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Topic Review
Application of Biological Domain Knowledge
Integrative approaches that utilize the biological knowledge while performing feature selection are necessary for this kind of data. The main idea behind the integrative gene selection process is to generate a ranked list of genes considering both the statistical metrics that are applied to the gene expression data, and the biological background information which is provided as external datasets. 
  • 1.1K
  • 19 Feb 2021
Topic Review
PC5-Based Cellular-V2X Evolution and Deployment
C-V2X (Cellular Vehicle-to-Everything) is a state-of-the-art wireless technology used in autonomous driving and intelligent transportation systems (ITS). 
  • 4.3K
  • 19 Feb 2021
Topic Review
Wireless Sensor System
With the generation of tremendous data, humans are experiencing a rapid development period. The large amount of data is produced from billions of wireless sensor nodes. A wireless sensor node is a sensing device capable of signal processing and data communication. A collection of those sensor nodes in a particular combination forms a wireless sensor network (WSN). Each wireless sensor node typically performs three main functions—sensing, processing, transceiving data, along with optionally issuing commands to actuators.
  • 1.3K
  • 18 Feb 2021
Topic Review
Computational Diagnostic Techniques in Electrocardiogram
Cardiovascular diseases (CVDs), including asymptomatic myocardial ischemia, angina, myocardial infarction, and ischemic heart failure, are the leading cause of death globally. Early detection and treatment of CVDs significantly contribute to the prevention or delay of cardiovascular death. Electrocardiogram (ECG) records the electrical impulses generated by heart muscles, which reflect regular or irregular beating activity. Computer-aided techniques provide fast and accurate tools to identify CVDs using a patient’s ECG signal, which have achieved great success in recent years. Latest computational diagnostic techniques based on ECG signals for estimating CVDs conditions are summarized here. The procedure of ECG signals analysis is discussed in several subsections, including data preprocessing, feature engineering, classification, and application. In particular, the End-to-End models integrate feature extraction and classification into learning algorithms, which not only greatly simplifies the process of data analysis, but also shows excellent accuracy and robustness. Portable devices enable users to monitor their cardiovascular status at any time, bringing new scenarios as well as challenges to the application of ECG algorithms. Computational diagnostic techniques for ECG signal analysis show great potential for helping health care professionals, and their application in daily life benefits both patients and sub-healthy people.
  • 1.1K
  • 18 Feb 2021
Topic Review
Contrastive Self-Supervised Learning
Self-supervised learning has gained popularity because of its ability to avoid the cost of annotating large-scale datasets. It is capable of adopting self-defined pseudolabels as supervision and use the learned representations for several downstream tasks. 
  • 1.5K
  • 18 Feb 2021
Topic Review
AI and General movements (GMs)
       General movements (GMs) are spontaneous movements of infants up to five months post-term involving the whole body varying in sequence, speed, and amplitude. The assessment of GMs has shown its importance for identifying infants at risk for neuromotor deficits, especially for the detection of cerebral palsy. As the assessment is based on videos of the infant that are rated by trained professionals, the method is time-consuming and expensive. Therefore, approaches based on Artificial Intelligence have gained significantly increased attention in the last years.
  • 1.7K
  • 18 Feb 2021
Topic Review
Heart Health Monitoring Service Platform
Heart Health Monitoring Service Platform is a concept that allows medical device manufacturers to offer diagnosis support for a range of diseases to healthcare providers. The proposed platform is based on heart rate monitoring and the diagnosis support is achieved with deep learning. 
  • 649
  • 17 Feb 2021
Topic Review
Three-Dimensional Printing
Additive manufacturing with an emphasis on 3D printing has recently become popular due to its exceptional advantages over conventional manufacturing processes. However, 3D printing process parameters are challenging to optimize, as they influence the properties and usage time of printed parts. Therefore, it is a complex task to develop a correlation between process parameters and printed parts’ properties via traditional optimization methods. A machine-learning technique was recently validated to carry out intricate pattern identification and develop a deterministic relationship, eliminating the need to develop and solve physical models. In machine learning, artificial neural network (ANN) is the most widely utilized model, owing to its capability to solve large datasets and strong computational supremacy.
  • 1.1K
  • 17 Feb 2021
Topic Review
PET/CT Radiomics in Lung Cancer
Quantitative extraction of imaging features from medical scans (‘radiomics’) has become a major research topic in recent years. Numerous studies have emphasized the potential use of radiomics for computer-assisted diagnosis, as well as for predicting survival and response to treatment in patients with lung cancer. Furthermore, radiomics is appealing in that it enables full-field analysis of the lesion, provides nearly real-time results, and is non-invasive.
  • 705
  • 17 Feb 2021
Topic Review
Autonomous Vehicle
An Autonomous Vehicle (AV), or a driverless car, or a self-driving vehicle is a car, bus, truck, or any other vehicle that is able to drive from point A to point B and perform all necessary driving operations and functions without any human intervention. An Autonomous Vehicle is normally equipped with different types of sensors to perceive the surrounding environment, including Normal Vision Cameras, Infrared Cameras, RADAR, LiDAR, and Ultrasonic Sensors.  An autonomous vehicle should be able to detect and recognise all type of road users including surrounding vehicles, pedestrians, cyclists, traffic signs, road markings, and can segment the free spaces, intersections, buildings, and trees to perform a safe driving task.  Currently, no realistic prediction expects we see fully autonomous vehicles earlier than 2030. 
  • 984
  • 17 Feb 2021
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