Enhancing Secure Medical Data Communication Through Integration of LSB and DCT for Robust Analysis in Image Steganography by Ramyashree, P. S. Venugopala, S. Raghavendra, Vijay S. Kubihal

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Hybrid Prophet-NAR Model for Short-Term Electricity Load Forecasting by Winita Sulandari, Yudho Yudhanto, Etik Zukhronah, Isnandar Slamet, Hilman Ferdinandus Pardede, Paulo Canas Rodrigues, Muhammad Hisyam Lee

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Electrogastrogram-based detection of cybersickness with the application of wavelet transformation and machine learning: A case study by Ilija V. Tanasković, Nenad B. Popović, Jaka J. Sodnik, Sašo J. Tomažič, Nadica S. Miljković

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Pursuit on the plane by objects moving away from the trajectory of defending object, with simulation of detection area by A. А. Dubanov, T. V. Ausheev

“…The results of the research can be in demand in the design of unmanned aerial vehicles with elements of autonomous control and artificial intelligence.…”
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SGCL-LncLoc: An Interpretable Deep Learning Model for Improving lncRNA Subcellular Localization Prediction with Supervised Graph Contrastive Learning by Min Li, Baoying Zhao, Yiming Li, Pingjian Ding, Rui Yin, Shichao Kan, Min Zeng

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A multi-task model for failure identification and GPS assessment in metro trains by Pratik Vinayak Jadhav, Sairam V. A, Siddharth Sonkavade, Shivali Amit Wagle, Preksha Pareek, Ketan Kotecha, Tanupriya Choudhury

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A machine learning framework for short-term prediction of chronic obstructive pulmonary disease exacerbations using personal air quality monitors and lifestyle data by M. Atzeni, G. Cappon, J. K. Quint, F. Kelly, B. Barratt, M. Vettoretti

“…The framework employs (i) k-means clustering to uncover potentially distinct patient sub-types, (ii) supervised ML techniques (Logistic Regression, Random Forest, and eXtreme Gradient Boosting) to train and test predictive models for each patient sub-type and (iii) an explainable artificial intelligence technique (SHAP) to interpret the final models. …”
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External validation of AI-based scoring systems in the ICU: a systematic review and meta-analysis by Patrick Rockenschaub, Ela Marie Akay, Benjamin Gregory Carlisle, Adam Hilbert, Joshua Wendland, Falk Meyer-Eschenbach, Anatol-Fiete Näher, Dietmar Frey, Vince Istvan Madai

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SARS-CoV2 pneumonia patients admitted to the ICU: Analysis according to clinical and biological parameters and the extent of lung parenchymal lesions on chest CT scan, a monocentri... by Abed Al Hadi Krisht, Kévin Grapin, Romain Chauvot de Beauchene, Benjamin Bonnet, Lucie Cassagnes, Bertrand Evrard, Mireille Adda, Bertrand Souweine, Claire Dupuis

“…The extent of lung parenchyma lesions observed on the chest CT performed on admission was established by artificial intelligence software.<h4>Measurements</h4>Several clinical characteristics and laboratory features were collected on admission including plasma interleukin-6, HLA-DR monocytic-expression rate (mHLA-DR), and the extent of lung parenchymal lesions. …”
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User and Developer Views on Using AI Technologies to Facilitate the Early Detection of Skin Cancers in Primary Care Settings: Qualitative Semistructured Interview Study by Owain Tudor Jones, Natalia Calanzani, Suzanne E Scott, Rubeta N Matin, Jon Emery, Fiona M Walter

“…Earlier detection of skin cancer leads to better outcomes for patients. Artificial intelligence (AI) technologies have been applied to skin cancer diagnosis, but many technologies lack clinical evidence and/or the appropriate regulatory approvals. …”
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Graphene nanomaterial-based electrochemical biosensors for salivary biomarker detection: A translational approach to oral cancer diagnostics by D. Mahalakshmi, J. Nandhini, G. Meenaloshini, E. Karthikeyan, KK Karthik, J. Sujaritha, Vandhana, V, C. Ragavendran

