Novel Approaches for the Early Detection of Glaucoma Using Artificial Intelligence by Marco Zeppieri, Lorenzo Gardini, Carola Culiersi, Luigi Fontana, Mutali Musa, Fabiana D’Esposito, Pier Luigi Surico, Caterina Gagliano, Francesco Saverio Sorrentino

“…Background: If left untreated, glaucoma—the second most common cause of blindness worldwide—causes irreversible visual loss due to a gradual neurodegeneration of the retinal ganglion cells. …”
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Hybrid Machine Learning Model for Efficient Botnet Attack Detection in IoT Environment by Mudasir Ali, Mobeen Shahroz, Muhammad Faheem Mushtaq, Sultan Alfarhood, Mejdl Safran, Imran Ashraf

“…Botnet attack emerged as one of the most harmful attacks. Botnet identification is becoming challenging due to the numerous attack vectors and the ongoing evolution of viruses. …”
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The study of the influence of <i>Thlaspi arvense</i> L. on the characteristics of the reproductive system of male rats by R. G. Farkhutdinov, K. A. Pupykina, L. A. Sharafutdinova, A. M. Fedorova, Z. R. Hismatullina, M. I. Garipova, E. F. Koroleva, A. A. Yamaleeva, T. D. Rendyuk

“…The arsenal of medicinal plants used in traditional medicine for the treatment of diseases in men is mainly represented by phytoadaptogens, most of which have a small resource potential in Russia, therefore, it is relevant to search for plants with a sufficient raw material base and with the potential for cultivation. …”
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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

“…By analysing data from sensors and system logs, ML algorithms can identify patterns indicative of faults or inefficiencies, such as shading, soiling, or equipment malfunctions, often before they become serious issues. Convolutional Neural Networks (CNNs) are a class of deep learning algorithms most commonly applied. …”
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Inequalities in Mild Cognitive Impairment Risk Among Chinese Middle-Aged and Older Adults: Insights from an Integrated Learning Model by Bi S, Guo D, Tan H, Chen Y, Li G

“…Education emerged as the most critical predictor, followed by Instrumental Activities of Daily Living (IADL) and gender. …”
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Machine learning and artificial intelligence in type 2 diabetes prediction: a comprehensive 33-year bibliometric and literature analysis by Mahreen Kiran, Ying Xie, Nasreen Anjum, Graham Ball, Barbara Pierscionek, Duncan Russell

“…Ensemble methods (e.g., Random Forest, Gradient Boosting) and deep learning models (e.g., Convolutional Neural Networks) dominate recent advancements. …”
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NEURAL NETWORKS INTEGRATION INTO LEGAL RESOURCES FOR ANTI-СORRUPTION MEASURES IN INTERNATIONAL ECONOMIC CO-OPERATION by Oleksii Makarenkov

“…The presence of virtuous individuals in top public positions within the world's most powerful nations has been demonstrated to reduce the level of global corruption-driven perversion and vice versa. …”
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Ensemble Streamflow Simulations in a Qinghai–Tibet Plateau Basin Using a Deep Learning Method with Remote Sensing Precipitation Data as Input by Jinqiang Wang, Zhanjie Li, Ling Zhou, Chi Ma, Wenchao Sun

“…The SHAP-based interpretability analysis further demonstrated that RF made the most significant contribution to the ensemble simulation, while LSTM contributed the least. …”
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Interpretation of Bayesian-optimized deep learning models for enhancing soil erosion susceptibility prediction and management: a case study of Eastern India by Meshel Alkahtani, Javed Mallick, Saeed Alqadhi, Md Nawaj Sarif, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…These insights facilitate the prioritization of soil conservation measures, enabling decision-makers to focus on the most impactful factors for mitigating soil erosion.…”
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Modern options of endoscopic retrograde stenting of bile ducts in treatment of obstructive jaundice at malignant pancreatobiliary tumors by S. A. Budzinsky, S. G. Shapovalyants, Ye. D. Fedorov, A. G. Mylnikov, D. V. Bakhtiozina

“…Acute obstructive jaundice developed on background of malignant pancreatobiliary neoplasms is one of the most complex and dramatic problems of modern abdominal surgery. …”
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Adaptation of the microflora of pig farms to the disinfectant “Sviteco PIP Multi” and the antagonistic activity of the probiotic bacilli contained in its composition by V. O. Myronchuk, R. A. Peleno

“…At the same time, adding “Sviteco PIP Multi” to the medium gave growth to most microorganisms at 49–50 subcultures and significantly lower concentrations. …”
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Machine learning approaches for EGFR mutation status prediction in NSCLC: an updated systematic review by Liu Haixian, Liu Haixian, Pang Shu, Pang Shu, Li Zhao, Li Zhao, Lu Chunfeng, Lu Chunfeng, Li Lun

