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Topic Review
Efficient Thorax Disease Classification by DCNN
Thorax disease is a life-threatening disease caused by bacterial infections that occur in the lungs. It could be deadly if not treated at the right time, so early diagnosis of thoracic diseases is vital. Computer vision techniques using deep learning are being used specifically for categorizing medical and natural images. As a direct result of this endeavor’s success, many academics are presently using deep convolutional neural networks (DCNNs) to diagnose thoracic illnesses based on chest radiographs. 
  • 99
  • 27 Nov 2023
Topic Review
Algorithms for Histopathology Image Detection and Segmentation
Histopathology image analysis is considered as a gold standard for the early diagnosis of serious diseases such as cancer. The advancements in the field of computer-aided diagnosis (CAD) have led to the development of several algorithms for accurately segmenting histopathology images.
  • 218
  • 27 Nov 2023
Topic Review
Blockchain-Based Model for the Prevention of Superannuation Fraud
Superannuation is the fund set aside by employers to provide their employees with a dignified retirement. The issues can arise with retirement funds from employers, such as failure to make required contributions to an employee’s superannuation fund, incorrect payments, or debiting the wrong fund, contrary to legal or contractual obligations. Blockchain technology has gained popularity because of its ability to improve security and prevent fraud across many sectors, including finance.
  • 272
  • 27 Nov 2023
Topic Review
Olive Leaf Disease Diagnosis
Artificial intelligence has many applications in various industries, including agriculture. It can help overcome challenges by providing efficient solutions, especially in the early stages of development. When working with tree leaves to identify the type of disease, diseases often show up through changes in leaf color. Therefore, it is crucial to improve the color brightness before using them in intelligent agricultural systems.
  • 160
  • 24 Nov 2023
Topic Review
Laser Cutting Path Problem
Efficiently cutting smaller two-dimensional parts from a larger surface area is a recurring challenge in many manufacturing environments. This point falls under the cut-and-pack (C&P) problems. This research specifically focused on a specialization of the cut path determination (CPD) known as the laser cutting path planning (LCPP) problem.
  • 163
  • 24 Nov 2023
Topic Review
Healthcare Sustainability: Hospitalization Rate Forecasting
Monitoring and forecasting hospitalization rates are of essential significance to public health systems in understanding and managing overall healthcare deliveries and strategizing long-term sustainability. Early-stage prediction of hospitalization rates is crucial to meet the medical needs of numerous patients during emerging epidemic diseases such as COVID-19. Nevertheless, this is a challenging task due to insufficient data and experience. In addition, relevant existing work neglects or fails to exploit the extensive contribution of external factors such as news, policies, and geolocations. Herein, researchers demonstrate the significant relationship between hospitalization rates and COVID-19 infection cases. A transfer learning architecture with dynamic location-aware sentiment and semantic analysis (TLSS) is adapted to a new application scenario: hospitalization rate prediction during COVID-19. This architecture learns and transfers general transmission patterns of existing epidemic diseases to predict hospitalization rates during COVID-19. Researchers combine the learned knowledge with time series features and news sentiment and semantic features in a dynamic propagation process. Extensive experiments are conducted to compare the proposed approach with several state-of-the-art machine learning methods with different lead times of ground truth. The results show that TLSS exhibits outstanding predictive performance for hospitalization rates. Thus, it provides advanced artificial intelligence (AI) techniques for supporting decision-making in healthcare sustainability.
  • 343
  • 24 Nov 2023
Topic Review
Volumetric Haptic Displays
Volumetric interfaces and displays have been an area of substantial focus in human–computer interaction (HCI), bringing about new ways to enhance interactivity, learning, and understanding as an extension to existing modalities. While much research in the area exists, current haptic display projects tend to be difficult to implement as part of existing visual display technologies. 
  • 226
  • 24 Nov 2023
Topic Review
Concept Extraction in Education
In the education field, foundational subject-related knowledge reflects concepts frequently expressed as single words or phrases. Educational concepts must be blended into learning and instructional practices; students’ inadequate conceptual understanding can cause them to forget information during the learning process. Similarly, instructors can enhance learning materials’ quality through a clear sense of subject-specific concepts. Extracting concepts from various subject areas based on extensive unstructured text is thus critical for instructors and students, especially to enrich teaching and learning activities.
  • 278
  • 24 Nov 2023
Topic Review
Federated Learning Based on Deep Reinforcement Learning
Federated learning (FL) is a distributed machine learning paradigm that enables a large number of clients to collaboratively train models without sharing data.
  • 216
  • 24 Nov 2023
Topic Review
Financial Fraud Detection
The financial sector faces a significant challenge in the form of financial fraud, encompassing various forms of criminal deception aimed at securing financial gains, including activities like telecommunication fraud and credit card skimming. The proliferation of electronic payment technology has propelled online transactions into the mainstream, thereby amplifying the occurrence of fraudulent schemes. The prevalence of these fraudulent transactions has led to substantial losses for financial institutions. However, the large daily transactions pose a challenge for humans in manually identifying fraud.
  • 235
  • 24 Nov 2023
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