AIMC Topic: Neural Networks, Computer

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A novel application of neural networks to identify potentially effective combinations of biologic factors for enhancement of bone fusion/repair.

PloS one
INTRODUCTION: The use of biologic adjuvants (orthobiologics) is becoming commonplace in orthopaedic surgery. Among other applications, biologics are often added to enhance fusion rates in spinal surgery and to promote bone healing in complex fracture...

CATNet: Cross-event attention-based time-aware network for medical event prediction.

Artificial intelligence in medicine
Medical event prediction (MEP) is a fundamental task in the healthcare domain, which needs to predict medical events, including medications, diagnosis codes, laboratory tests, procedures, outcomes, and so on, according to historical medical records o...

Virtual disease landscape using mechanics-informed machine learning: Application to esophageal disorders.

Artificial intelligence in medicine
Esophageal disorders are related to the mechanical properties and function of the esophageal wall. Therefore, to understand the underlying fundamental mechanisms behind various esophageal disorders, it is crucial to map mechanical behavior of the eso...

Not from Scratch: Predicting Thermophysical Properties through Model-Based Transfer Learning Using Graph Convolutional Networks.

Journal of chemical information and modeling
In this study, a framework for the prediction of thermophysical properties based on transfer learning from existing estimation models is explored. The predictive capabilities of conventional group-contribution methods and traditional machine-learning...

Classification of Holograms with 3D-CNN.

Sensors (Basel, Switzerland)
A hologram, measured by using appropriate coherent illumination, records all substantial volumetric information of the measured sample. It is encoded in its interference patterns and, from these, the image of the sample objects can be reconstructed i...

Estimation of the Kinematics and Workspace of a Robot Using Artificial Neural Networks.

Sensors (Basel, Switzerland)
At present, in specific and complex industrial operations, robots have to respect certain requirements and criteria as high kinematic or dynamic performance, specific dimensions of the workspace, or limitation of the dimensions of the mobile elements...

Improving the Reliability of Scale-Free Image Morphometrics in Applications with Minimally Restrained Livestock Using Projective Geometry and Unsupervised Machine Learning.

Sensors (Basel, Switzerland)
Advances in neural networks have garnered growing interest in applications of machine vision in livestock management, but simpler landmark-based approaches suitable for small, early stage exploratory studies still represent a critical stepping stone ...

Detection of arrhythmia in 12-lead varied-length ECG using multi-branch signal fusion network.

Physiological measurement
Automatic detection of arrhythmia based on electrocardiogram (ECG) plays a critical role in early prevention and diagnosis of cardiovascular diseases. With the increase in widely available digital ECG data and the development of deep learning, multi-...

A multi-granularity convolutional neural network model with temporal information and attention mechanism for efficient diabetes medical cost prediction.

Computers in biology and medicine
As the cost of diabetes treatment continues to grow, it is critical to accurately predict the medical costs of diabetes. Most medical cost studies based on convolutional neural networks (CNNs) ignore the importance of multi-granularity information of...

A Review on Rolling Bearing Fault Signal Detection Methods Based on Different Sensors.

Sensors (Basel, Switzerland)
As a precision mechanical component to reduce friction between components, the rolling bearing is widely used in many fields because of its slight friction loss, strong bearing capacity, high precision, low power consumption, and high mechanical effi...