AIMC Topic: Deep Learning

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Machine Learning Classifiers for Twitter Surveillance of Vaping: Comparative Machine Learning Study.

Journal of medical Internet research
BACKGROUND: Twitter presents a valuable and relevant social media platform to study the prevalence of information and sentiment on vaping that may be useful for public health surveillance. Machine learning classifiers that identify vaping-relevant tw...

Generating diagnostic report for medical image by high-middle-level visual information incorporation on double deep learning models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Writing diagnostic reports for medical images is a heavy and tedious work. The automatic generation of medical image diagnostic reports can assist doctors to reduce their workload and improve diagnosis efficiency. It is of ...

Deep learning based genome analysis and NGS-RNA LL identification with a novel hybrid model.

Bio Systems
The conventional image segmentation techniques have a lot of issues with highest computational cost and low level accuracy for medical image diagnosis and genome analysis. The deep learning based optimization models utilize to predict the liver cance...

3D Automatic Segmentation of Aortic Computed Tomography Angiography Combining Multi-View 2D Convolutional Neural Networks.

Cardiovascular engineering and technology
PURPOSE: The quantitative analysis of contrast-enhanced Computed Tomography Angiography (CTA) is essential to assess aortic anatomy, identify pathologies, and perform preoperative planning in vascular surgery. To overcome the limitations given by man...

Comparison of CBCT-based dose calculation methods in head and neck cancer radiotherapy: from Hounsfield unit to density calibration curve to deep learning.

Medical physics
PURPOSE: Anatomical variations occur during head and neck (H&N) radiotherapy treatment. kV cone-beam computed tomography (CBCT) images can be used for daily dose monitoring to assess dose variations owing to anatomic changes. Deep learning methods (D...

Assessment and Estimation of Face Detection Performance Based on Deep Learning for Forensic Applications.

Sensors (Basel, Switzerland)
Face recognition is a valuable forensic tool for criminal investigators since it certainly helps in identifying individuals in scenarios of criminal activity like fugitives or child sexual abuse. It is, however, a very challenging task as it must be ...

A Deep-Learning Approach for Foot-Type Classification Using Heterogeneous Pressure Data.

Sensors (Basel, Switzerland)
The human foot is easily deformed owing to the innate form of the foot or an incorrect walking posture. Foot deformations not only pose a threat to foot health but also cause fatigue and pain when walking; therefore, accurate diagnoses of foot deform...

Personal identification with orthopantomography using simple convolutional neural networks: a preliminary study.

Scientific reports
Forensic dental examination has played an important role in personal identification (PI). However, PI has essentially been based on traditional visual comparisons of ante- and postmortem dental records and radiographs, and there is no globally accept...

Identifying COVID19 from Chest CT Images: A Deep Convolutional Neural Networks Based Approach.

Journal of healthcare engineering
Coronavirus Disease (COVID19) is a fast-spreading infectious disease that is currently causing a healthcare crisis around the world. Due to the current limitations of the reverse transcription-polymerase chain reaction (RT-PCR) based tests for detect...

Use of deep learning methods to translate drug-induced gene expression changes from rat to human primary hepatocytes.

PloS one
In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the results of animal and in vitro model exposures to r...