AI-driven pharmacovigilance: Enhancing adverse drug reaction detection with deep learning and NLP by Dr. Bharti Khemani, Dr. Sachin Malave, Samyukta Shinde, Mandvi Shukla, Razzaq Shikalgar, Harshita Talwar

“…These findings suggest that specific demographic and clinical factors significantly influence the likelihood of adverse reactions, offering valuable insights for targeted monitoring and risk mitigation strategies[11]. This research underscores the potential of predictive modeling to enhance pharmacovigilance efforts and ensure safer clinical trial outcomes. • The research methodology includes a comparison of supervised learning algorithms, such as Logistic Regression, Random Forest, Gradient Boost, CNN, and genetic algorithms, to identify patterns and anomalies in clinical trial data. …”
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CLIPPERS. Three clinical cases and review by L. N. Prakhova, A. S. Parfyonova, Zh. I. Savintseva, A. G. Ilves, E. V. Bubnova, V. S. Krasnov, A. M. Tarasova, N. A. Totolyan

“…Furthermore, the necessity of further research is shown for improving the accuracy and specificity of the diagnostic criteria, as well as for defining biomarkers and developing algorithms of effective therapy.…”
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Image quality improvement in head and neck angiography based on dual-energy CT and deep learning by He Zhang, Lulu Zhang, Juan Long, He Zhang, Xiaonan Sun, Shuai Zhang, Aiyun Sun, Shenman Qiu, Yankai Meng, Tao Ding, Chunfeng Hu, Kai Xu

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A comprehensive transplanting of black-box adversarial attacks from multi-class to multi-label models by Zhijian Chen, Qi Zhou, Yujiang Liu, Wenjian Luo

“…However, previous research on black-box attacks has primarily focused on multi-class classification models, with relatively few studies on black-box attack algorithms for multi-label classification models. …”
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GASTROINTESTINAL FOOD ALLERGY IN CHILDREN by Svetlana G. Makarova, Leyla S. Namazova-Baranova, Elena A. Vishneva, Oksana A. Ereshko, Irina G. Gordeeva

“…According to different researchers, allergic lesions of the gastrointestinal tract occurs in 25–50% of patients with such common pathology as an allergy to cow's milk proteins. …”
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A Comparative Study of Breast Cancer Detection and Recurrence Prediction Using CatBoost Classifier by Rana Dhia’a Abdu-aljabar, Khansaa Dheya Aljafaar, Zinah Jaffar Mohammed Ameen, Hala A. Naman

“…The goal is to evaluate models using key metrics (sensitivity, specificity, precision, F1 score, accuracy, ROC, and AUC score). Among all algorithms examined, CatBoost stood out, showcasing AUC values above 98 %, 90 %, and 83% on different datasets. …”
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Genetical Swarm Optimization of Multihop Routes in Wireless Sensor Networks by Davide Caputo, Francesco Grimaccia, Marco Mussetta, Riccardo E. Zich

“…In recent years, wireless sensor networks have been attracting considerable research attention for a wide range of applications, but they still present significant network communication challenges, involving essentially the use of large numbers of resource-constrained nodes operating unattended and exposed to potential local failures. …”
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A practical study of artificial intelligence-based real-time feedback in online physical education teaching by Jiewei Ma, Lianzhen Ma, Shilong Qi, Bo Zhang, Wenpian Ruan

“…While promising, the technology has limitations in accuracy and interactivity. Future research should focus on optimizing algorithms and integrating adaptive learning to create more effective OLPE strategies.…”
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A Proposed Method of Automating Data Processing for Analysing Data Produced from Eye Tracking and Galvanic Skin Response by Javier Sáez-García, María Consuelo Sáiz-Manzanares, Raúl Marticorena-Sánchez

“…A Notebook in Jupyter is proposed with the steps for importing and processing data, as well as for using supervised and unsupervised machine learning algorithms.…”
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Robust Two-stage Dispatch of Multi-area Integrated Electric-gas Systems: A Decentralized Approach by Nan Jia, Cheng Wang, Yao Li, Nian Liu, Tianshu Bi

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Innovative approaches to optimizing the road safety monitoring system by Shevtsova A.G., Bychkova C.A., Podkopaev A.V., Nechaev O.Y.

