AIMC Topic: Deep Learning

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Occlusion enhanced pan-cancer classification via deep learning.

BMC bioinformatics
Quantitative measurement of RNA expression levels through RNA-Seq is an ideal replacement for conventional cancer diagnosis via microscope examination. Currently, cancer-related RNA-Seq studies focus on two aspects: classifying the status and tissue ...

Deep learning-based automated angle measurement for flatfoot diagnosis in weight-bearing lateral radiographs.

Scientific reports
This study aimed to develop and evaluate a deep learning-based system for the automatic measurement of angles (specifically, Meary's angle and calcaneal pitch) in weight-bearing lateral radiographs of the foot for flatfoot diagnosis. We utilized 3960...

A deep learning model for anti-inflammatory peptides identification based on deep variational autoencoder and contrastive learning.

Scientific reports
As a class of biologically active molecules with significant immunomodulatory and anti-inflammatory effects, anti-inflammatory peptides have important application value in the medical and biotechnology fields due to their unique biological functions....

Deep learning enables accurate soft tissue tendon deformation estimation in vivo via ultrasound imaging.

Scientific reports
Image-based deformation estimation is an important tool used in a variety of engineering problems, including crack propagation, fracture, and fatigue failure. These tools have been important in biomechanics research where measuring in vitro and in vi...

A review: artificial intelligence in image-guided spinal surgery.

Expert review of medical devices
INTRODUCTION: Due to the complex anatomy of the spine and the intricate surgical procedures involved, spinal surgery demands a high level of technical expertise from surgeons. The clinical application of image-guided spinal surgery has significantly ...

A lightweight intelligent laryngeal cancer detection system for rural areas.

American journal of otolaryngology
OBJECTIVE: Early diagnosis of laryngeal cancer (LC) is crucial, particularly in rural areas. Despite existing studies on deep learning models for LC identification, challenges remain in selecting suitable models for rural areas with shortages of lary...

Fruit-In-Sight: A deep learning-based framework for secondary metabolite class prediction using fruit and leaf images.

PloS one
Fruits produce a wide variety of secondary metabolites of great economic value. Analytical measurement of the metabolites is tedious, time-consuming, and expensive. Additionally, metabolite concentrations vary greatly from tree to tree, making it dif...

Detection of Lungs Tumors in CT Scan Images Using Convolutional Neural Networks.

IEEE/ACM transactions on computational biology and bioinformatics
Current human being's lifestyle has caused / exacerbated many diseases. One of these diseases is cancer, and among all kinds of cancers like, brain pulmonary; lung cancer is fatal. The cancers could be detected early to save lives using Computer Aide...

Artificial Intelligence and Blockchain Enabled Smart Healthcare System for Monitoring and Detection of COVID-19 in Biomedical Images.

IEEE/ACM transactions on computational biology and bioinformatics
Millions of individuals around the world have been impacted by the ongoing coronavirus outbreak, known as the COVID-19 pandemic. Blockchain, Artificial Intelligence (AI), and other cutting-edge digital and innovative technologies have all offered pro...

Hierarchical Hybrid Networks for Automatic Pulmonary Blood Vessel Segmentation in Computed Tomography Images.

IEEE/ACM transactions on computational biology and bioinformatics
Pulmonary arterial hypertension (PAH) is considered the third most common cardiovascular disease after coronary heart disease and hypertension. The diagnosis of PAH is mainly based on the comprehensive judgment of computed tomography and other medica...