Genetic Artificial Hummingbird Algorithm-Support Vector Machine for Timely Power Theft Detection by Emmanuel Gbafore, Davies Rene Segera, Cosmas Raymond Mutugi Kiruki

“…The methodology entailed data preprocessing, data split into training, validation, and testing sets in an 80-10-10 ratio, z-score normalization, optimization, training, validation, testing, and computation of six evaluation metrics. …”
Get full text

Cell‐free epigenomes enhanced fragmentomics‐based model for early detection of lung cancer by Yadong Wang, Qiang Guo, Zhicheng Huang, Liyang Song, Fei Zhao, Tiantian Gu, Zhe Feng, Haibo Wang, Bowen Li, Daoyun Wang, Bin Zhou, Chao Guo, Yuan Xu, Yang Song, Zhibo Zheng, Zhongxing Bing, Haochen Li, Xiaoqing Yu, Ka Luk Fung, Heqing Xu, Jianhong Shi, Meng Chen, Shuai Hong, Haoxuan Jin, Shiyuan Tong, Sibo Zhu, Chen Zhu, Jinlei Song, Jing Liu, Shanqing Li, Hefei Li, Xueguang Sun, Naixin Liang

“…It also showed remarkable performance in detecting minimally invasive adenocarcinoma, with a sensitivity of 96.2%, highlighting its potential for early detection in clinical settings. …”
Get full text

Medical Image Watermarking Technique for Accurate Tamper Detection in ROI and Exact Recovery of ROI by R. Eswaraiah, E. Sreenivasa Reddy

“…Then, authentication data and information of ROI are embedded in border pixels. …”
Get full text

Cervical screening using HPV-DNA cytology in a low-income setting: an audit within a socio-economically deprived rural community in the Philippines by Elena Harty, Samantha Carr, Zelda Doyle, Charlotte Hespe

Get full text

Reinforcement Learning With Deep Features: A Dynamic Approach for Intrusion Detection in IoT Networks by Mohamad Khayat, Ezedin Barka, Mohamed Adel Serhani, Farag Sallabi, Khaled Shuaib, Heba M. Khater

“…Furthermore, an RL-based IDS (RL-IDS) that incorporates RNNs and autoencoders with a deep Q-network was proposed to enhance threat detection. Experimental outcomes emphasize the superiority of the method, obtaining 99.45% accuracy with 70% training data and 99.80% with 80%. …”
Get full text

Semantic segmentation of optical satellite images for the illegal construction detection using transfer learning by Yashasvi Mehta, Abdullah Baz, Shobhit K. Patel

“…Furthermore, it utilizes real-world data, enhancing its practical relevance, and incorporates IoT integration for real-time monitoring capabilities, setting it apart from existing studies.…”
Get full text

Detecting Positive and Negative Changes From SAR Images by an Evolutionary Multi-Objective Approach by Shuang Liang, Hao Li, Yun Zhu, Maoguo Gong

“…The experimental results on two simulated data sets and three real SAR data sets confirm the effectiveness of the proposed method.…”
Get full text

DKA-YOLO: Enhanced Small Object Detection via Dilation Kernel Aggregation Convolution Modules by Yicheng Qiu, Feng Sha, Li Niu

Get full text

Performance and Cost-Effectiveness of Computed Tomography Lung Cancer Screening Scenarios in a Population-Based Setting: A Microsimulation Modeling Analysis in Ontario, Canada. by Kevin Ten Haaf, Martin C Tammemägi, Susan J Bondy, Carlijn M van der Aalst, Sumei Gu, S Elizabeth McGregor, Garth Nicholas, Harry J de Koning, Lawrence F Paszat

“…Quality of life was not incorporated in the analyses, and assumptions for follow-up procedures were based on data from the NLST, which may not be generalizable to a population-based setting.…”
Get full text

Rotating Machinery Fault Detection Using Support Vector Machine via Feature Ranking by Harry Hoa Huynh, Cheol-Hong Min

