Drug repositioning framework using embedding drug-protein-disease similarities with graph convolution network and ensemble learning by Hanaa Torkey, Heba El-Behery, Abdel-Fattah Atti, Nawal El-Fishawy

“…The approach extracts embedding feature vectors of drugs and targets from a heterogeneous multi-source network to predict unknown drug-target interactions (DTIs). We employ a Meta-Path instance that has extensive drug and target characteristic data. …”
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Innovative approaches to standardisation in forest commodity science: Trends and prospects by O. Sytnyk, I. Kimeichuk

“…The study revealed modern innovative approaches to standardisation in forest commodity science, among which digital technologies, blockchain systems, artificial intelligence algorithms and remote monitoring tools played a key role. …”
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Improving Diagnostic Performance for Head and Neck Tumors with Simple Diffusion Kurtosis Imaging and Machine Learning Bi-Parameter Analysis by Suzuka Yoshida, Masahiro Kuroda, Yoshihide Nakamura, Yuka Fukumura, Yuki Nakamitsu, Wlla E. Al-Hammad, Kazuhiro Kuroda, Yudai Shimizu, Yoshinori Tanabe, Masataka Oita, Irfan Sugianto, Majd Barham, Nouha Tekiki, Nurul N. Kamaruddin, Miki Hisatomi, Yoshinobu Yanagi, Junichi Asaumi

“…MK and ADC values were extracted from pixels within the tumor area and used as explanatory variables. Five ML algorithms were used to create models for the prediction of tumor status (benign or malignant), which were evaluated through ROC analysis. …”
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Integrating machine learning and sentiment analysis in movie recommendation systems by Amany M. Sarhan, Hager Ayman, Mariam Wagdi, Bassant Ali, Aliaa Adel, Rahf Osama

“…Through trials, the proposed system employs two public datasets for sentiment analysis, namely the TMDB5k dataset and the Reviews dataset, and makes predictions (positive, negative, or neutral) based on the content of the review through conducting sentiment analysis on the text using the Viscous Accretion Disk Evolution Resource (VADER) approach. …”
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Random Forest-Based Retrieval of XCO₂ Concentration from Satellite-Borne Shortwave Infrared Hyperspectral by Wenhao Zhang, Zhengyong Wang, Tong Li, Bo Li, Yao Li, Zhihua Han

“…This paper proposes a method to predict the concentration of column-averaged CO₂ (XCO₂) from shortwave infrared hyperspectral satellite data, using machine learning to avoid the iterative computations of the physical method. …”
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Data-driven axial compressive strength investigation of FRP-confined coral aggregate concrete by Chang Zhou, Kai-Di Peng, Yu-Lei Bai

“…The SHapley Additive exPlanation (SHAP) algorithm is employed to elucidate the prediction mechanisms of the ML models and to clarify the interactions between the eight input features and the axial compressive strength of FRP-confined CAC. …”
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ABCD microstates: a new word in EEG mathematical analysis by A. A. Ivanov

“…Here, a fairly new approach to the mathematical processing of EEG signals is overviewed that allows not only to diagnose brain functional state, but also to predict the treatment outcomes in critically ill patients in intensive care units. …”
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Refining efficiency in standalone proton exchange membrane fuel cell systems through gross hopper optimization-based maximum power point tracking control by Nethra K., Reddy K. Jyotheeswara, Dash Ritesh, Parida Prasanta Kumar, Swain Sarat Chandra, Dhanamjayulu C., Mahapatro Abinash

“…To further improve prediction accuracy, the GHO algorithm incorporates a natural cubic-spline prediction model within its iterative mechanism, which enhances power generation predictions under dynamic conditions such as abrupt changes in fuel cell temperature and reactant partial pressure. …”
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Prospects for Legal Regulation of Quantum Communication by A. Minbaleev, S. Zenin, K. Evsikov

“…The authors note that their predictions about the cryptographic strength of encryption algorithms are based solely on modern knowledge about the capabilities of quantum computing and do not take into account its hidden potential, for example, in terms of cryptanalysis information systems based on a machine learning model generated by a quantum computer. …”
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Robust InceptionV3 with Novel EYENET Weights for Di-EYENET Ocular Surface Imaging Dataset: Integrating Chain Foraging and Cyclone Aging Techniques by Muhammad Ahmad Khan, Saif Ur Rehman Khan, Hafeez Ur Rehman, Suliman Aladhadh, Ding Lin

“…Abstract Predicting diabetic types from ocular surface eye images is a challenging task due to subtle variations in features and the potential overlap in presentations among different diabetic types. …”
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The effects of limb position and grasped load on hand gesture classification using electromyography, force myography, and their combination. by Peyton R Young, Kihun Hong, Eden J Winslow, Giancarlo K Sagastume, Marcus A Battraw, Richard S Whittle, Jonathon S Schofield

