AIMC Topic: Deep Learning

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A deep learning model to classify and detect brain abnormalities in portable microwave based imaging system.

Scientific reports
Automated classification and detection of brain abnormalities like a tumor(s) in reconstructed microwave (RMW) brain images are essential for medical application investigation and monitoring disease progression. This paper presents the automatic clas...

Multi-label annotation of text reports from computed tomography of the chest, abdomen, and pelvis using deep learning.

BMC medical informatics and decision making
BACKGROUND: There is progress to be made in building artificially intelligent systems to detect abnormalities that are not only accurate but can handle the true breadth of findings that radiologists encounter in body (chest, abdomen, and pelvis) comp...

Detection and Classification of Colorectal Polyp Using Deep Learning.

BioMed research international
Colorectal Cancer (CRC) is the third most dangerous cancer in the world and also increasing day by day. So, timely and accurate diagnosis is required to save the life of patients. Cancer grows from polyps which can be either cancerous or noncancerous...

Real-Time Twitter Spam Detection and Sentiment Analysis using Machine Learning and Deep Learning Techniques.

Computational intelligence and neuroscience
In this modern world, we are accustomed to a constant stream of data. Major social media sites like Twitter, Facebook, or Quora face a huge dilemma as a lot of these sites fall victim to spam accounts. These accounts are made to trap unsuspecting gen...

Diagnosis of Retinal Diseases Based on Bayesian Optimization Deep Learning Network Using Optical Coherence Tomography Images.

Computational intelligence and neuroscience
Retinal abnormalities have emerged as a serious public health concern in recent years and can manifest gradually and without warning. These diseases can affect any part of the retina, causing vision impairment and indeed blindness in extreme cases. T...

Automated quality assessment of chest radiographs based on deep learning and linear regression cascade algorithms.

European radiology
OBJECTIVES: Develop and evaluate the performance of deep learning and linear regression cascade algorithms for automated assessment of the image layout and position of chest radiographs.

Root-zone soil moisture estimation based on remote sensing data and deep learning.

Environmental research
Soil moisture in the root zone is the most important factor in eco-hydrological processes. Even though soil moisture can be obtained by remote sensing, limited to the top few centimeters (<5 cm). Researchers have attempted to estimate root-zone soil ...

A deep learning masked segmentation alternative to manual segmentation in biparametric MRI prostate cancer radiomics.

European radiology
OBJECTIVES: To determine the value of a deep learning masked (DLM) auto-fixed volume of interest (VOI) segmentation method as an alternative to manual segmentation for radiomics-based diagnosis of clinically significant (CS) prostate cancer (PCa) on ...

Weed Classification from Natural Corn Field-Multi-Plant Images Based on Shallow and Deep Learning.

Sensors (Basel, Switzerland)
Crop and weed discrimination in natural field environments is still challenging for implementing automatic agricultural practices, such as weed control. Some weed control methods have been proposed. However, these methods are still restricted as they...