Prediction of Early Diagnosis in Ovarian Cancer Patients Using Machine Learning Approaches with Boruta and Advanced Feature Selection by Tuğçe Öznacar, Tunç Güler

“…Objectives: Ovarian cancer continues to be one of the most prevalent gynecological cancers diagnosed. Early detection is highly critical for increasing survival chances. …”
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Applications of Machine Learning in Human Factors and Ergonomics: A Comprehensive Review of Research From the Past Decade by Erman Cakit, Waldemar Karwowski

“…This review not only benchmarks algorithmic performance but also identifies research gaps and provides guidance for future machine-learning applications in human factors, ergonomics, and human-centered systems design.…”
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Adversarial attacks dataset for low light image enhancementMendeley Data by Axel Martinez, Matthieu Olague, Gustavo Olague, Emilio Hernandez, Julio Cesar Lopez-Arredondo

“…Enhancement tasks for low-light images are an open problem whose solutions can impact downstream tasks in fields like surveillance, medicine, autonomous driving, or object detection. As a result, the necessity to create algorithms that can withstand harmful and subtle disturbances has garnered interest, as both humans and machines can significantly influence how programs perform. …”
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Edge-aware multisensor brain image fusion via guided filtering in Laplacian domain by Shweta Sharma, Shalli Rani, Ayush Dogra, Mohammed Wasim Bhatt

“…This work presents a new edge-aware multi-sensor brain image fusion technique using Laplacian energy maps for edge preservation, guided filtering for image decomposition, and adaptive fusion algorithms for integration of base and detail layers. …”
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Enhanced Underwater Image Restoration and Clarity Optimization Using Advanced Digital Image Processing Techniques by Gopirajan Punniyakotti Varadharajan, Pradeep T., Charan R.

“…Underwater image enhancement is essential in various tasks such as underwater detection, surveillance, and exploration given that the images these activities produce usually have poor quality because of the influence of some factors (low contrast, noise, and color distortion caused by light absorption and scattering). …”
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SEAP: squeeze-and-excitation attention guided pruning for lightweight steganalysis networks by Qiushi Li, Shenghai Luo, Shunquan Tan, Zhenjun Li

“…Abstract In recent years, the increasing computational and storage demands of deep steganalysis models have drawn attention to lightweight architectures. While pruning algorithms for image steganalysis networks have been proposed, they often do not apply to networks equipped with mobile inverted bottleneck (MBConv) structures, such as EfficientNet. …”
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The diagnostic performance evaluation of the SD BIOLINE HIV/syphilis Duo rapid test in southern Ethiopia: a cross-sectional study by Techalew Shimelis, Endale Tadesse

“…The performance of the test to detect HIV was evaluated using 400 sera (200 HIV positives and 200 HIV negatives). …”
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Experimental analysis of polymorphic microsatellite loci in Cladocera: mixed breeding strategy and population dynamics by Poroshina A.A., Sherbakov D.Yu.

“…We use primers predicted by an algorithm for DNA amplification from Daph- nia samples and capillary electrophoresis to detect polymorphic loci. …”
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False-positive tolerant model misconduct mitigation in distributed federated learning on electronic health record data across clinical institutions by Maxim Edelson, Anh Pham, Tsung-Ting Kuo

“…Future work can apply our methodology to more sophisticated machine learning algorithms or scale the experiments in a large-scale learning scenario with more participating sites and larger sample sizes.…”
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Artificial Intelligence-Assisted Selection Strategies in Sheep: Linking Reproductive Traits with Behavioral Indicators by Ebru Emsen, Muzeyyen Kutluca Korkmaz, Bahadir Baran Odevci

“…Recent advancements in artificial intelligence (AI), including video tracking, wearable sensors, and machine learning (ML) algorithms, offer new opportunities to identify behavior-based indicators linked to key reproductive traits such as estrus, lambing, and maternal behavior. …”
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Enhancing DDoS Attack Classification through SDN and Machine Learning: A Feature Ranking Analysis by Aymen AlAwadi, Kawthar Rasoul ALesawi

“…Due to their high accuracy and lower complexity, KNN and NB outperform ML algorithms in this study…”
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Systematic Security Analysis of Sensors and Controls in PV Inverters: Threat Validation and Countermeasures by Fengchen Yang, Kaikai Pan, Chen Yan, Xiaoyu Ji, Wenyuan Xu

“…These vulnerabilities can lead to incorrect sensor readings, disrupting control algorithms. We propose an IEMI attack that results in three potential outcomes: Denial of Service (DoS), physical damage to the inverter, and power output reduction. …”
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Implementation of automation tools for test analysis in the Radiotherapy Quality Assurance Programs by João Guilherme Rivera Santiago, Laura Furnari, Marcus Vinicius Saad de Paula Rodrigues, Victor Augusto Bertotti Ribeiro

“…The findings highlight the importance of conducting studies during the implementation phase of such tools to understand the algorithms used and establish appropriate usage and control measures for routine practice. …”
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Security-centric node identification in complex networks by Lanying Liu, Ning Du, Duyong Sheng

“…To achieve this, we develop a mathematical model to compute SC, introduce efficient algorithms for identifying critical nodes, and implement an incremental update mechanism to enhance adaptability in real-time networks. …”
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PreSCAN: A Comprehensive Review of Pre-Silicon Physical Side-Channel Vulnerability Assessment Methodologies by Md Kawser Bepary, Tao Zhang, Farimah Farahmandi, Mark Tehranipoor

“…We explore the intricacies of cryptographic algorithms, various side-channel attacks, and the latest mitigation techniques. …”
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Neural networks for the analysis of traced particles in kinetic plasma simulations by G. Torralba Paz, A. Bohdan, J. Niemiec

“…We perform classification, regression, and anomaly detection algorithms on the dataset by using a convolutional neural network, a multi-layer perceptron, and an autoencoder. …”
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Source reconstruction accuracy of MEG and EEG Bayesian inversion approaches. by Paolo Belardinelli, Erick Ortiz, Gareth Barnes, Uta Noppeney, Hubert Preissl

“…Still, no correct network detection is possible without reliable source localization. …”
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Machine Learning for Chinese Corporate Fraud Prediction: Segmented Models Based on Optimal Training Windows by Chang Chuan Goh, Yue Yang, Anthony Bellotti, Xiuping Hua

“…We propose a comprehensive and practical framework for Chinese corporate fraud prediction which incorporates classifiers, class imbalance, population drift, segmented models, and model evaluation using machine learning algorithms. Based on a three-stage experiment, we first find that the random forest classifier has the best performance in predicting corporate fraud among 17 machine learning models. …”
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Developing a Non-Invasive Intelligent System for Blood Glucose Level Estimation Using Reflective Optical Sensors by Mihaela MARIN, Teodora Alexandra DOBRIN, Florin Bogdan MARIN

“…The TCRT5000 sensor detects light reflectivity changes caused by blood flow, indirectly estimating glucose levels without the discomfort of invasive techniques. …”
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Beyond the Leak: Analyzing the Real-World Exploitation of Stolen Credentials Using Honeypots by Matej Rabzelj, Urban Sedlar

“…We examine generative algorithms (e.g., keywalk patterns, hashcat rules), finding they are widely used by users but not attackers—unless included in wordlists. …”
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