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Topic Review
Applications in Computational Pathology
Deep learning techniques, such as convolutional neural networks (CNNs), generative adversarial networks (GANs), and graph neural networks (GNNs) have, over the past decade, changed the accuracy of prediction in many diverse fields. In recent years, the application of deep learning techniques in computer vision tasks in pathology has demonstrated extraordinary potential in assisting clinicians, automating diagnoses, and reducing costs for patients.
  • 928
  • 19 Apr 2022
Topic Review
Transporting Blood Using Unmanned Aerial Vehicles
Unmanned Aerial Vehicles (UAVs) play crucial roles in numerous applications, such as healthcare services. For example, UAVs can help in disaster relief and rescue missions, such as by delivering blood samples and medical supplies.
  • 928
  • 21 Nov 2022
Topic Review
Artificial Intelligence-Based Support in Cardiology
Artificial Intelligence (AI)-based algorithms, in particular, Deep Neural Networks (DNNs), have recently revolutionized image creation. Precise segmentation of lesions may contribute to an efficient diagnostics process and a more effective selection of targeted therapy. For example, an AI-based algorithm for the segmentation of pigmented skin lesions has been developed, which enables diagnosis in the earlier stages of the disease, without invasive medical procedures. With flexibility and scalability, AI can be also considered an efficient tool for cancer diagnosis, particularly in the early stages of the disease.
  • 927
  • 27 Mar 2024
Topic Review
SAA-UNet
The disaster of the COVID-19 pandemic has claimed numerous lives and wreaked havoc on the entire world due to its transmissible nature. One of the complications of COVID-19 is pneumonia. Different radiography methods, particularly computed tomography (CT), have shown outstanding performance in effectively diagnosing pneumonia.
  • 926
  • 05 Jun 2023
Topic Review
Machine-Learning-Based Chemoinformatics
In modern drug discovery, the combination of chemoinformatics and quantitative structure–activity relationship (QSAR) modeling has emerged as a formidable alliance, enabling researchers to harness the vast potential of machine learning (ML) techniques for predictive molecular design and analysis.
  • 922
  • 18 Jul 2023
Topic Review
Mental Fatigue Detection Using Physiological Signals
Fatigue is a state characterized by both physical and mental exhaustion, resulting from prolonged activity, inadequate rest, or excessive cognitive demands. Physiological signals offer a valuable insight into the body’s internal state. Monitoring and interpreting these signals provide real-time information about an individual’s physical and mental condition, enabling early fatigue detection. 
  • 922
  • 10 Nov 2023
Topic Review
Detection-Based Vision-Language Understanding
Given a query language, a Detection-based Vision-Language Understanding (DVLU) system needs to respond based on the detected regions (i.e.,bounding boxes). With the significant advancement in object detection, DVLU has witnessed great improvements in recent years, such as Visual Question Answering (VQA) and Visual Grounding (VG).
  • 919
  • 09 Sep 2022
Topic Review
Infant Cry Signal Diagnostic System
Early diagnosis of medical conditions in infants is crucial for ensuring timely and effective treatment. However, infants are unable to verbalize their symptoms, making it difficult for healthcare professionals to accurately diagnose their conditions. Crying is often the only way for infants to communicate their needs and discomfort. The different combination of the fused features is then fed into multiple machine learning algorithms including random forest (RF), support vector machine (SVM), and deep neural network (DNN) models. The evaluation of the system using the accuracy, precision, recall, F1-score, confusion matrix, and receiver operating characteristic (ROC) curve, showed promising results for the early diagnosis of medical conditions in infants based on the crying signals only, where the system achieved the highest accuracy of 97.50% using the combination of the spectrogram, harmonic ratio (HR), and Gammatone frequency cepstral coefficients (GFCCs) through the deep learning process. 
  • 919
  • 10 Jul 2023
Topic Review
Artificial Intelligence and Sustainability
Artificial intelligence has undergone transformative advancements, reshaping diverse sectors such as healthcare, transport, agriculture, energy, and the media. Despite the enthusiasm surrounding AI’s potential, concerns persist about its potential negative impacts, including substantial energy consumption and ethical challenges. This Systematic Mapping Study (SMS) study accomplishes a comprehensive analysis of "AI Sustainability," integrating both the sustainability of AI and AI for sustainability across environmental, social, and economic dimensions. The field exhibits a dynamic landscape, maturing significantly since 2019 with a surge in publications and diverse contributions. The study reveals a balanced perspective, emphasizing both sustainability perspectives equally. Recent papers indicate a trend towards holistic studies, yet the economic dimension remains relatively underexplored. Future research is encouraged to delve into the economic dimension, align with the United Nations’ Sustainable Development Goals (SDGs), and address stakeholder influence, ensuring a sustainable and inclusive AI future.
