AIMC Topic: Deep Learning

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Exhaled breath signal analysis for diabetes detection: an optimized deep learning approach.

Computer methods in biomechanics and biomedical engineering
In this study, a flexible deep learning system for breath analysis is created using an optimal hybrid deep learning model. To improve the quality of the gathered breath signals, the raw data are first pre-processed. Then, the most relevant features l...

Intelligent Detection Method for Wildlife Based on Deep Learning.

Sensors (Basel, Switzerland)
Wildlife is an important part of natural ecosystems and protecting wildlife plays a crucial role in maintaining ecological balance. The wildlife detection method for images and videos based on deep learning can save a lot of labor costs and is of gre...

Single-Cell Radiation Response Scoring with the Deep Learning Algorithm CeCILE 2.0.

Cells
External stressors, such as ionizing radiation, have massive effects on life, survival, and the ability of mammalian cells to divide. Different types of radiation have different effects. In order to understand these in detail and the underlying mecha...

Deep learning-based image classification of turtles imported into Korea.

Scientific reports
Although turtles play a key role in maintaining healthy and balanced environments, these are endangered due to global trade to meet the high demand for food, medicine, and pets in Asia. In addition, imported non-native turtles have been controlled as...

Preliminary analysis of predicting the first recurrence in patients with neovascular age-related macular degeneration using deep learning.

BMC ophthalmology
BACKGROUND: To predict, using deep learning, the first recurrence in patients with neovascular age-related macular degeneration (nAMD) after three monthly loading injections of intravitreal anti-vascular endothelial growth factor (anti-VEGF).

Fully automated deep learning models with smartphone applicability for prediction of pain using the Feline Grimace Scale.

Scientific reports
This study used deep neural networks and machine learning models to predict facial landmark positions and pain scores using the Feline Grimace Scale (FGS). A total of 3447 face images of cats were annotated with 37 landmarks. Convolutional neural net...

Pattern recognition of forced oscillation technique measurement results using deep learning can identify asthmatic patients more accurately than setting reference ranges.

Scientific reports
No official clinical reference values have been established for MostGraph, which measures total respiratory resistance and reactance using the forced oscillation technique, complicating result interpretation. This study aimed to establish a reference...

Deep learning-based segmentation of multisite disease in ovarian cancer.

European radiology experimental
PURPOSE: To determine if pelvic/ovarian and omental lesions of ovarian cancer can be reliably segmented on computed tomography (CT) using fully automated deep learning-based methods.

Research on augmented reality navigation of in vitro fenestration of stent-graft based on deep learning and virtual-real registration.

Computer assisted surgery (Abingdon, England)
OBJECTIVES: fenestration of stent-graft (IVFS) demands high-precision navigation methods to achieve optimal surgical outcomes. This study aims to propose an augmented reality (AR) navigation method for IVFS, which can provide overlay display to loc...

Increased interpretation of deep learning models using hierarchical cluster-based modelling.

PloS one
Linear prediction models based on data with large inhomogeneity or abrupt non-linearities often perform poorly because relationships between groups in the data dominate the model. Given that the data is locally linear, this can be overcome by splitti...