“…BackgroundWith the rapid advances in artificial intelligence—particularly convolutional neural networks—researchers now exploit CT, PET/CT and other imaging modalities to predict epidermal growth factor receptor (EGFR) mutation status in non-small-cell lung cancer (NSCLC) non-invasively, rapidly and repeatably. …”
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Deep learning-based automated measurement of hip key angles and auxiliary diagnosis of developmental dysplasia of the hip by Ruixin Li, Xiao Wang, Tianran Li, Beibei Zhang, Xiaoming Liu, Wenhua Li, Qirui Sui

“…Abstract Objectives Anteroposterior pelvic radiographs remains the most widely employed method for diagnosing developmental dysplasia of the hip. …”
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A Neural Network for the Prediction of the Visual Acuity Gained from Vitrectomy and Peeling for Epiretinal Membrane by Rupert Kamnig, MD, Noah Robatsch, Anna Hillenmayer, MD, Denise Vogt, MD, Susanna F. König, MD, Efstathios Vounotrypidis, MD, Armin Wolf, MD, Christian M. Wertheimer, MD

“…The images were processed using a convolutional network. The output of both networks was concatenated and presented to a second multilayer perceptron. …”
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Enhancing Radiologist Productivity with Artificial Intelligence in Magnetic Resonance Imaging (MRI): A Narrative Review by Arun Nair, Wilson Ong, Aric Lee, Naomi Wenxin Leow, Andrew Makmur, Yong Han Ting, You Jun Lee, Shao Jin Ong, Jonathan Jiong Hao Tan, Naresh Kumar, James Thomas Patrick Decourcy Hallinan

“…A few studies also explored machine learning-based automation software and, more recently, large language models. Although most demonstrated gains in efficiency and accuracy, limited external validation and dataset heterogeneity could reduce broader adoption. …”
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Traditional Chinese medicine diagnostic prediction model for holistic syndrome differentiation based on deep learning by Zhe Chen, Dong Zhang, Chunxiang Liu, Hui Wang, Xinyao Jin, Fengwen Yang, Junhua Zhang

“…Based on the Bidirectional Encoder Representations from Transformers (BERT) and Convolutional Neural Networks (CNN) models, with the classification constraints from TCM holistic syndrome differentiation, the TCM-BERT-CNN model was constructed, which completes the end-to-end TCM holistic syndrome text classification task through symptom input and syndrome output. …”
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A hybrid deep learning framework for global irradiance prediction using fuzzy C-Means, CNN-WNN, and Informer models by Walid Mchara, Lazhar Manai, Mohamed Abdellatif Khalfa, Monia Raissi, Wissem Dimassi, Salah Hannachi

“…Finally, the Informer model — equipped with attention mechanisms — identifies long-term temporal dependencies, selecting the most informative timesteps for accurate prediction.The study’s experiments were conducted using a comprehensive dataset sourced from the Photovoltaic Geographical Information System (PVGIS). …”
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A Novel Bilateral Data Fusion Approach for EMG-Driven Deep Learning in Post-Stroke Paretic Gesture Recognition by Alexey Anastasiev, Hideki Kadone, Aiki Marushima, Hiroki Watanabe, Alexander Zaboronok, Shinya Watanabe, Akira Matsumura, Kenji Suzuki, Yuji Matsumaru, Hiroyuki Nishiyama, Eiichi Ishikawa

“…We introduce a hybrid deep learning model for recognizing hand gestures from electromyography (EMG) signals in subacute stroke patients: the one-dimensional convolutional long short-term memory neural network (CNN-LSTM). …”
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Rapid estimation of DON content in wheat flour using close‐range hyperspectral imaging and machine learning by Dinesh Kumar Saini, Anshul Rana, Jyotirmoy Halder, Mohammad Maruf Billah, Harsimardeep S. Gill, Jinfeng Zhang, Subash Thapa, Shaukat Ali, Brent Turnipseed, Karl Glover, Maitiniyazi Maimaitijiang, Sunish K. Sehgal

“…Abstract Fusarium head blight (FHB) is one of the most destructive fungal diseases affecting wheat (Triticum aestivum). …”
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Passive Sensing for Mental Health Monitoring Using Machine Learning With Wearables and Smartphones: Scoping Review by ShiYing Shen, Wenhao Qi, Jianwen Zeng, Sixie Li, Xin Liu, Xiaohong Zhu, Chaoqun Dong, Bin Wang, Yankai Shi, Jiani Yao, Bingsheng Wang, Xiajing Lou, Simin Gu, Pan Li, Jinghua Wang, Guowei Jiang, Shihua Cao

“…Deep learning models (eg, convolutional neural networks and long short-term memory) showed high accuracy, while traditional ML (eg, random forest) remained prevalent due to better interpretability. …”
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