AIMC Topic: Algorithms

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Using a Deep Learning Model to Explore the Impact of Clinical Data on COVID-19 Diagnosis Using Chest X-ray.

Sensors (Basel, Switzerland)
The coronavirus pandemic (COVID-19) is disrupting the entire world; its rapid global spread threatens to affect millions of people. Accurate and timely diagnosis of COVID-19 is essential to control the spread and alleviate risk. Due to the promising ...

Preoperative planning method based on a MOPSO algorithm for robot-assisted cholecystectomy.

International journal of computer assisted radiology and surgery
PURPOSE: Surgical robots have multiple manipulators with complex mechanisms and need to work in a narrow space in the patient's body. Therefore, for robot-assisted minimally invasive surgery (RMIS), it is very important to develop a reasonable preope...

Oncocytoma-Related Gene Signature to Differentiate Chromophobe Renal Cancer and Oncocytoma Using Machine Learning.

Cells
Publicly available gene expression datasets were analyzed to develop a chromophobe and oncocytoma related gene signature (COGS) to distinguish chRCC from RO. The datasets GSE11151, GSE19982, GSE2109, GSE8271 and GSE11024 were combined into a discover...

A U-Net Approach to Apical Lesion Segmentation on Panoramic Radiographs.

BioMed research international
The purpose of the paper was the assessment of the success of an artificial intelligence (AI) algorithm formed on a deep-convolutional neural network (D-CNN) model for the segmentation of apical lesions on dental panoramic radiographs. A total of 470...

Deep Learning Application for Effective Classification of Different Types of Psoriasis.

Journal of healthcare engineering
Psoriasis is a chronic inflammatory skin disorder mediated by the immune response that affects a large number of people. According to latest worldwide statistics, 125 million individuals are suffering from psoriasis. Deep learning techniques have dem...

An exploration of error-driven learning in simple two-layer networks from a discriminative learning perspective.

Behavior research methods
Error-driven learning algorithms, which iteratively adjust expectations based on prediction error, are the basis for a vast array of computational models in the brain and cognitive sciences that often differ widely in their precise form and applicati...

Artificial intelligence for dermatopathology: Current trends and the road ahead.

Seminars in diagnostic pathology
Artificial intelligence (AI), including deep learning methods that leverage neural network-based algorithms, hold significant promise for dermatopathology and other areas of diagnostic pathology in research and clinical practice. There has been signi...

Muscle force estimation from lower limb EMG signals using novel optimised machine learning techniques.

Medical & biological engineering & computing
The main objective of this work is to establish a framework for processing and evaluating the lower limb electromyography (EMG) signals ready to be fed to a rehabilitation robot. We design and build a knee rehabilitation robot that works with surface...

StrVCTVRE: A supervised learning method to predict the pathogenicity of human genome structural variants.

American journal of human genetics
Whole-genome sequencing resolves many clinical cases where standard diagnostic methods have failed. However, at least half of these cases remain unresolved after whole-genome sequencing. Structural variants (SVs; genomic variants larger than 50 base ...