AIMC Topic: Algorithms

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A medical percussion instrument using a wavelet-based method for archivable output and automatic classification.

Computers in biology and medicine
There is no standard instrument for carrying out medical percussion even though the procedure has been in continuous use since 1761. This study developed one such instrument. It generates medical percussion sounds in a reproducible manner and accurat...

Development and Validation of a Deep Learning-Based Automatic Brain Segmentation and Classification Algorithm for Alzheimer Disease Using 3D T1-Weighted Volumetric Images.

AJNR. American journal of neuroradiology
BACKGROUND AND PURPOSE: Limited evidence has suggested that a deep learning automatic brain segmentation and classification method, based on T1-weighted brain MR images, can predict Alzheimer disease. Our aim was to develop and validate a deep learni...

Application of Transfer Learning in EEG Decoding Based on Brain-Computer Interfaces: A Review.

Sensors (Basel, Switzerland)
The algorithms of electroencephalography (EEG) decoding are mainly based on machine learning in current research. One of the main assumptions of machine learning is that training and test data belong to the same feature space and are subject to the s...

Smartphone Motion Sensor-Based Complex Human Activity Identification Using Deep Stacked Autoencoder Algorithm for Enhanced Smart Healthcare System.

Sensors (Basel, Switzerland)
Human motion analysis using a smartphone-embedded accelerometer sensor provided important context for the identification of static, dynamic, and complex sequence of activities. Research in smartphone-based motion analysis are implemented for tasks, s...

Identification of early liver toxicity gene biomarkers using comparative supervised machine learning.

Scientific reports
Screening agrochemicals and pharmaceuticals for potential liver toxicity is required for regulatory approval and is an expensive and time-consuming process. The identification and utilization of early exposure gene signatures and robust predictive mo...

[A brief history of artificial intelligence].

Medecine sciences : M/S
For more than a decade, we have witnessed an acceleration in the development and the adoption of artificial intelligence (AI) technologies. In medicine, it impacts clinical and fundamental research, hospital practices, medical examinations, hospital ...

A Multifeature Extraction Method Using Deep Residual Network for MR Image Denoising.

Computational and mathematical methods in medicine
In order to improve the resolution of magnetic resonance (MR) image and reduce the interference of noise, a multifeature extraction denoising algorithm based on a deep residual network is proposed. First, the feature extraction layer is constructed b...

A novel Chebyshev neural network approach for solving singular arbitrary order Lane-Emden equation arising in astrophysics.

Network (Bristol, England)
The motivation of this investigation is to develop a single-layer Chebyshev Neural Network (ChNN) model to handle singular fractional (arbitrary)-order Lane-Emden type equations. These equations are well-known application problems of astrophysics and...

Fully-automated functional region annotation of liver via a 2.5D class-aware deep neural network with spatial adaptation.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Automatic functional region annotation of liver should be very useful for preoperative planning of liver resection in the clinical domain. However, many traditional computer-aided annotation methods based on anatomical landm...

Radiomic Detection of EGFR Mutations in NSCLC.

Cancer research
Radiomics is defined as the use of automated or semi-automated post-processing and analysis of multiple features derived from imaging exams. Extracted features might generate models able to predict the molecular profile of solid tumors. The aim of th...