AIMC Topic: Deep Learning

Clear Filters Showing 18431 to 18440 of 28423 articles

From the Laboratory to the Field: IMU-Based Shot and Pass Detection in Football Training and Game Scenarios Using Deep Learning.

Sensors (Basel, Switzerland)
The applicability of sensor-based human activity recognition in sports has been repeatedly shown for laboratory settings. However, the transferability to real-world scenarios cannot be granted due to limitations on data and evaluation methods. On the...

Target Prediction Model for Natural Products Using Transfer Learning.

International journal of molecular sciences
A large proportion of lead compounds are derived from natural products. However, most natural products have not been fully tested for their targets. To help resolve this problem, a model using transfer learning was built to predict targets for natura...

Automated ECG classification based on 1D deep learning network.

Methods (San Diego, Calif.)
The standard 12-lead electrocardiogram (ECG) records the heart's electrical activity from electrodes on the skin, and is widely used in screening and diagnosis of the cardiac conditions due to its low price and non-invasive characteristics. Manual ex...

Internet of medical things embedding deep learning with data augmentation for mammogram density classification.

Microscopy research and technique
Females are approximately half of the total population worldwide, and most of them are victims of breast cancer (BC). Computer-aided diagnosis (CAD) frameworks can help radiologists to find breast density (BD), which further helps in BC detection pre...

Diagnosing Atrial Septal Defect from Electrocardiogram with Deep Learning.

Pediatric cardiology
The heart murmur associated with atrial septal defects is often faint and can thus only be detected by chance. Although electrocardiogram examination can prompt diagnoses, identification of specific findings remains a major challenge. We demonstrate ...

Feasibility of deep learning-based fully automated classification of microsatellite instability in tissue slides of colorectal cancer.

International journal of cancer
High levels of microsatellite instability (MSI-H) occurs in about 15% of sporadic colorectal cancer (CRC) and is an important predictive marker for response to immune checkpoint inhibitors. To test the feasibility of a deep learning (DL)-based classi...

A through-focus scanning optical microscopy dimensional measurement method based on deep-learning classification model.

Journal of microscopy
Through-focus scanning optical microscopy (TSOM) is an economical, non-contact and nondestructive method for rapid measurement of three-dimensional nanostructures. There are two methods using TSOM image to measure the dimensions of one sample, includ...

Deep learning early warning system for embryo culture conditions and embryologist performance in the ART laboratory.

Journal of assisted reproduction and genetics
Staff competency is a crucial component of the in vitro fertilization (IVF) laboratory quality management system because it impacts clinical outcomes and informs the key performance indicators (KPIs) used to continuously monitor and assess culture co...

Automatic control of simulated moving bed process with deep Q-network.

Journal of chromatography. A
Optimal control of a simulated moving bed (SMB) process is challenging because the system dynamics is represented as nonlinear partial differential-algebraic equations combined with discrete events. In addition, product purity constraints are active ...

An artificial intelligence deep learning model for identification of small bowel obstruction on plain abdominal radiographs.

The British journal of radiology
OBJECTIVES: Small bowel obstruction is a common surgical emergency which can lead to bowel necrosis, perforation and death. Plain abdominal X-rays are frequently used as a first-line test but the availability of immediate expert radiological review i...