Ecotoxicity prediction of chemical compounds using machine learning and different molecular structure representations by Michał Marek, Rafał Kurczab

“…This paper presents the development of models for predicting chemical ecotoxicity (HC50) based on machine learning algorithms and different molecular representations. …”
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Detection and Analysis of Malicious Software Using Machine Learning Models by Selman Hızal, Ahmet Öztürk

“…In this study, we evaluate the performance of ML algorithms for obfuscated malware detection using the CIC-MalMem-2022 dataset. …”
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Ensembles of spectral-spatial convolutional neural network models for classifying soil types in hyperspectral images by N.A. Firsov, V.V. Podlipnov, N.A. Ivliev, D.D. Ryskova, A.V. Pirogov, A.A. Muzyka, A.R. Makarov, V.E. Lobanov, V.I. Platonov, A.N. Babichev, V.A. Monastyrskiy, V.I. Olgarenko, D.P. Nikolaev, R.V. Skidanov, A.V. Nikonorov, N.L. Kazanskiy, V.A. Soyfer

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Heart Rate Detection and Classification from Speech Spectral Features Using Machine Learning by Mohammed USMAN, Mohammed ZUBAIR, Zeeshan AHMAD, Monji ZAIDI, Thafasal IJYAS, Muneer PARAYANGAT, Mohd WAJID, Mohammad SHIBLEE, Syed Jaffar ALI

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A Unified Approach to Image Recognition and Cryptography via Flexible Weak Inverse Property Quasigroups by Mohammad Mazyad Hazzazi, Muhammad Nadeem, Muhammad Kamran, Muhammad Arshad, Samuel Asefa Fufa

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Heavy metal biomarkers and their impact on hearing loss risk: a machine learning framework analysis by Ali Nabavi, Mohammad Kashkooli, Sara Sadat Nabavizadeh, Farimah Safari

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A Spatiotemporal Feature Extraction Technique Using Superlet-CNN Fusion for Improved Motor Imagery Classification by Neha Sharma, Manoj Sharma, Amit Singhal, Nuzhat Fatema, Vinay Kumar Jadoun, Hasmat Malik, Asyraf Afthanorhan

“…Through an intensive comparison with present algorithms assessed in variety of performance evaluating metrics the present study emphasize the exceptional ability of proposed approach to accurately classify the different MI categories from the EEG signals and which is a great contribution to the field of BCI research field.…”
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Instagram and #Wellness: Uncovering Gender and Body Patterns by Ana Marta M. Flores, Rita Sepúlveda

“…This becomes particularly meaningful when these expressions are linked to gender. Our research explores how wellness and gender are depicted in popular Instagram posts. …”
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A deep learning approach for blood glucose monitoring and hypoglycemia prediction in glycogen storage disease by Ji Seung Ryu, Jang Hoon Ru, Yunkoo Kang, Sejung Yang

“…However, there is a lack of research focusing specifically on patients with GSD. …”
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Multi-label software requirement smells classification using deep learning by Ashagrew Liyih Alem, Ketema Keflie Gebretsadik, Shegaw Anagaw Mengistie, Muluye Fentie Admas

“…Therefore, Bi-LSTM achieved a greater F1-score macro average than the other algorithms.…”
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Landslide vulnerability mapping using GIS-based statistical model for sustainable ecosystem management in the Himalayan region of Teesta River basin, India by Subodh Chandra Pal, Tanmoy Biswas, Sumit Ghorai, Chaitanya Baliram Pande, Aznarul Islam, Abu Reza Md. Towfiqul Islam, Edris Alam

“…The landslide inventory data are subdivided into training data sets (70%) for applying algorithms in models and testing data sets (30%) for testing model accuracy. …”
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Characterization of Hazelnut Trees in Open Field Through High-Resolution UAV-Based Imagery and Vegetation Indices by Maurizio Morisio, Emanuela Noris, Chiara Pagliarani, Stefano Pavone, Amedeo Moine, José Doumet, Luca Ardito

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Enhancing Machine Learning Models Through PCA, SMOTE-ENN, and Stochastic Weighted Averaging by Youngjin Han, Inwhee Joe

“…Predicting survival outcomes in critical accidents has been a focal point in machine learning research. This study addresses several limitations of existing methods, including insufficient management of data imbalance, lack of emphasis on hyperparameter tuning, and proneness to overfitting. …”
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Machine learning predictive performance in road accident severity: A case study from Thailand by Ittirit Mohamad, Sajjakaj JomnonKwao, Vatanavongs Ratanavaraha

“…This study evaluates the predictive performance of multiple supervised machine learning algorithms in classifying accident severity, addressing the gap in prior research that lacks a comparative analysis of multiple models trained on large-scale crash data. …”
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Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model by Changjiang Liang, Changjiang Liang, Dandan Liu, Dandan Liu, Weiyi Ge, Weiyi Ge, Wenzhong Huang, Wenzhong Huang, Yubin Lan, Yubin Lan, Yubin Lan, Yongbing Long, Yongbing Long, Yongbing Long, Yongbing Long

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SUDDEN DEATH IN HYPERTROPHIC CARDIOMYOPATHY: SEARCH FOR NEW RISK FACTORS by N. S. Krylova, E. A. Kovalevskaya, N. G. Poteshkina, A. E. Demkina, F. M. Khashieva

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Evaluation of Feature Transformation and Machine Learning Models on Early Detection of Diabetes Mellitus by Ahmed Ali Linkon, Inshad Rahman Noman, Md Rashedul Islam, Joy Chakra Bortty, Kanchon Kumar Bishnu, Araf Islam, Rakibul Hasan, Masuk Abdullah

“…To comprehensively evaluate the effectiveness of these preprocessing techniques, we experimented with twelve different ML models, including both traditional algorithms and ensemble methods. A publicly available dataset has been used for this research, containing 768 samples and 8 features. …”
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Software Defect Prediction Using Deep Q-Learning Network-Based Feature Extraction by Qinhe Zhang, Jiachen Zhang, Tie Feng, Jialang Xue, Xinxin Zhu, Ningyang Zhu, Zhiheng Li

“…Sensitive analysis experiments show that binary classification algorithms based on SDP approaches using the DQN-based feature extraction outperform those without using it. …”
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A novel feature extractor based on constrained cross network for detecting sleep state by Chenlei Tian, Fei Song

“…Most existing methods that utilize wrist-worn devices data for detection rely on heuristic algorithms or traditional machine learning, which suffer from low classification efficiency and insufficient accuracy. …”
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NLP for computational insights into nutritional impacts on colorectal cancer care by Shengnan Gong, Xiaohong Jin, Yujie Guo, Jie Yu

“…The dataset also contained an imbalanced binary CRC outcome, which is rebalanced utilizing the random oversampling. …”
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