Precision in practice: exploring the impact of ai and machine learning on ultrasound guided regional anaesthesia by Noor Ul Huda Bhatti, Syed Ghazi Ali Kirmani, Maryam Butt

“…It is used to conduct predictive tasks without programming instructions by creating algorithms. Extensive research has been conducted to evaluate the influence of machine learning on innovative anaesthesia methods. …”
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Features of tactics of inspection of accident sites in the investigation of illegal interference in the activities of energy facilities using unmanned vehicles by S. L. Kislenko, A. B. Smushkin

“…At the same time, the importance of urgently studying the volatile memory of a working device is stated.Conclusions about the achievement of the research goal: the paper proposes adaptive algorithms for the investigator's actions in various investigative situations: when the functioning of the device was suppressed by electronic warfare; when the UAV was physically damaged or destroyed; when an attacker with a UAV control device (remote control, smartphone, laptop, special glasses, etc.) was detained at the scene; when the control device is detected, but the attacker himself has disappeared; when the attacker has destroyed the control device; when information from the UAV (video and sensor readings) was transmitted not only to the operator's device, but also to another addressee; when the operator was detained on the territory of the fuel and energy complex. …”
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Machine Learning-Based Prediction of Postoperative Deep Vein Thrombosis Following Tibial Fracture Surgery by Humam Baki, İsmail Bülent Özçelik

“…The top-performing model (random forest with RFE) attained an AUC of ~0.99, while several others (including LightGBM and SVM-based models) also reached AUC values in the 0.97–0.99 range. Notably, support vector machine models paired with Boruta or LASSO feature selection demonstrated the best calibration (lowest Brier scores), indicating reliable risk estimation. …”
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Application of statistical methods for predicting udp-flood attacks by M. V. Tumbinskaya, V. V. Volkov, B. G. Zagidullin

“…For DDoS attacks lasting up to 20 minutes, seasonality was also detected in the first quarter of the calendar year, which means that the largest number of attacks of this duration should be expected in the first quarter of 2020. …”
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Association between resolved hepatitis B virus infection and depression in American adults : a cross-sectional study by Zihan Qin, Yizhuo Liu, Yifei Liu, Anqi Yang, Ruoyi Zhang, Kun Zhang, Shutian Zhang

“…Propensity score matching (PSM) was performed to balance baseline characteristics. Algorithms such as inverse probability of treatment weighting (IPTW) were also applied. …”
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Extracting Information from Unstructured Medical Reports Written in Minority Languages: A Case Study of Finnish by Elisa Myllylä, Pekka Siirtola, Antti Isosalo, Jarmo Reponen, Satu Tamminen, Outi Laatikainen

“…The results of classical classifiers were also compared with FinBERT, a domain-adapted Finnish BERT model. …”
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Breast thermography: a systematic review and meta-analysis by Ane Goñi-Arana, Jorge Pérez-Martín, Francisco Javier Díez

“…However, advances in infrared technology and image processing algorithms in the twenty-first century led to a renewed interest in thermography. …”
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TARREAN: A Novel Transformer with a Gate Recurrent Unit for Stylized Music Generation by Yumei Zhang, Yulin Zhou, Xiaojiao Lv, Jinshan Li, Heng Lu, Yuping Su, Honghong Yang

“…Music generation by AI algorithms like Transformer is currently a research hotspot. …”
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A Spatio-Temporal Deep Learning Model for Automatic Arctic Sea Ice Classification with Sentinel-1 SAR Imagery by Li Zhao, Yufeng Zhou, Wei Zhong, Cheng Jin, Bo Liu, Fangzhao Li

“…Based on deep learning technology, many automatic sea ice classification algorithms have been developed using synthetic aperture radar (SAR) imagery over the last decade. …”
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Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads by Mostafa M. Radwan, Sundus A. Faris, Ahmed Y. Barakat, Ahmad Mousa

“…Machine and deep learning algorithms have recently been more instrumental for forecasting pavement conditions. …”
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Species delimitation and microalgal cryptic diversity analysis of the genus Micractinium (Chlorophyta) by E. S. Krivina, A. D. Temraleeva, Yu. S. Bukin