“…An emerging alternative control technique is force myography (FMG) which uses pattern recognition algorithms to predict hand gestures from the axial forces present at the skin's surface created by contractions of the underlying muscles. …”
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Model Input-Output Configuration Search With Embedded Feature Selection for Sensor Time-Series and Image Classification by Anh Tuan Hoang, Zsolt Janos Viharos

“…Machine learning is a powerful tool for extracting valuable information and making various predictions from diverse datasets. Traditional machine learning algorithms rely on well-defined input and output variables; however, there are scenarios where the separation between the input and output variables and the underlying, associated input and output layers of the model are unknown. …”
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Maximum Power Exploitation of Photovoltaic System under Fast-Varying Solar Irradiation and Local Shading by Yi-Jui Chiu, Bi Li, Chin-Ling Chen, Shui-Yang Lien, Ding Chen, Ji-Ming Yi, Yung-Hui Shih

“…The photovoltaic (PV) model commonly used in engineering has difficulty in accurately predicting the actual power generation. In this study, a PV model commonly used in engineering was used to establish a PV simulation model and improve it based on experimental data. …”
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Clustering and classification of early knee osteoarthritis using machine-learning analysis of step-up and down test kinematics in recreational table tennis players by Ui-jae Hwang, Kyu Sung Chung, Sung-min Ha

“…While conventional imaging methods often fail to detect early changes and require specialized expertise for interpretation, this study aimed to investigate the use of frontal plane kinematic data during step-up (SU) and step-down (SD) tests to classify and predict early osteoarthritis (EOA) using machine-learning techniques. …”
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Lightweight coal mine conveyor belt foreign object detection based on improved Yolov8n by Jierui Ling, Zhibo Fu, Xinpeng Yuan

“…Thirdly, to enhance the algorithm’s focus on key features, a Large Separable Kernel Attention mechanism (LSKA) is utilized to improve the original SPPF, thereby boosting the overall performance of the algorithm. …”
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Identifying the NEAT1/miR-26b-5p/S100A2 axis as a regulator in Parkinson's disease based on the ferroptosis-related genes. by Taole Li, Jifeng Guo

“…Corresponding miRNAs and lncRNAs were predicted to construct a ceRNA network. The scRNA-seq and experimental results showed that the signature model had a certain diagnostic effect and lncRNA NEAT1 might regulate the progression of ferroptosis in PD via the NEAT1/miR-26b-5p/S100A2 axis.…”
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Optimizing Artificial Neural Networks Using Mountain Gazelle Optimizer by Muhammed Abdulhamid Karabiyik, Bahaeddin Turkoglu, Tunc Asuroglu

“…Effectively adjusting these parameters is essential to minimize the error between predicted and actual outputs. While traditional training algorithms, such as gradient-based methods, have been widely used, they often face challenges like premature convergence and stagnation in local optima. …”
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Exploiting heart rate variability for driver drowsiness detection using wearable sensors and machine learning by Zakwan AlArnaout, Chamseddine Zaki, Yehia Kotb, Mouhammad AlAkkoumi, Nour Mostafa

“…We propose a system model that integrates wearable devices equipped with photoplethysmography (PPG) sensors, transmitting data to a smartphone and then to a cloud server. Two novel algorithms are developed to segment and label features periodically, predicting drowsiness levels based on HRV derived from PPG signals. …”
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Artificial Intelligence-based Approaches for Characterizing Plaque Components From Intravascular Optical Coherence Tomography Imaging: Integration Into Clinical Decision Support Sy... by Michela Sperti, Camilla Cardaci, Francesco Bruno, Syed Taimoor Hussain Shah, Konstantinos Panagiotopoulos, Karim Kassem, Giuseppe De Nisco, Umberto Morbiducci, Raffaele Piccolo, Francesco Burzotta, Fabrizio D’Ascenzo, Marco Agostino Deriu, Claudio Chiastra

“…Therefore, this review highlights the need for further advancements in AI-based IVOCT analysis, emphasizing the importance of additional validation and improved integration with clinical systems to enhance plaque characterization, support clinical decision-making, and advance risk prediction.…”
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Evaluating Medical Entity Recognition in Health Care: Entity Model Quantitative Study by Shengyu Liu, Anran Wang, Xiaolei Xiu, Ming Zhong, Sizhu Wu

“…The macrofactors affecting model performance were also screened using the multilevel factor elimination algorithm. ResultsThe fine-tuned BERT for Biomedical Text Mining, with balanced resource use, generally achieved the highest prediction accuracy across the Revised JNLPBA and AnatEM datasets, with microaverage (AVG_MICRO) scores of 0.932 and 0.8494, respectively, highlighting its superior proficiency in identifying medical entities. …”
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