“…Especially the use of machine learning algorithms has been very popular in all areas, including fault detection. This paper explores a case study of applying machine learning techniques and neural networks to detect ten different machinery fault conditions using publicly available data sets collected from a tachometer, two accelerometers, and a microphone. …”
Get full text

Performance of Apriori Algorithm for Detecting Drug–Drug Interactions from Spontaneous Reporting Systems by Yajie He, Jianping Sun, Xianming Tan

“…This study fills that gap through comprehensive simulation studies designed to mimic key features of SRS data. We show that latent confounding can substantially distort detection accuracy: for example, when using the reporting ratio (RR) as a secondary indicator, the area under the curve (AUC) for detecting main effects dropped by approximately 30% and for DDIs by about 15%, compared to settings without confounding. …”
Get full text

Detection and Theoretical Numerical Simulation of the Failure Depth of the Bottom Plate in Belt Pressure Mining by Xipeng Cui, Shuancheng Gu, Jinhua Li, Jiahao Wen, Kailei Zhao, Xinlei Liu

“…By using “ultrasonic detection method + stress monitoring inverse analysis method,” the measured data such as disturbance failure depth and distribution law of large mining width working face were obtained. …”
Get full text

Assessing ML classification algorithms and NLP techniques for depression detection: An experimental case study. by Giuliano Lorenzoni, Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

“…<h4>Purpose of the study</h4>This paper tackles such an assessment based on a case study that compares different ML classifiers, specifically in terms of data cleaning and pre-processing, feature selection, parameter setting, and model choices.…”
Get full text

Feasibility study of texture-based machine learning approach for early detection of neonatal jaundice by Nanthida Phattraprayoon, Teerapat Ungtrakul, Patiparn Kummanee, Sunisa Tavaen, Tanin Pirunnet, Todsaporn Fuangrod

“…Non-invasive approaches may be beneficial in settings with limited resources. This feasibility study explores a texture-based machine learning approach for early detection of neonatal jaundice. …”
Get full text

Multidimensional Comprehensive Evaluation Method for Sonar Detection Efficiency Based on Dynamic Spatiotemporal Interactions by Shizhe Wang, Weiyi Chen, Zongji Li, Xu Chen, Yanbing Su

“…Based on the above models, we construct the multidimensional sonar detection efficiency evaluation indicator system by implementing a confidence analysis, effective detection rate calculation, and a data volatility quantification analysis. …”
Get full text

ChromosomeNet: Deep Learning-Based Automated Chromosome Detection in Metaphase Cell Images by Chih-En Kuo, Jun-Zhou Li, Jenn-Jhy Tseng, Feng-Chu Lo, Ming-Jer Chen, Chien-Hsing Lu

“…Unlike previous studies that have reported simple chromosome images as identification results, we obtained a 99.5&#x0025; accuracy in the detection of difficult images. <italic>Conclusions:</italic> The volume of data we tested, even including difficult images, was much larger than those in the literature. …”
Get full text

Self-Supervised Multi-Task Learning for the Detection and Classification of RHD-Induced Valvular Pathology by Lorna Mugambi, Ciira wa Maina, Liesl Zühlke

Get full text

Cloud-based database framework of corrosion detecting and grading for temporary steel pipe supports by Ali Akbar, Goeun Choi, James Mugo Njoroge, Soonwook Kwon

“…On held-out test sets, the system demonstrated robust performance, achieving a mean average precision (mAP@[.5:.95]) of 0.71 for the precise detection of steel pipe supports. …”
Get full text

A transformer based multi task learning approach to multimodal hate speech detection by Prashant Kapil, Asif Ekbal

“…This line of research has been progressed in this work by building a multi-task learning-based multimodal system for detecting hateful memes by training four hateful meme data sets concurrently. …”
Get full text

Epileptic Seizure Detection Using Machine Learning: A Systematic Review and Meta-Analysis by Lin Bai, Gerhard Litscher, Xiaoning Li

“…This meta-analysis reviews the performance of ML models in seizure detection and analyzes factors such as the model type (deep learning vs. traditional ML), data preprocessing methods, and dataset types. …”
Get full text