RunicNet: Leveraging CNNs With Attention Mechanisms for Cervical Cancer Cell Classification by Erin Beate Bjørkeli, Morteza Esmaeili

“…Integrating such AI systems into clinical workflows may enhance early detection and reduce diagnostic variability in Pap smear analysis.…”
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Sensing dynamic human activity zones using geo-tagged big data in Greater London, UK during the COVID-19 pandemic. by Tongxin Chen, Di Zhu, Tao Cheng, Xiaowei Gao, Huanfa Chen

“…Herein, we proposed an explainable analysis framework to explore the HAZ variations consisting of three parts, i.e., footfall detection, HAZs delineation and the identification of relationships between urban characteristics and HAZs. …”
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Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…Our study employs a wide range of ML algorithms, such as Logistic Regression (LR), Naive Bayes (NB), Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), K-Nearest Neibors (KNN), AdaBoost (AB), Gradient Boosting Machine (GBM), Light Gradient Boosting Machine (LGBM), CatBoost (CB), Linear Discriminant Analysis (LDA), and Artificial Neural Network (ANN) to assess the predictive performance of these algorithms in the context of heart disease detection. …”
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Self-Supervised Learning to Unveil Brain Dysfunctional Signatures in Brain Disorders: Methods and Applications by Ying Li, Yanwu Yang, Yuchu Chen, Chenfei Ye, Ting Ma

“…Leveraging the intrinsic organization of brain signals for comprehensive feature extraction, these models enable the analysis of critical neurofunctional features within a clinically relevant framework, overcoming challenges related to data heterogeneity and the scarcity of labeled data. …”
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mzGroupAnalyzer--predicting pathways and novel chemical structures from untargeted high-throughput metabolomics data. by Hannes Doerfler, Xiaoliang Sun, Lei Wang, Doris Engelmeier, David Lyon, Wolfram Weckwerth

“…At the same time it is impossible to handle the amount of data involved in a metabolomics analysis manually. Algorithms are therefore imperative to allow for automated m/z feature extraction and subsequent structure or pathway assignment. …”
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Evaluating Grayware Characteristics and Risks by Zhongqiang Chen, Zhanyan Liang, Yuan Zhang, Zhongrong Chen

“…Grayware encyclopedias collect known species to provide information for incident analysis, however, the lack of categorization and generalization capability renders them ineffective in the development of defense strategies against clustered strains. …”
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Quantifying Microplastic Leaching from Paper Cups: A Specklegram Image Analytical Approach by Mankuzhy Anilkumar Rithwiq, Puthuparambil Anju Abraham, Mohanachandran Nair Sindhu Swapna, Sankaranarayana Iyer Sankararaman

“…The study indicates contrast as the potential sensitive specklegram feature for microplastics detection and quantification.…”
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EXPRESSION OF THE TUMOR-ASSOCIATED PROTEINS IN THE OVARIAN CANCER by T. S. Bobrova, K. I. Zhordania, Yu. V. Chuyev

“…The further research using a larger amount of the clinical material and development of the more precise quantitative immunoenzyme analysis to measure TAP, is needed. It is possible that detection of TAP using MCA-1 and As may serve a basis for the creation of the test-system for the immunodiagnostics of the OC and determination of the stage of the tumor process.…”
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The current bovine leukemia spread situation in the Russian Federation by Donnik I.M., Petropavlovskiy M.V., Gulyukin M.I., Krivonos R.A., Chernykh O.Yu., Palagin S.Yu.

“…The main feature of the course of the disease in the region was a reduction in the average age of animals with an identified hematological stage of leukemia. …”
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RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…A novel application of RL for dynamic feature refinement and adjustment based on reward functions was employed to optimize the detection capabilities of the model. …”
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Automatic cattle identification system based on color point cloud using hybrid PointNet++ Siamese network by Pyae Phyo Kyaw, Pyke Tin, Masaru Aikawa, Ikuo Kobayashi, Thi Thi Zin

“…The proposed approach employs a hybrid detection method that first applies a 2D depth image detection model before converting the detected region into a color point cloud, allowing for robust feature extraction. …”
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IMM4HT:an identification method of malicious mirror website for high-speed network traffic by Lei ZHANG, Peng ZHANG, Wei SUN, Xingdong YANG, Lichao XING

