The importance of understanding how feature engineering contributes to breast cancer metastasis analytics is growing as artificial intelligence (AI) technologies rapidly transform the field of precision oncology. This systematic review collated, them...
Acute Myocardial Infarction (AMI), a common disease that can have serious consequences, occurs when myocardial blood flow stops due to occlusion of the coronary artery. Early and accurate prediction of AMI is critical for rapid prognosis and improved...
In the field of rehabilitation, the electromyography (EMG) signal plays an important role in interpreting patients’ intentions and physical conditions. Nevertheless, utilizing merely the EMG signal suffers from difficulty in recognizing slight...
A general issue in climate science is the handling of big data and running complex and computationally heavy simulations. In this paper, we explore the potential of using machine learning (ML) to spare computational time and optimize data usage. The...
Video games, especially competitive ones such as Dota 2, have gained great relevance both as entertainment and in e-sports, where predicting the outcome of games can offer significant strategic advantages. In this context, machine learning (ML) is pr...
This study compares the effects of pre-processing multiple polymers together to form a single-phase polymer alloy prior to amorphous solid dispersion formulation. KinetiSol compounding was used to pre-process a 1:1 (w/w) ratio of hypromellose acetate...
Background: Recent studies have shown that hyperspectral imaging (HSI) combined with neural networks can detect colorectal cancer. Usually, different pre-processing techniques (e.g., wavelength selection and scaling, smoothing, denoising) are analyze...
The analysis of reliable studies helps to identify the credibility, scope, and limitations of various techniques for condition monitoring of a wind turbine (WT) system’s design and development to reduce the operation and maintenance (O&M) c...
Anthropogenic activities and natural climate changes are the central driving forces of global ecosystems and agriculture changes. Climate changes, such as rainfall and temperature changes, have had the greatest impact on different types of plant prod...
Skin cancer is caused by aberrant cells that proliferate uncontrollably after unrepaired DNA damage results in mutations in the epidermis. The majority of skin cancer is caused by high UV exposure from the sun, tanning beds, or sunlamps. Due to socio...
Recent advances in event-based cameras have led to significant developments in robotics, particularly in visual simultaneous localization and mapping (VSLAM) applications. This technique enables real-time camera motion estimation and simultaneous env...
Monitoring civil infrastructure is increasingly critical due to aging assets, urban expansion, and the need for early detection of structural instabilities. Interferometric Synthetic Aperture Radar (InSAR) offers high-resolution, all-weather surface...
Dementia-related disorders, particularly Alzheimer’s disease (AD), represent a growing global health challenge, increasing the need for early and reliable detection. Electroencephalography (EEG), a non-invasive and cost-effective neurophysiolog...
In the evolving landscape of targeted marketing, integrating deep learning (DL) and explainable AI (XAI) offers a promising avenue for enhanced customer segmentation. This paper introduces a groundbreaking approach, DeepLimeSeg, which synergizes DL m...
Coarse Grain Spectral Analysis (CGSA) can explain the possible multiscaling nature of the thousands of low-amplitude peaks observed in the power spectra of some pulsating stars. Space-based observations allowed for the scientific community to find th...
In the Information Age, the widespread usage of blackbox algorithms makes it difficult to understand how data is used. The practice of sensor fusion to achieve results is widespread, as there are many tools to further improve the robustness and perfo...
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 ar...
The inclusion of seaweeds in daily-consumption food is a worthy-of-attention challenge due to their high nutritional value and potential health benefits. In this way, their composition, organoleptic profile, and toxicity must be assessed. This work f...
The Urban Heat Island (UHI) phenomenon constitutes one of the most significant climate-related challenges for contemporary cities, intensifying thermal stress, energy demand, and social vulnerability. This study proposes a methodological framework th...
Accurate identification of the hepatopancreas is essential for prawn quality assessment and automated seafood processing. This study presents an explainable deep learning framework for the binary classification of prawn images into “with hepato...
Background: The high costs, long development timelines, and low clinical success rates in oncology highlight an urgent need for reliable computational strategies for drug repositioning. Current machine learning approaches often integrate heterogeneou...
Artificial intelligence applications in mental health diagnosis face persistent challenges related to interpretability, trust, and the integrity of results. This study presents a trust-aware explainable deep learning framework that combines systemati...
Background and Objectives: Breast cancer remains a leading cause of cancer-related morbidity and mortality worldwide, and robust, interpretable artificial intelligence (AI) pipelines are increasingly being explored to support mammography-based detect...
As reconstruction and redevelopment accelerate, the generation of construction waste increases, and construction waste treatment technology is being developed accordingly, especially using artificial intelligence (AI). The majority of AI research pro...
For the purpose of improving the accuracy of underwater acoustic target recognition with only a small number of labeled data, we proposed a novel recognition method, including 4 steps: pre-processing, pre-training, fine-tuning and recognition. The 4...
