AIMC Topic: Deep Learning

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Deep learning approach identified a gene signature predictive of the severity of renal damage caused by chronic cadmium accumulation.

Journal of hazardous materials
Epidemiology studies have indicated that environmental cadmium exposure, even at low levels, will result in chronic cadmium accumulation in the kidney with profound adverse consequences and that the diabetic population is more susceptible. However, t...

A deep learning algorithm to improve readers' interpretation and speed of pancreatic cystic lesions on dual-phase enhanced CT.

Abdominal radiology (New York)
PURPOSE: To develop a deep learning model (DLM) to improve readers' interpretation and speed in the differentiation of pancreatic cystic lesions (PCLs) on dual-phase enhanced CT, and a low contrast media dose, external testing set validated the model...

Feature Reduction for Molecular Similarity Searching Based on Autoencoder Deep Learning.

Biomolecules
The concept of molecular similarity has been commonly used in rational drug design, where structurally similar molecules are examined in molecular databases to retrieve functionally similar molecules. The most used conventional similarity methods use...

Deep Learning Based SWIR Object Detection in Long-Range Surveillance Systems: An Automated Cross-Spectral Approach.

Sensors (Basel, Switzerland)
SWIR imaging bears considerable advantages over visible-light (color) and thermal images in certain challenging propagation conditions. Thus, the SWIR imaging channel is frequently used in multi-spectral imaging systems (MSIS) for long-range surveill...

Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria.

Academic radiology
RATIONALE AND OBJECTIVES: Osteoporosis affects 9% of individuals over 50 in the United States and 200 million women globally. Spinal osteoporotic compression fractures (OCFs), an osteoporosis biomarker, are often incidental and under-reported. Accura...

Fully automatic resolution of untargeted GC-MS data with deep learning assistance.

Talanta
DeepResolution (Deep learning-assisted multivariate curve Resolution) has been proposed to solve the co-eluting problem for GC-MS data. However, DeepResolution models must be retrained when encountering unknown components, which is undoubtedly time-c...

Dose prediction via distance-guided deep learning: Initial development for nasopharyngeal carcinoma radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Geometric information such as distance information is essential for dose calculations in radiotherapy. However, state-of-the-art dose prediction methods use only binary masks without distance information. This study aims to de...

Pushing the Limits of Surface-Enhanced Raman Spectroscopy (SERS) with Deep Learning: Identification of Multiple Species with Closely Related Molecular Structures.

Applied spectroscopy
Raman spectroscopy is a non-destructive and label-free molecular identification technique capable of producing highly specific spectra with various bands correlated to molecular structure. Moreover, the enhanced detection sensitivity offered by surfa...

Prognosis patients with COVID-19 using deep learning.

BMC medical informatics and decision making
BACKGROUND: The coronavirus (COVID-19) is a novel pandemic and recently we do not have enough knowledge about the virus behaviour and key performance indicators (KPIs) to assess the mortality risk forecast. However, using a lot of complex and expensi...

Development and quantitative assessment of deep learning-based image enhancement for optical coherence tomography.

BMC ophthalmology
PURPOSE: To develop a deep learning-based framework to improve the image quality of optical coherence tomography (OCT) and evaluate its image enhancement effect with the traditional image averaging method from a clinical perspective.