Investigating the dynamics and uncertainties in portfolio optimization using the Fourier-Millen transform. by Muhammad Hilal Alkhudaydi, Aiedh Mrisi Alharthi

“…These are then compared with other algorithms, such as vector autoregression, in portfolio optimisation tests. …”
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Flow cytometry in the diagnosis of plasma cell tumors and assessment of minimal residual disease by L. Yu. Grivtsova, T. Yu. Mushkarina, V. V. Lunin, P. A. Zeynalova

“…Standardized flow cytometric protocols (the Euro-Flow conception) and algorithms for both the diagnosis of plasma cell tumors and the detection of minimal residual disease in plasma cell myeloma are described.…”
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Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…The optical time domain reflectometer (OTDR) curve features of communication fibers exhibit subtle differences among their normal, subhealthy, and faulty operating states, making it challenging for existing machine learning-based fault diagnosis algorithms to extract these minute features. …”
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Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data by Ailing Zhang, Haobo Zhang

“…The best-performing model achieved an accuracy of 0.85 and an AUC of 0.80, highlighting the potential of combining sMRI and rs-fMRI features with ML for early depression detection while revealing the potential of overfitting in small-sample and high-dimensional settings. …”
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Comparison of Machine Learning Models for Classification of Breast Cancer Risk Based on Clinical Data by Haniyeh Rafiepoor, Alireza Ghorbankhanloo, Kazem Zendehdel, Zahra Zangeneh Madar, Sepideh Hajivalizadeh, Zeinab Hasani, Ali Sarmadi, Behzad Amanpour‐Gharaei, Mohammad Amin Barati, Mozafar Saadat, Seyed‐Ali Sadegh‐Zadeh, Saeid Amanpour

“…Ten classification algorithms were applied to the dataset. The accuracy, sensitivity, precision, and feature importance in the machine learning algorithms were assessed and compared to previous studies for evaluation. …”
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Predicting the Attraction and Retention of Customers in Sports Pools in Isfahan City Using a Decision Tree: Presenting a Data Mining-Based Model by Seyed Masoud Mirsaeidi, Davood Nasr Esfahani

“…Furthermore, the combined GOA-DT algorithm selected only 7 out of the 22 features that were effective in detecting customer churn, whereas the SA-DT algorithm led to the selection of 8 features. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Developing a non-invasive, accurate prediction model is clinically significant for early MetS detection and prevention. Objective To develop a non-invasive prediction model for MetS by integrating body roundness index (BRI), gender, age, height, and waist circumference with machine learning algorithms, and to validate its generalizability across different ethnic groups. …”
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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

“…The dissimilarities between the top features set of the general and segmented models suggest that segmented models are useful in providing a better understanding of fraud occurrence.…”
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CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…Convolutional Neural Networks (CNNs) are a class of deep learning algorithms most commonly applied. They are particularly powerful for tasks involving data recognition, classification, and analysis due to their ability to automatically and adaptively learn spatial hierarchies of features. …”
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High-Performance Multi-Object Tracking for Autonomous Driving in Urban Scenarios With Heterogeneous Embedded Boards by Alessio Medaglini, Biagio Peccerillo, Sandro Bartolini

“…The main objective is to exploit the high-performance capabilities of NVIDIA heterogeneous embedded platforms, which are not automatically compatible with the peculiar features of these algorithms. We propose and discuss some non-trivial software design choices and implementation strategies that are needed to match the specific computational and memory access needs of MOT strategies, and the architectural opportunities of NVIDIA embedded GPGPU systems. …”
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Advancing ECG Signal Classification With a Fuzzy Classifier Approach by Jan Rabcan, Vitaly Levashenko, Elena Zaitseva, Miroslav Kvassay

“…The analysis of ECG signals plays an important role in healthcare, particularly for the detection of heart conditions such as arrhythmia, coronary artery disease, or heart attack. …”
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End-to-end multiple object tracking in high-resolution optical sensors of drones with transformer models by Yubin Yuan, Yiquan Wu, Langyue Zhao, Yuqi Liu, Yaxuan Pang

