AIMC Topic: Deep Learning

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Deep Learning Model for Cosmetic Gel Classification Based on a Short-Time Fourier Transform and Spectrogram.

ACS applied materials & interfaces
Cosmetics and topical medications, such as gels, foams, creams, and lotions, are viscoelastic substances that are applied to the skin or mucous membranes. The human perception of these materials is complex and involves multiple sensory modalities. Tr...

A Survey of Deep Learning Methods for Estimating the Accuracy of Protein Quaternary Structure Models.

Biomolecules
The quality prediction of quaternary structure models of a protein complex, in the absence of its true structure, is known as the Estimation of Model Accuracy (EMA). EMA is useful for ranking predicted protein complex structures and using them approp...

Image analysis and teaching strategy optimization of folk dance training based on the deep neural network.

Scientific reports
To improve the recognition effect of the folk dance image recognition model and put forward new suggestions for teachers' teaching strategies, this study introduces a Deep Neural Network (DNN) to optimize the folk dance training image recognition mod...

Deep-learning survival analysis for patients with calcific aortic valve disease undergoing valve replacement.

Scientific reports
Calcification of the aortic valve (CAVDS) is a major cause of aortic stenosis (AS) leading to loss of valve function which requires the substitution by surgical aortic valve replacement (SAVR) or transcatheter aortic valve intervention (TAVI). These ...

Artificial intelligence in surgery.

Nature medicine
Artificial intelligence (AI) is rapidly emerging in healthcare, yet applications in surgery remain relatively nascent. Here we review the integration of AI in the field of surgery, centering our discussion on multifaceted improvements in surgical car...

Deep Learning Features and Metabolic Tumor Volume Based on PET/CT to Construct Risk Stratification in Non-small Cell Lung Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: To build a risk stratification by incorporating PET/CT-based deep learning features and whole-body metabolic tumor volume (MTV), which was to make predictions about overall survival (OS) and progression-free survival (PFS) f...

Frequency and phase correction of GABA-edited magnetic resonance spectroscopy using complex-valued convolutional neural networks.

Magnetic resonance imaging
PURPOSE: To determine the significance of complex-valued inputs and complex-valued convolutions compared to real-valued inputs and real-valued convolutions in convolutional neural networks (CNNs) for frequency and phase correction (FPC) of GABA-edite...

Deep neural network for the prediction of KRAS, NRAS, and BRAF genotypes in left-sided colorectal cancer based on histopathologic images.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
BACKGROUND: The KRAS, NRAS, and BRAF genotypes are critical for selecting targeted therapies for patients with metastatic colorectal cancer (mCRC). Here, we aimed to develop a deep learning model that utilizes pathologic whole-slide images (WSIs) to ...

Hybrid deep learning assisted multi classification: Grading of malignant thyroid nodules.

International journal for numerical methods in biomedical engineering
Thyroid nodules are commonly diagnosed with ultrasonography, which includes internal characteristics, varying looks, and hazy boundaries, making it challenging for a clinician to differentiate between malignant and benign forms based only on visual i...

Image Fusion Method Based on Snake Visual Imaging Mechanism and PCNN.

Sensors (Basel, Switzerland)
The process of image fusion is the process of enriching an image and improving the image's quality, so as to facilitate the subsequent image processing and analysis. With the increasing importance of image fusion technology, the fusion of infrared an...