  • 918
  • 05 Mar 2024
Topic Review
Bayes Factor and Prior Elicitation
The Bayes factor is a ratio of the marginal likelihood of two competing models. The marginal likelihood for a model class is a weighted average of the likelihood over all the parameter values represented by the prior distribution. Therefore, carefully choosing priors and conducting a prior sensitivity analysis play an essential role when using Bayes factors as a model selection tool. This section briefly discusses the prior distributions, prior elicitation, and prior sensitivity analysis.
  • 913
  • 24 Feb 2022
Topic Review
Public Transport COVID-19-Safe: New Barriers and Policies
The COVID-19 emergency forced cities worldwide to adopt measures to restrict travel and implement new urban public transport solutions. The discontinuity and reduction of services made users recognize public transport systems as contamination vectors, and the decrease in the number of passengers can already be seen in several places. Countermeasures that reduce the contact with other passengers—directly (limit the number of passengers in vehicles) or indirectly (operate with large vehicles)—and increase offers are possible solutions to make users feel safe while riding. 
  • 913
  • 28 Mar 2022
Topic Review
PCB Defect Based on Improved YOLOv7
The printed circuit board (PCB) holds immense importance in the electronic industry as a crucial component for the development of electronic products. PCBs are becoming increasingly integrated and smaller due to the excellent craftsmanship, precise wiring, and rapid development of integrated circuits.
  • 912
  • 11 May 2023
Topic Review
Human Action Recognition Methods
In the field of artificial intelligence, human action recognition is an important part of research in this area, making human interaction with the external environment possible. While human communication can be conveyed with words, facial expressions, written text, etc., the relationship between computers and sensors to understand human intentions and behaviour is now a popular area of research. As a result, more and more researchers are devoting their time and experience to the study of human action recognition.
  • 912
  • 28 Jul 2023
Topic Review
Gastrointestinal Tract Disorders
Globally, gastrointestinal (GI) tract diseases are on the rise. If left untreated, people may die from these diseases. Early discovery and categorization of these diseases can reduce the severity of the disease and save lives. Automated procedures are necessary, since manual detection and categorization are laborious, time-consuming, and prone to mistakes.
  • 911
  • 21 Aug 2023
Topic Review
Child Handwritten Arabic Character Recognition
Handwritten Arabic character recognition has received increasing research interest. However, as of yet, the majority of the existing handwriting recognition systems have only focused on adult handwriting. In contrast, there have not been many studies conducted on child handwriting, nor has it been regarded as a major research issue yet. Compared to adults’ handwriting, children’s handwriting is more challenging since it often has lower quality, higher variation, and larger distortions.
  • 910
  • 22 Aug 2023
Topic Review
Pattern Tracking Problem
A pattern is a collection of objects that are similar to each other, arranged in a way that is in contradiction of their natural arrangement. It can also be defined as the opposite of chaos, an entity, loosely defined, which one can assign a specific name. For pattern tracking, tracked objects are usually called patterns. Objects can be defined as something of interest for future analysis. For example, in images, tracking boats at sea, vehicles on the road, aircraft in the air, and people walking on the street can be considered monitoring for a certain purpose and thus tracking.
  • 909
  • 11 Jul 2023
Topic Review
The Robustness of Machine Learning in Network Security
Utilizing machine learning (ML) based methodologies for Network Intrusion Detection Systems (NIDSs) engenders valid concerns, primarily stemming from the inherent vulnerabilities of current ML models to various security threats.
  • 909
  • 08 Nov 2023
Topic Review
Facility Location Problem
The facility location problem (FLP) is a complex optimization problem that has been widely researched and applied in industry.
  • 908
  • 31 Oct 2023
Topic Review
Machine Learning for Breast Cancer Classification
Breast cancer is a prevalent disease that affects mostly women, and early diagnosis will expedite the treatment of this ailment. Recently, machine learning (ML) techniques have been employed in biomedical and informatics to help fight breast cancer. Extracting information from data to support the clinical diagnosis of breast cancer is a tedious and time-consuming task. The use of machine learning and feature extraction techniques has significantly changed the whole process of a breast cancer diagnosis.
  • 907
  • 08 Jul 2022
Topic Review
Computer Vision Technology for Physical Exercise Monitoring
Physical activity is movement of the body or part of the body to make the muscles more active and to lose the energy from the body. Regular physical activity in the daily routine is very important to maintain good physical and mental health. It can be performed at home, a rehabilitation center, gym, etc., with a regular monitoring system. How long and which physical activity is essential for specific people is very important to know because it depends on age, sex, time, people that have specific diseases, etc. Therefore, it is essential to monitor physical activity either at a physical activity center or even at home. Physiological parameter monitoring using contact sensor technology has been practiced for a long time.
  • 907
  • 06 Feb 2023
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