AIMC Topic: Deep Learning

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Comprehensive Review: Machine and Deep Learning in Brain Stroke Diagnosis.

Sensors (Basel, Switzerland)
Brain stroke, or a cerebrovascular accident, is a devastating medical condition that disrupts the blood supply to the brain, depriving it of oxygen and nutrients. Each year, according to the World Health Organization, 15 million people worldwide expe...

Bibliometric analysis of the application of deep learning in cancer from 2015 to 2023.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Recently, the application of deep learning (DL) has made great progress in various fields, especially in cancer research. However, to date, the bibliometric analysis of the application of DL in cancer is scarce. Therefore, this study aime...

Uncovering hidden and complex relations of pandemic dynamics using an AI driven system.

Scientific reports
The COVID-19 pandemic continues to challenge healthcare systems globally, necessitating advanced tools for clinical decision support. Amidst the complexity of COVID-19 symptomatology and disease severity prediction, there is a critical need for robus...

Temporal-spatial cross attention network for recognizing imagined characters.

Scientific reports
Previous research has primarily employed deep learning models such as Convolutional Neural Networks (CNNs), and Recurrent Neural Networks (RNNs) for decoding imagined character signals. These approaches have treated the temporal and spatial features ...

The State-of-the-Art Overview to Application of Deep Learning in Accurate Protein Design and Structure Prediction.

Topics in current chemistry (Cham)
In recent years, there has been a notable increase in the scientific community's interest in rational protein design. The prospect of designing an amino acid sequence that can reliably fold into a desired three-dimensional structure and exhibit the i...

Single-Subject Deep-Learning Image Reconstruction With a Neural Optimization Transfer Algorithm for PET-Enabled Dual-Energy CT Imaging.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Combining dual-energy computed tomography (DECT) with positron emission tomography (PET) offers many potential clinical applications but typically requires expensive hardware upgrades or increases radiation doses on PET/CT scanners due to an extra X-...

ATR-FTIR spectroscopy and machine/deep learning models for detecting adulteration in coconut water with sugars, sugar alcohols, and artificial sweeteners.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Packaged coconut water offers various options, from pure to those with added sugars and other additives. While the purity of coconut water is esteemed for its health benefits, its popularity also exposes it to potential adulteration and misrepresenta...

Deep Learning-Based Real-Time Ureter Identification in Laparoscopic Colorectal Surgery.

Diseases of the colon and rectum
BACKGROUND: Iatrogenic ureteral injury is a serious complication of abdominopelvic surgery. Identifying the ureters intraoperatively is essential to avoid iatrogenic ureteral injury. We developed a model that may minimize this complication.

Super-resolution deep learning reconstruction approach for enhanced visualization in lumbar spine MR bone imaging.

European journal of radiology
OBJECTIVES: This study aims to assess the effectiveness of super-resolution deep-learning-based reconstruction (SR-DLR), which leverages k-space data, on the image quality of lumbar spine magnetic resonance (MR) bone imaging using a 3D multi-echo in-...