learning-Derived Virtual Staining and Biochemical Quantification of Cancer Cells through Raman Hyperspectral Imaging.

Analytical chemistry
Advances in virtual staining and spatial omics have revolutionized our ability to explore cellular architecture and molecular composition with unprecedented detail. Virtual staining techniques, which rely on computational algorithms to map molecular ...

Time-Gated Raman Spectroscopy Combined with Deep Learning for Rapid, Label-Free Histopathological Discrimination of Gastric Cancer.

Analytical chemistry
Gastric cancer is one of the most common malignant tumors of the digestive system, with a high mortality rate due to late-stage diagnosis. Current clinical diagnosis relies on endoscopic biopsy and histopathological analysis, which are highly depende...