“…The algorithms used for species delimitation had different results on the number of potentially species-level clusters allocated. …”
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Hybrid AI and semiconductor approaches for power quality improvement by Ravikumar Chinthaginjala, Asadi Srinivasulu, Anupam Agrawal, Tae Hoon Kim, Sivarama Prasad Tera, Shafiq Ahmad

“…The research addresses key power quality challenges - including voltage sags, swells, harmonics, and transient disturbances - through a data-driven framework that combines traditional control techniques with adaptive learning models. A variety of algorithms, including Support Vector Machines (SVM), Random Forests, Neural Networks, Convolutional Neural Networks (CNN), and Long Short-Term Memory (LSTM) networks, were tested using real-time data. …”
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Optimizing role assignment for scaling innovations through AI in agricultural frameworks: An effective approach by Sonia Bisht, Ranjana, Swapnila Roy

“…The findings demonstrate that optimized role assignment not only enhances the performance of AI applications but also fosters a collaborative ecosystem that is adaptable to changing agricultural demands. …”
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The importance of using mobile ultrasound devices in improving the quality and safety of emergency care, anesthesia and intensive care by A. A. Krishtafor, D. A. Krishtafor, O. V. Kravets, O. V. Pylypenko

“…Further expansion of the use of the POCUS concept and integration of ultrasound into life support algorithms are related to the development of available compact, highly sensitive ultrasound devices suitable for prehospital diagnostics.…”
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Association between hemoglobin A1c variability and hypoglycemia-related hospitalizations in veterans with diabetes mellitus by Julia C Prentice, Molly J Y Zhao, David C Mohr, Paul R Conlin

“…Average A1c levels were also independently associated with HRH, with levels <7.0% (53 mmol/mol) having lower risk and >9% (75 mmol/mol) with greater risk. …”
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Gene regulatory network resource aids in predicting trans-acting regulators of biosynthetic gene clusters in Aspergillus fumigatus by Hye-won Seo, Jin Woo Bok, Nancy P. Keller

“…These advances highlight the power of inference algorithms to uncover unpredictable networks in specialized metabolite synthesis.IMPORTANCEToxic secondary metabolites are virulence factors of the opportunistic fungal pathogen Aspergillus fumigatus, yet the transcriptional networks regulating secondary metabolite production remain elusive. …”
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Deep Learning in Defect Detection of Wind Turbine Blades: A Review by Katleho Masita, Ali N. Hasan, Thokozani Shongwe, Hasan Abu Hilal

“…Defects such as cracks, delamination, erosion, and icing not only compromise the structural integrity of blades but also significantly reduce their aerodynamic efficiency and energy production capabilities. …”
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Integrative analysis identifies FBXO5 as a critical mediator of CRPC progression and bone metastatic potential by Rajnikant Raut, Devesh Srivastava, Amit Kumar Chakraborty, Manish V. Bais, Parul Mishra, Ashish Misra

“…Methods and Results In this study, we employed machine learning (ML) algorithms and integrative bioinformatics approaches to analyze the gene expression profiles of E3 ubiquitin ligases in CRPC patients. …”
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RETRACTED ARTICLE: A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications by Hadi Hashemzadeh, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Mario Rothbauer, Peter Ertl, Hossein Naderi-Manesh

“…The rapid development of machine learning techniques, especially deep learning algorithms, has attracted much interest in its application to medical image problems. …”
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Comparing miR-16 and miR-1228 as an optimal endogenous control for quantification of circulating microRNAs in colorectal cancer patients by Chia-Lin Yang, Fu-Ming Tsai, Chuang-Wei Chen, Kuan-Hong Hsiao, Jia-Hui Chen, Woei-Yau Kao

“…The effects of normalizers on the relative quantification of circulating miR-31 in plasma samples of colorectal cancer (CRC) were also assessed. Materials and Methods: The cel-miR-39 was a spiked-in RNA used as an external control and added to plasma samples before RNA extraction. …”
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