Survey data play a crucial role in various research fields, including economics, education, and healthcare, by providing insights into human behavior and opinions. However, item non-response, where respondents fail to answer specific questions, prese...
Robust plant disease detection in real-world agricultural environments remains challenging due to dynamic environmental conditions. Accurate and reliable disease identification is essential for precision agriculture and effective crop management. Alt...
Excitation–emission matrix (EEM) fluorescence spectroscopy, when combined with machine learning algorithms, has emerged as a highly promising tool for non-invasive biomedical diagnosis, demonstrating significant potential across various applica...
Fourier-transform infrared (FT-IR) spectroscopy provides rapid, accessible, and chemically informative molecular fingerprints, but quantitative analysis of complex samples is often hindered by band overlap, baseline variation, matrix effects, and non...
Student dropout in Higher Education remains a persistent challenge with significant academic, social and economic consequences. Predictive analytics using traditional Machine Learning and Deep Learning have been increasingly explored to support early...
The reinforced concrete (RC) member’s shear strength estimation has been experimentally studied in most cases due to its nonlinear behavior. Many empirical equations have been derived from the experimental data; however, even those adopted in the con...
Breast cancer is a serious medical condition that requires early detection for successful treatment. Mammography is a commonly used imaging technique for breast cancer screening, but its analysis can be time-consuming and subjective. This study explo...
Liquid crystal display (LCD) is a display device based on liquid crystal electro-optic effect, and LCDs have gradually appeared and have become an indispensable part of people’s lives. In the development of LCD technology, the detection of Mura...
The environmental impact of industrial processes, especially regarding CO2 emissions, requires innovative tools to monitor and optimize resource consumption. This study presents a data-driven approach for a carded nonwoven production line, aiming to...
Energy efficiency in industrial environments is subject to regulatory and economic constraints. Automated intralogistics systems, such as High Rack Storage Systems (HRSS), exhibit complex and dynamic energy patterns. This paper proposes an unsupervis...
The nasal cavity three-dimensional structure reconstruction is significant for the diagnosis and treatment of nasal and nasopharynx diseases. Currently, most systems for nasal cavity three-dimensional structure reconstruction are based on a long-sour...
Saliva is a largely unexplored liquid biopsy that can be readily obtained noninvasively. Not dissimilar to blood plasma or serum, it contains a vast array of bioconstituents that may be associated with the absence or presence of a disease condition....
This study proposes a deep learning-based framework for the automated classification of photovoltaic solar cells as defective or normal using electroluminescence (EL) imaging. A balanced dataset containing 20,400 EL images, comprising 10,200 defectiv...
Neuromuscular dysfunction during the sit-to-walk (STW) task in Parkinson’s disease (PD) remains poorly understood. We aimed to analyze surface electromyography (sEMG) signals across STW phases using explainable machine learning (ML) and deep learning...
12 December 2022
Feature selection is a common step in data preprocessing that precedes machine learning to reduce data space and the computational cost of processing or obtaining the data. Filtering out uninformative variables is also important for knowledge discove...
Coronavirus disease 2019 (COVID-19) has resulted in approximately 5 million deaths around the world with unprecedented consequences in people’s daily routines and in the global economy. Despite vast increases in time and money spent on COVID-19...
Parkinson’s Disease (PD) is a complex neurodegenerative disorder characterized by a spectrum of motor and non-motor symptoms, prominently featuring the freezing of gait (FOG), which significantly impairs patients’ quality of life. Despite...
Accurate interpretation of chest radiographs is central to the early diagnosis and management of pulmonary disorders. This study introduces an explainable deep learning framework that integrates biomedical signal fidelity analysis with transfer learn...
Social media and mobile devices, commonly referred to as socimedevices, have become integral to students’ daily lives, influencing both their academic performance and overall well-being. Depending on usage patterns, these technologies can posit...
Water quality monitoring is essential for environmental protection, public health, and sustainable water resource management. However, many important water quality parameters remain difficult or expensive to measure continuously using conventional se...
Although numerous studies have developed promising diagnostic algorithms, many have yet to be translated into workflow-integrated tools. Gliomas represent a substantial proportion of primary brain tumors, and their preoperative differentiation by tum...
Network anomaly detection systems (NADSs) play a significant role in every network defense system as they detect and prevent malicious activities. Therefore, this paper offers an exhaustive overview of different aspects of anomaly-based network intru...
Early detection of colorectal cancer can significantly facilitate clinicians’ decision-making and reduce their workload. This can be achieved using automatic systems with endoscopic and histological images. Recently, the success of deep learnin...
This study aims to introduce Bayesian Knowledge Tracing (BKT), a probabilistic model used in educational data mining to estimate learners’ knowledge states over time. It also provides a practical guide to estimating BKT models using the pyBKT l...
Metabolomics has emerged as a powerful analytical approach for comprehensive chemical profiling in complex biological and environmental systems. The increasing volume, dimensionality, and complexity of metabolomics data have driven the adoption of ma...
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