AIMC Topic: Deep Learning

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Deep learning techniques for liver and liver tumor segmentation: A review.

Computers in biology and medicine
Liver and liver tumor segmentation from 3D volumetric images has been an active research area in the medical image processing domain for the last few decades. The existence of other organs such as the heart, spleen, stomach, and kidneys complicate li...

ScanNet: an interpretable geometric deep learning model for structure-based protein binding site prediction.

Nature methods
Predicting the functional sites of a protein from its structure, such as the binding sites of small molecules, other proteins or antibodies, sheds light on its function in vivo. Currently, two classes of methods prevail: machine learning models built...

Risk assessment of ICU patients through deep learning technique: A big data approach.

Journal of global health
BACKGROUND: Intensive Care Unit (ICU) patients are exposed to various medications, especially during infusion, and the amount of infusion drugs and the rate of their application may negatively affect their health status. A deep learning model can mon...

Deep learning body-composition analysis of clinically acquired CT-scans estimates creatinine excretion with high accuracy in patients and healthy individuals.

Scientific reports
Assessment of daily creatinine production and excretion plays a crucial role in the estimation of renal function. Creatinine excretion is estimated by creatinine excretion equations and implicitly in eGFR equations like MDRD and CKD-EPI. These equati...

Can images crowdsourced from the internet be used to train generalizable joint dislocation deep learning algorithms?

Skeletal radiology
OBJECTIVE: Deep learning has the potential to automatically triage orthopedic emergencies, such as joint dislocations. However, due to the rarity of these injuries, collecting large numbers of images to train algorithms may be infeasible for many cen...

Deep learning architectures for Parkinson's disease detection by using multi-modal features.

Computers in biology and medicine
BACKGROUND: The use of multi-modal features for improving the diagnosing accuracy of Parkinson's disease (PD) is still under consideration.

Deep Learning Regression Approaches Applied to Estimate Tillering in Tropical Forages Using Mobile Phone Images.

Sensors (Basel, Switzerland)
We assessed the performance of Convolutional Neural Network (CNN)-based approaches using mobile phone images to estimate regrowth density in tropical forages. We generated a dataset composed of 1124 labeled images with 2 mobile phones 7 days after th...

A Combined Semi-Supervised Deep Learning Method for Oil Leak Detection in Pipelines Using IIoT at the Edge.

Sensors (Basel, Switzerland)
Pipelines are integral components for storing and transporting liquid and gaseous petroleum products. Despite being durable structures, ruptures can still occur, resulting not only in financial losses and energy waste but, most importantly, in immeas...

Developing an Intelligent System with Deep Learning Algorithms for Sentiment Analysis of E-Commerce Product Reviews.

Computational intelligence and neuroscience
Most consumers rely on online reviews when deciding to purchase e-commerce services or products. Unfortunately, the main problem of these reviews, which is not completely tackled, is the existence of deceptive reviews. The novelty of the proposed sys...

Dermoscopic Image Classification of Pigmented Nevus under Deep Learning and the Correlation with Pathological Features.

Computational and mathematical methods in medicine
The objective of this study was to explore the image classification and case characteristics of pigmented nevus (PN) diagnosed by dermoscopy under deep learning. 268 patients were included as the research objects and they were randomly divided into o...