“…Aiming at the problem that some information causing harm to the network environment was transmitted through the mirror website so as to bypass the detection,an identification method of malicious mirror website for high-speed network traffic was proposed.At first,fragmented data from the traffic was extracted,and the source code of the webpage was restored.Next,a standardized processing module was utilized to improve the accuracy.Additionally,the source code of the webpage was divided into blocks,and the hash value of each block was calculated by the simhash algorithm.Therefore,the simhash value of the webpage source codes was obtained,and the similarity between the webpage source codes was calculated by the Hamming distance.The page snapshot was then taken and SIFT feature points were extracted.The perceptual hash value was obtained by clustering analysis and mapping processing.Finally,the similarity of webpages was calculated by the perceptual hash values.Experiments under real traffic show that the accuracy of the method is 93.42%,the recall rate is 90.20%,the F value is 0.92,and the processing delay is 20 μs.Through the proposed method,malicious mirror website can be effectively detected in the high-speed network traffic environment.…”
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From Convolutional Networks to Vision Transformers: Evolution of Deep Learning in Agricultural Pest and Disease Identification by Mengyao Zhang, Chaofan Liu, Zihan Li, Baoquan Yin

“…Traditional pest and disease identification methods mainly rely on manual detection or traditional machine learning techniques, but they have obvious deficiencies in terms of their accuracy and generalisation ability. …”
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Improving the Routing Security in Wireless Sensor Networks using Neutrosophic Set and Machine Learning Models by Hanadi Ahmad Simmak, Ahmed A El-Douh, Tareef S Alkellezli, Rabih Sbera, Darin shafek, Ahmed Abdelhafeez

“…Our approach makes use of real-time feature analysis of simulated WSN routing data. We create a strong foundation for categorization. …”
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Integration of Multivariate Beta-based Hidden Markov Models and Support Vector Machines with Medical Applications by Narges Manouchehri, Nizar Bouguila

“…We apply our proposed model to medical applications, lung cancer detection, colonoscopy image, and colon tissue analysis. …”
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Railway safety monitoring algorithm based on distributed optical fiber vibration sensor by Fuyang CHEN, Bin JIANG, Yu SHA

“…Aiming at the monitoring problem of the human climbing behaviour existing along the railway,a railway safety detection algorithm based on distributed optical fiber vibration sensors was proposed by combining the distributed optical fiber sensing technology and signal analysis technology.The surrounding vibration was sensed and transmitted through the optical cables laid along the fence network of the railway,and then the Internet of things (IoT) connection between the railway and monitoring algorithm was built to realize the intelligent monitoring of the climbing behavior.In view of the complicated surrounding environment of the railway and more interference,the Hamming window and wavelet threshold denoising method were used to filter the signal of each frame to improve the signal-to-noise ratio of the vibration signal.In the selection of features,the power spectrum and short-time over-level rate of the signal were extracted from the time domain and frequency domain respectively as a joint feature to determine whether there was climbing or creeping behavior.Since that the climbing behavior was spatially continuous,the minimum alarm range was set to filter out alarms with a too small range,which improved the accuracy of the monitoring system.…”
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Enhanced Fault Localization in Multi-Terminal HVDC Systems Using Improved Gaussian Process Regression by Abha Pragati, Manohar Mishra, Pritam Bhowmik, Josep M. Guerrero, Debadatta Amaresh Gadanayak

“…Additionally, a detailed analysis on feature selection is conducted using the RRelief feature selection method. …”
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Rapid and Accurate Measurement of Major Soybean Components Using Near-Infrared Spectroscopy by Chenxiao Li, Jiatong Yu, Sheng Wang, Qinglong Zhao, Qian Song, Yanlei Xu

“…Comparative analysis revealed that the RF model consistently outperformed the others across most combinations. …”
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A Novel Framework for Quantum-Enhanced Federated Learning with Edge Computing for Advanced Pain Assessment Using ECG Signals via Continuous Wavelet Transform Images by Madankumar Balasubramani, Monisha Srinivasan, Wei-Horng Jean, Shou-Zen Fan, Jiann-Shing Shieh

“…The cornerstone of our system is a Quantum Convolutional Hybrid Neural Network (QCHNN) that harnesses quantum entanglement properties to enhance feature detection and classification robustness. This quantum-enhanced approach is seamlessly integrated into a federated learning framework, allowing distributed training across multiple healthcare facilities while preserving patient privacy through secure aggregation protocols. …”
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Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer by Ayan Chatterjee, Michael A. Riegler, K. Ganesh, Pål Halvorsen

“…Artificial intelligence (AI) research aims to use HRV data for accurate stress level classification, aiding early detection and well-being approaches. This study’s objective is to create a semantic model of HRV features in a knowledge graph and develop an accurate, reliable, explainable, and ethical AI model for predictive HRV analysis. …”
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