AIMC Topic: Deep Learning

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Multitask Deep Learning for Segmentation and Classification of Primary Bone Tumors on Radiographs.

Radiology
Background An artificial intelligence model that assesses primary bone tumors on radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep learning (DL) model for simultaneous bounding box placement, segmentation, and cla...

Colorectal Polyp Image Detection and Classification through Grayscale Images and Deep Learning.

Sensors (Basel, Switzerland)
Colonoscopy screening and colonoscopic polypectomy can decrease the incidence and mortality rate of colorectal cancer (CRC). The adenoma detection rate and accuracy of diagnosis of colorectal polyp which vary in different experienced endoscopists hav...

Automatically disambiguating medical acronyms with ontology-aware deep learning.

Nature communications
Modern machine learning (ML) technologies have great promise for automating diverse clinical and research workflows; however, training them requires extensive hand-labelled datasets. Disambiguating abbreviations is important for automated clinical no...

Mobile microscopy and telemedicine platform assisted by deep learning for the quantification of Trichuris trichiura infection.

PLoS neglected tropical diseases
Soil-transmitted helminths (STH) are the most prevalent pathogens among the group of neglected tropical diseases (NTDs). The Kato-Katz technique is the diagnosis method recommended by the World Health Organization (WHO) although it often presents a d...

ReFeaFi: Genome-wide prediction of regulatory elements driving transcription initiation.

PLoS computational biology
Regulatory elements control gene expression through transcription initiation (promoters) and by enhancing transcription at distant regions (enhancers). Accurate identification of regulatory elements is fundamental for annotating genomes and understan...

Study on 3D Clothing Color Application Based on Deep Learning-Enabled Macro-Micro Adversarial Network and Human Body Modeling.

Computational intelligence and neuroscience
In real life, people's life gradually tends to be simple, so the convenience of online shopping makes more and more research begin to explore the convenience optimization of shopping, in which the fitting system is the research product. However, due ...

Optimization Research on Deep Learning and Temporal Segmentation Algorithm of Video Shot in Basketball Games.

Computational intelligence and neuroscience
The analysis of the video shot in basketball games and the edge detection of the video shot are the most active and rapid development topics in the field of multimedia research in the world. Video shots' temporal segmentation is based on video image ...

Influential Usage of Big Data and Artificial Intelligence in Healthcare.

Computational and mathematical methods in medicine
Artificial intelligence (AI) is making computer systems capable of executing human brain tasks in many fields in all aspects of daily life. The enhancement in information and communications technology (ICT) has indisputably improved the quality of pe...

Comparison of two deep learning image reconstruction algorithms in chest CT images: A task-based image quality assessment on phantom data.

Diagnostic and interventional imaging
PURPOSE: The purpose of this study was to compare the effect of two deep learning image reconstruction (DLR) algorithms in chest computed tomography (CT) with different clinical indications.

Multitrait machine- and deep-learning models for genomic selection using spectral information in a wheat breeding program.

The plant genome
Prediction of breeding values is central to plant breeding and has been revolutionized by the adoption of genomic selection (GS). Use of machine- and deep-learning algorithms applied to complex traits in plants can improve prediction accuracies. Beca...