The use of heart rate variability, oxygen saturation, and anthropometric data with machine learning to predict the presence and severity of obstructive sleep apnea by Rafael Rodrigues dos Santos, Matheo Bellini Marumo, Alan Luiz Eckeli, Helio Cesar Salgado, Luiz Eduardo Virgílio Silva, Renato Tinós, Rubens Fazan

“…Heart rate variability (HRV) is a simple and non-invasive approach used as a probe to evaluate cardiac autonomic modulation, with a variety of newly developed indices lacking studies with OSA patients.ObjectivesWe aimed to evaluate numerous HRV indices, derived from linear but mainly nonlinear indices, combined or not with oxygen saturation indices, for detecting the presence and severity of OSA using machine learning models.MethodsECG waveforms were collected from 291 PSG recordings to calculate 34 HRV indices. …”
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Data stream mining techniques for real-time monitoring and control of smart power grids in Kenya: challenges and opportunities by Cornelius Mutuku Mulevu, George Onyango Okeyo, Joseph Muliaro Wafula

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Early Detection of Mental Health Disorders based on Sentiment using Stacking Method by Naufal Maldini, Danang Wahyu Utomo, Rahmadika Putri Tresyani

“…These results outperform the individual algorithms tested in the research. The findings demonstrate the significant potential of sentiment analysis powered by machine learning for early detection of mental health disorders, making it a valuable tool to enhance diagnosis and intervention in mental health care more effectively.…”
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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…Comparative experiments demonstrate that BMEPO exhibits stronger competitiveness in feature selection quality and classification performance compared to advanced feature selection algorithms. Finally, to further enhance the classification performance of defect prediction, a heterogeneous data stacking ensemble learning algorithm (HEDSE) based on feature selection is proposed. …”
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Comparative Analysis of Machine learning Methods to Identify signs of suspicious Transactions of Credit Institutions and Their Clients by Yu. M. Beketnova

“…The author concluded that the PCA-Based Anomaly Detection algorithm showed more accurate results compared to the One-Class Support Vector Machine algorithm. …”
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Multimodal Deep Learning for Android Malware Classification by James Arrowsmith, Teo Susnjak, Julian Jang-Jaccard

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Detect Multi Spoken Languages Using Bidirectional Long Short-Term Memory by Fawziya Ramo, Mohammed Kannah

“…Kurdish), which is called M2L_dataset is the source of data used in this paper.A Bidirectional Long Short-Term Memory (BiLSTM) algorithm applied in this paper for detection speaker language and the result was perfect, binary language detection had a test accuracy of 100%, and three languages detection had a test accuracy of 99.19%.…”
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TaxaCal: enhancing species-level profiling accuracy of 16S amplicon data by Qingrong Shen, Xiaoqian Fan, Yangyang Sun, Hao Gao, Xiaoquan Su

“…Results To address this issue, we present TaxaCal (Taxonomic Calibrator), a machine learning algorithm designed to calibrate species-level taxonomy profiles in 16S amplicon data using a two-tier correction strategy. …”
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Extraction of typical oyster pile columns in the Maowei Sea, Beibu Gulf, based on unmanned aerial vehicle laser point cloud orthophotos by Jinze Du, Jinze Du, Meiqin Huang, Zhenjun Kang, Zhenjun Kang, Zhenjun Kang, Yichao Tian, Yichao Tian, Yichao Tian, Jin Tao, Jin Tao, Qiang Zhang, Qiang Zhang, Yutong Xie, Yutong Xie, Yutong Xie, Jinying Mo, Jinying Mo, LiYan Huang, LiYan Huang, Yusheng Feng, Yusheng Feng

“…It utilizes multi-spectral image data from unmanned aerial vehicles (UAVs), light detection and ranging (LiDAR) point cloud technology, and deep learning algorithms to extract representative oyster pile columns in Maowei Sea within Beibu Gulf. …”
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An IoT-Enabled Wearable Device for Fetal Movement Detection Using Accelerometer and Gyroscope Sensors by Atcharawan Rattanasak, Talit Jumphoo, Wongsathon Pathonsuwan, Kasidit Kokkhunthod, Khwanjit Orkweha, Khomdet Phapatanaburi, Pattama Tongdee, Porntip Nimkuntod, Monthippa Uthansakul, Peerapong Uthansakul