“…Finally, we present a futuristic outlook on the integration of graphene-based biosensors with artificial intelligence, microfluidics, and telemedicine platforms to enable personalized diagnostics and treatment monitoring. …”
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Depression Detection and Diagnosis Based on Electroencephalogram (EEG) Analysis: A Systematic Review by Kholoud Elnaggar, Mostafa M. El-Gayar, Mohammed Elmogy

“…<b>Methods:</b> This survey emphasizes the critical role of EEG in advancing artificial intelligence (AI)-driven approaches for depression diagnosis. …”
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IoT-Based Multisensors Fusion for Activity Recognition via Key Features and Hybrid Transfer Learning by Ahmad Jalal, Danyal Khan, Touseef Sadiq, Moneerah Alotaibi, Sultan Refa Alotaibi, Hanan Aljuaid, Hameedur Rahman

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Recent Developments of Directional Overcurrent Relay Coordination in Ring Distribution Network Based on Hybrid Optimization Techniques by Annas Alamshah, Suzana Pil Ramli, Nurulafiqah Nadzirah Mansor, Muhamad Usama, Hazlie Mokhlis, Hadi Suyono, Rini Nur Hasanah

“…The paper delves into Nature-Inspired Algorithms (NIAs), metaheuristic approaches, mathematical formulations, and artificial intelligence methods, critically assessing their capabilities in navigating the complex landscape of relay coordination. …”
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Real-Time Plant Health Detection Using Deep Convolutional Neural Networks by Mahnoor Khalid, Muhammad Shahzad Sarfraz, Uzair Iqbal, Muhammad Umar Aftab, Gniewko Niedbała, Hafiz Tayyab Rauf

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Toward Robust Lung Cancer Diagnosis: Integrating Multiple CT Datasets, Curriculum Learning, and Explainable AI by Amira Bouamrane, Makhlouf Derdour, Akram Bennour, Taiseer Abdalla Elfadil Eisa, Abdel-Hamid M. Emara, Mohammed Al-Sarem, Neesrin Ali Kurdi

“…Finally, explainable artificial intelligence (XAI) using Gradient-weighted Class Activation Mapping (Grad-CAM) was employed to better understand the model. …”
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Diagnostic Performance of Deep Learning Applications in Hepatocellular Carcinoma Detection Using Computed Tomography Imaging by Enes Şahin, Ozan Can Tatar, Mehmet Eşref Ulutaş, Sertaç Ata Güler, Turgay Şimşek, Nihat Zafer Utkan, Nuh Zafer Cantürk

“…Conclusion: The implementation of the YOLO architecture for detecting HCC in CT scans has shown substantial promise, indicating that DL models could soon become a standard tool in oncological diagnostics. As artificial intelligence technology continues to evolve, its integration into healthcare systems is expected to advance the accuracy and efficiency of diagnostics in oncology, enhancing early detection and treatment strategies and potentially improving patient survival rates.…”
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AI-Driven Framework for Recognition of Guava Plant Diseases through Machine Learning from DSLR Camera Sensor Based High Resolution Imagery by Ahmad Almadhor, Hafiz Tayyab Rauf, Muhammad Ikram Ullah Lali, Robertas Damaševičius, Bader Alouffi, Abdullah Alharbi

“…In this paper, an artificial intelligence (AI) driven framework is presented to detect and classify the most common guava plant diseases. …”
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Application of Phi (<italic>&#x03A6;</italic>), the Golden Ratio, in Computing: A Systematic Review by M. Akhtaruzzaman, Jamal Uddin Tanvin, Amir Akramin Shafie, Fahim Shahryer, Sachitra Halder

“…The review also categorizes findings by their specific applications and contexts, providing valuable insights into <inline-formula> <tex-math notation="LaTeX">$\phi $ </tex-math></inline-formula>&#x2019;s impact on mathematics, cryptography, search algorithms, machine learning, artificial intelligence, photonics, natural sciences, system design, power engineering, robotics, and practical human life. …”
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Cross-education: motor unit adaptations mediate the strength increase in non-trained muscles following 8 weeks of unilateral resistance training by Edoardo Lecce, Alessandra Conti, Alessandro Del Vecchio, Francesco Felici, Alessandro Scotto di Palumbo, Massimo Sacchetti, Ilenia Bazzucchi

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