“…Conventional approaches rely heavily on manual feature engineering and intricate algorithms, which can further limit efficiency. …”
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Artificial Intelligence in Primary Malignant Bone Tumor Imaging: A Narrative Review by Platon S. Papageorgiou, Rafail Christodoulou, Panagiotis Korfiatis, Dimitra P. Papagelopoulos, Olympia Papakonstantinou, Nancy Pham, Amanda Woodward, Panayiotis J. Papagelopoulos

“…Through machine learning and deep learning techniques, AI leverages computational algorithms and large datasets to enhance medical imaging interpretation and support clinical decision-making. …”
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SOME ASPECTS OF SCANNING LASER OPHTHALMOSCOPY IN THE DIAGNOSTICS OF OPHTHALMOPATHOLOGY by S. A. Kochergin, S. Yu. Slonimsky, A. A. Ovsyanko, O. D. Gupalo

“…However, for the earliest detection of the smallest pathological changes, data of the normal ocular fundus state using a scanning laser ophthalmoscope is necessary. …”
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ULOTrack: Underwater Long-Term Object Tracker for Marine Organism Capture by Ju He, Yang Yu, Hongyu Wei, Hu Xu

“…ULOTrack is based on a performance discrimination and re-detection framework and constitutes three modules: (1) an object tracker, which can extract multi-feature information of the underwater target; (2) a multi-layer tracking performance discriminator, which serves the purpose of evaluating the stability of the current tracking state, thereby reducing potential model drift; and (3) lightweight detection, which can predict the candidate boxes to relocate the lost tracked underwater object. …”
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Predicting cancer risk using machine learning on lifestyle and genetic data by Mohamed Abdelmoaty Ahmed, Ahmed AbdelMoety, Asmaa Mohamed Ahmed Soliman

“…Abstract Cancer remains one of the leading causes of mortality worldwide, where early detection significantly improves patient outcomes and reduces treatment burden. …”
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Novel machine learning-driven comparative analysis of CSP, STFT, and CSP-STFT fusion for EEG data classification across multiple meditation and non-meditation sessions in BCI pipel... by Nalinda D. Liyanagedera, Corinne A. Bareham, Heather Kempton, Hans W. Guesgen

“…While testing different feature extraction algorithms, a common neural network structure was used as the classification algorithm to compare the performance of the feature extraction algorithms. …”
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Rapid acquisition and surface defects recognition based on panoramic image of small-section hydraulic tunnel by Haoyu Wang, Jichen Xie, Jinyang Fu, Cong Zhang, Dingping Chen, Zhiheng Zhu, Xuesen Zhang

“…The algorithm introduces DenseNet to optimize the backbone feature extraction network and incorporates an efficient channel attention ECA module to make a better extraction of features of defects. …”
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DA-YOLOv7: A Deep Learning-Driven High-Performance Underwater Sonar Image Target Recognition Model by Zhe Chen, Guohao Xie, Xiaofang Deng, Jie Peng, Hongbing Qiu

“…The experimental results on the UATD, the Underwater Optical Target Detection Intelligent Algorithm Competition 2021 Dataset (URPC), and SCTD datasets show that DA-YOLOV7 exhibits outstanding performance, with mAP@0.5 scores reaching 89.4%, 89.9%, and 99.15%, respectively. …”
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Automated Recognition of Conidia of Nematode-Trapping Fungi Based on Improved YOLOv8 by Enming Zhao, Hongyi Zhao, Guangyu Liu, Jianbo Jiang, Fa Zhang, Jilei Zhang, Chuang Luo, Bobo Chen, Xiaoyan Yang

“…This adjustment significantly optimizes the detection and differentiation of limited features and small-sized conidia among aggregated samples. …”
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