“…This study evaluated ten signal extraction methods, six machine learning algorithms, and four feature selection techniques to enhance classification performance. …”
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A Novel Dataset for Polyp Segmentation and Detection Using a Vision-Language Model by Mahdiyeh Alilou, Javad Mozaffari, Abdollah Amirkhani, Shahriar B. Shokouhi, Alireza Khafaf

“…Colorectal Cancer (CRC) is caused by malignant polyps that develop on the colon walls, and early detection is crucial for prevention. Colonoscopy is one of the most effective methods for the detection of polyps, and deep learning algorithms can be utilized for colonoscopy image processing. …”
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Visual impairment prevention by early detection of diabetic retinopathy based on stacked auto-encoder by Shagufta Almas, Fazli Wahid, Sikandar Ali, Ahmed Alkhyyat, Kamran Ullah, Jawad Khan, Youngmoon Lee

“…Leveraging a comprehensive dataset from KAGGLE containing 35,126 retinal fundus images representing one healthy (normal) stage and four DR stages, our proposed model demonstrates superior accuracy compared to existing deep learning algorithms. Data augmentation techniques address class imbalance, while SAEs facilitate accurate classification through layer-wise unsupervised pre-training and supervised fine-tuning. …”
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Structural Health Monitoring by Fiber Optic Sensors by Alfredo Guemes, Luis Eduardo Mujica, Daniel del-Río-Velilla, Antonio Fernandez-Lopez

“…In this paper, we compare algorithms based on multivariate data analysis as well as data processing using neural networks, comparing their performance on a real structure.…”
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End-to-end deep fusion of hyperspectral imaging and computer vision techniques for rapid detection of wheat seed quality by Tingting Zhang, Jing Li, Jinpeng Tong, Yihu Song, Li Wang, Renye Wu, Xuan Wei, Yuanyuan Song, Rensen Zeng

“…Both conventional machine learning algorithms and deep convolutional neural networks (DCNN) were employed to develop discriminative models using independent datasets. …”
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A Hybrid Machine Learning Approach for Predicting Power Transformer Failures Using Internet of Things-Based Monitoring and Explainable Artificial Intelligence by Emrah Aslan, Yildirim Ozupak, Feyyaz Alpsalaz, Zakaria M. S. Elbarbary

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Enhancing the reliability and accuracy of wireless sensor networks using a deep learning and blockchain approach with DV-HOP algorithm for DDoS mitigation and node localization by Bhupinder Kaur, Deepak Prashar, Leo Mrsic, Ahmad Almogren, Ateeq Ur Rehman, Ayman Altameem, Seada Hussen

“…The remedy to these challenges in this work is a solution based on deep learning integrated with a blockchain-aided distance-vector hop (DV-HOP) localization algorithm for reliable and secure node localization. …”
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Balancing act: Tackling organized retail fraud on e-commerce platforms with imbalanced learning text models by Abed Mutemi, Fernando Bacao

“…The framework comprises four key components: text preprocessing, representation, knowledge extraction via machine learning algorithms, and model evaluation. By integrating data augmentation techniques, the framework enhances classifier performance in detecting fraud. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…Abstract In this paper, three Double Machine Learning (DML) models are proposed to enhance the accuracy of breast cancer detection using machine learning techniques using breast cancer detection dataset. …”
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RODA-OOD: Robust Domain Adaptation from Out-of-Distribution Data by Jaekyun Jeong, Mangyu Lee, Sunguk Yun, Keejun Han, Jungeun Kim

“…Domain adaptation aims to effectively learn from two domains with different distributions, solving labeling problems; however, traditional methods assume that the source and target data are in-distribution data that share the same labels. …”
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Comparison of SVM, K-NN, RF, CART, and GNB Algorithms for Water Bodies Detection Using Sentinel-2 Level-2a Imagery in Nakhon Pathom, Thailand by Ni Putu Nita Nathalia, Gede Andra Rizqy Wijaya, Kadek Yota Ernanda Aryanto, Ni Putu Novita Puspa Dewi, Putu Hendra Saputra, Ni Putu Karisma Dewi, Mellisa Damayanti, Kadek Losinanda Prawira

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