AIMC Topic: Algorithms

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Is it possible to use low-dose deep learning reconstruction for the detection of liver metastases on CT routinely?

European radiology
OBJECTIVES: To compare the image quality and hepatic metastasis detection of low-dose deep learning image reconstruction (DLIR) with full-dose filtered back projection (FBP)/iterative reconstruction (IR).

Neurodynamics-driven holistic approaches to semi-supervised feature selection.

Neural networks : the official journal of the International Neural Network Society
Feature selection is a crucial part of machine learning and pattern recognition, which aims at selecting a subset of informative features from the original dataset. Because of label information, supervised feature selection performs better than unsup...

Nondestructive microbial discrimination using single-cell Raman spectra and random forest machine learning algorithm.

STAR protocols
Raman microspectroscopy is a powerful tool for obtaining biomolecular information from single microbial cells in a nondestructive manner. Here, we detail steps to discriminate prokaryotic species using single-cell Raman spectra acquisitions followed ...

Multi-perspective region-based CNNs for vertebrae labeling in intraoperative long-length images.

Computer methods and programs in biomedicine
PURPOSE: Effective aggregation of intraoperative x-ray images that capture the patient anatomy from multiple view-angles has the potential to enable and improve automated image analysis that can be readily performed during surgery. We present multi-p...

New Generation Federated Learning.

Sensors (Basel, Switzerland)
With the development of the Internet of things (IoT), federated learning (FL) has received increasing attention as a distributed machine learning (ML) framework that does not require data exchange. However, current FL frameworks follow an idealized s...

Gait Trajectory Prediction on an Embedded Microcontroller Using Deep Learning.

Sensors (Basel, Switzerland)
Achieving a normal gait trajectory for an amputee's active prosthesis is challenging due to its kinematic complexity. Accordingly, lower limb gait trajectory kinematics and gait phase segmentation are essential parameters in controlling an active pro...

Learning-based control approaches for service robots on cloth manipulation and dressing assistance: a comprehensive review.

Journal of neuroengineering and rehabilitation
BACKGROUND: Service robots are defined as reprogrammable, sensor-based mechatronic devices that perform useful services in an autonomous or semi-autonomous way to human activities in an everyday environment. As the number of elderly people grows, ser...

Deep learning-based remote-photoplethysmography measurement from short-time facial video.

Physiological measurement
. Efficient non-contact heart rate (HR) measurement from facial video has received much attention in health monitoring. Past methods relied on prior knowledge and an unproven hypothesis to extract remote photoplethysmography (rPPG) signals, e.g. manu...

MC-UNet: Multimodule Concatenation Based on U-Shape Network for Retinal Blood Vessels Segmentation.

Computational intelligence and neuroscience
Accurate retinal blood vessels segmentation is an important step in the clinical diagnosis of ophthalmic diseases. Many deep learning frameworks have come up for retinal blood vessels segmentation tasks. However, the complex vascular structure and un...

An evolutionary deep learning soft sensor model based on random forest feature selection technique for penicillin fermentation process.

ISA transactions
Accurate and reliable measurement of key biological parameters during penicillin fermentation is of great significance for improving penicillin production. In this research context, a new hybrid soft sensor model method based on RF-IHHO-LSTM (random ...