AIMC Topic: Deep Learning

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Premature Ventricular Contraction Recognition Based on a Deep Learning Approach.

Journal of healthcare engineering
Electrocardiogram signal (ECG) is considered a significant biological signal employed to diagnose heart diseases. An ECG signal allows the demonstration of the cyclical contraction and relaxation of human heart muscles. This signal is a primary and n...

Models of Artificial Intelligence-Assisted Diagnosis of Lung Cancer Pathology Based on Deep Learning Algorithms.

Journal of healthcare engineering
In this article, in order to explore the application of a diagnosis system for lung cancer, we use an auxiliary diagnostic system to predict and diagnose the good and evil attributes of chest CT pulmonary nodules. This research improves the new diagn...

Detection of Types of Mental Illness through the Social Network Using Ensembled Deep Learning Model.

Computational intelligence and neuroscience
In today's era, social networking platforms are widely used to share emotions. These types of emotions are often analyzed to predict the user's behavior. In this paper, these types of sentiments are classified to predict the mental illness of the use...

An Optimized Decision Method for Smart Teaching Effect Based on Cloud Computing and Deep Learning.

Computational intelligence and neuroscience
In order to improve the effect of intelligent teaching and give full play to the role of intelligent technology in modern physical education, in this paper, cloud computing and deep learning methods are used to comprehensively evaluate the teaching e...

Application of Lightweight Deep Learning Model in Vocal Music Education in Higher Institutions.

Computational intelligence and neuroscience
The aim is to improve the teaching quality of music majors and cultivate their innovative ability. This article takes Vocal Music Education (VME) method as the research object to explore the teaching reform of Music Major courses. Firstly, this artic...

Dosimetric assessment of patient dose calculation on a deep learning-based synthesized computed tomography image for adaptive radiotherapy.

Journal of applied clinical medical physics
PURPOSE: Dose computation using cone beam computed tomography (CBCT) images is inaccurate for the purpose of adaptive treatment planning. The main goal of this study is to assess the dosimetric accuracy of synthetic computed tomography (CT)-based cal...

Feasibility of a deep learning-based diagnostic platform to evaluate lower urinary tract disorders in men using simple uroflowmetry.

Investigative and clinical urology
PURPOSE: To diagnose lower urinary tract symptoms (LUTS) in a noninvasive manner, we created a prediction model for bladder outlet obstruction (BOO) and detrusor underactivity (DUA) using simple uroflowmetry. In this study, we used deep learning to a...

Colon Cancer Grading Using Infrared Spectroscopic Imaging-Based Deep Learning.

Applied spectroscopy
Tumor grade assessment is critical to the treatment of cancers. A pathologist typically evaluates grade by examining morphologic organization in tissue using hematoxylin and eosin (H&E) stained tissue sections. Fourier transform infrared spectroscopi...

Automatic Cardiac Structure Contouring for Small Datasets with Cascaded Deep Learning Models.

Journal of medical systems
Cardiac structure contouring is a time consuming and tedious manual activity used for radiotherapeutic dose toxicity planning. We developed an automatic cardiac structure segmentation pipeline for use in low-dose non-contrast planning CT based on dee...

Generation of microbial colonies dataset with deep learning style transfer.

Scientific reports
We introduce an effective strategy to generate an annotated synthetic dataset of microbiological images of Petri dishes that can be used to train deep learning models in a fully supervised fashion. The developed generator employs traditional computer...