“…The results of the intellectual research in the field of road safety in the Federal Districts of Russia under consideration allow us to conclude that there are significant opportunities in the work of innovative approaches in the field of ensuring road safety through the introduction of intelligent systems and effective algorithms.…”
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MODERN ARCHITECTURE BOARD INFORMATION AND CONTROL SYSTEMS OF HEAVY VEHICLES by V. V. Filinov, S. A. Mikaeva, M. S. Rodyukov, A. V. Filinova

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Moving Vehicles Detection and Tracking on Highways and Transportation System for Smart Cities by Manoj Kumar, Susmita Ray, Dileep Kumar Yadav

“…The literature also reveals for existing research for the machine learning and AI based methodologies to resolve more complex real-time problems. …”
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Quantum Edge Detection and Convolution Using Paired Transform-Based Image Representation by Artyom Grigoryan, Alexis Gomez, Sos Agaian, Karen Panetta

“…Classical edge detection algorithms often struggle to process large, high-resolution image datasets efficiently. …”
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Exploring Machine Learning Methods for Aflatoxin M1 Prediction in Jordanian Breast Milk Samples by Abdullah Aref, Eman Omar, Eman Alseidi, Nour Elhuda A. Alqudah, Sharaf Omar

“…To develop predictive models of aflatoxin M1 in breast milk, we employed well-known supervised machine learning algorithms such as Random Forest and Gradient Boosting. …”
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Identification of therapeutic targets for Alzheimer’s Disease Treatment using bioinformatics and machine learning by ZhanQiang Xie, YongLi Situ, Li Deng, Meng Liang, Hang Ding, Zhen Guo, QinYing Xu, Zhu Liang, Zheng Shao

“…This study aimed to identify potential therapeutic targets for the treatment of AD using comprehensive bioinformatics methods and machine learning algorithms. By integrating differential gene expression analysis, weighted gene co-expression network analysis, Mfuzz clustering, single-cell RNA sequencing, and machine learning algorithms including LASSO regression, SVM-RFE, and random forest, five hub genes related to AD, including PLCB1, NDUFAB1, KRAS, ATP2A2, and CALM3 were identified. …”
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Machine Learning and the Conundrum of Stroke Risk Prediction by Yaacoub Chahine, Matthew J Magoon, Bahetihazi Maidu, Juan C del Álamo, Patrick M Boyle, Nazem Akoum

“…Another avenue of research explored is ML as a means of enriching multiscale computational modelling, which holds great promise for revealing thrombogenesis mechanisms. …”
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VGGBM-Net: A Novel Pixel-Based Transfer Features Engineering for Automated Coffee Bean Diseases Classification by Muhammad Shadab Alam Hashmi, Azam Mehmood Qadri, Ali Raza, Saleem Ullah, Aseel Smerat, Changgyun Kim, Muhammad Syafrudin, Norma Latif Fitriyani

“…These enhanced features are then used as inputs for advanced machine-learning algorithms. Unlike traditional models, this feature extraction enhances classification accuracy and robustness. …”
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Construction of a novel radioresistance-related signature for prediction of prognosis, immune microenvironment and anti-tumour drug sensitivity in non-small cell lung cancer by Yanliang Chen, Chan Zhou, Xiaoqiao Zhang, Min Chen, Meifang Wang, Lisha Zhang, Yanhui Chen, Litao Huang, Junjun Sun, Dandan Wang, Yong Chen

“…The objective of this research was to detect radioresistance-related genes (RRRGs) with prognostic value in NSCLC.Methods The weighted gene coexpression network analysis (WGCNA) and differentially expressed genes (DEGs) analysis were performed to identify RRRGs using expression profiles from TCGA and GEO databases. …”
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Clinical Manifestation and Errors in the Diagnosis of Classical Paroxysmal Nocturnal Hemoglobinuria: A clinical case series of 150 patients by AD Kulagin, OU Klimova, AV Dobronravov, MO Ivanova, TA Rudakova, EV Babenko, VA Dobronravov, BV Afanas’ev

“…Errors of the primary diagnosis reach 78 % and lead to inadequate treatment. The results of the research showed the need for multidisciplinary approach and strict adherence to diagnostic algorithms of PNH in the risk groups, according to current recommendations.…”
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