AI models for the identification of prognostic and predictive biomarkers in lung cancer: a systematic review and meta-analysis by Hind M. AlOsaimi, Aseel M. Alshilash, Layan K. Al-Saif, Jannat M. Bosbait, Roaa S. Albeladi, Dalal R. Almutairi, Alwaleed A. Alhazzaa, Tariq A. Alluqmani, Saud M. Al Qahtani, Sara A. Almohammadi, Razan A. Alamri, Abdullah A. Alkurdi, Waleed K. Aljohani, Raghad H. Alraddadi, Mohammed K. Alshammari

“…Most of the studies developed models for the prediction of EGFR, followed by PD-L1 and ALK biomarkers in lung cancer. …”
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Predictive modeling and interpretative analysis of risks of instability in patients with Myasthenia Gravis requiring intensive care unit admission by Chao-Yang Kuo, Emily Chia-Yu Su, Hsu-Ling Yeh, Jiann-Horng Yeh, Hou-Chang Chiu, Chen-Chih Chung

“…This novel, personalized approach to risk stratification elucidates crucial risk factors and has the potential to enhance clinical decision-making, optimize resource allocation, and ultimately improve patient outcomes.…”
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Pharmacological potential of 6,11-dihydro[1,2,4]triazolo[4’,3’:1,6]-pyrido[3,4-b]-5-carboxylic acid and its esters by S. O. Fedotov, A. S. Hotsulia

“…The combination of the indole fragment, which demonstrates activity due to its aromatic structure, with the 1,2,4-triazole nucleus, which is characterised by chemical stability and the ability to form hydrogen bonds, creates a promising basis for the development of new therapeutic agents with improved properties. The active implementation of various modifications of indole and 1,2,4-triazole frameworks is aimed at optimizing the pharmacokinetic and pharmacodynamic characteristics of medicinal products. …”
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GIS Analysis Model Integration and Service Composition Prospects by L. Ding, P. Cai, W. Huang, H. Zhang, F. Ding, W. Zhao, D. Tang, Z. Wang

“…Model ensemble techniques, rooted in machine learning and data mining, address limitations of single models by combining predictions from multiple base learners, thereby improving robustness and reducing overfitting. …”
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A machine learning-based screening model for the early detection of prostate cancer developed using serum microRNA data from a mixed cohort of 8,741 participants by Cong Lai, Zhensheng Hu, Zhuohang Li, Zhikai Wu, Kuiqing Li, Lin Li, Hongze Liu, Juanyi Shi, Yi Zhou, Kewei Xu, Cheng Liu

“…Abstract Objective Early detection of prostate cancer (PCa) can improve the prognosis of patients. Currently, the role of the prostate specific antigen test for PCa screening remains debatable. …”
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Analysis of types of medical interventions for patients with pancreatic adenocarcinoma in hospitals of Saint Petersburg for the period from 2014 to 2020 by V. E. Moiseenko, A. V. Pavlovsky, D. A. Granov, L. V. Kochorova, N. I. Vishnjakov, V. V. Hizha, A. V. Yazenok, N. Ju. Shirshova, L. A. Solovyova

“…The data obtained from such an analysis can become the basis for the development of algorithms and programs for optimizing the provision of care for patients suffering from this pathology. …”
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Shipyard Manpower Digital Recruitment: A Data-Driven Approach for Norwegian Stakeholders by Bogdan Florian Socoliuc, Andrei Alexandru Suciu, Mădălina Ecaterina Popescu, Doru Alexandru Plesea, Florin Nicolae

“…The application of machine learning algorithms provides predictive insights that support real-time adjustments to job postings, optimizing recruitment strategies. …”
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Non-Destructive Thickness Measurement of Energy Storage Electrodes via Terahertz Technology by Zhengxian Gao, Xiaoqing Jia, Jin Wang, Zhijun Zhou, Jianyong Wang, Dongshan Wei, Xuecou Tu, Lin Kang, Jian Chen, Dengzhi Chen, Peiheng Wu

“…Secondly, a hybrid signal processing algorithm is applied, combining an optimized Savitzky–Golay filter for high-frequency noise suppression with an enhanced sinc function wavelet threshold technique for signal fidelity improvement. …”
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A quantum random access memory (QRAM) using a polynomial encoding of binary strings by Priyanka Mukhopadhyay

“…In this paper we develop a new design for QRAM and implement it with Clifford+T circuit. We focus on optimizing the T-count and T-depth since non-Clifford gates are the most expensive to implement fault-tolerantly in most error correction schemes. …”
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Unraveling C-to-U RNA editing events from direct RNA sequencing by Adriano Fonzino, Caterina Manzari, Paola Spadavecchia, Uday Munagala, Serena Torrini, Silvestro Conticello, Graziano Pesole, Ernesto Picardi

“…Using in vitro synthesized and human ONT reads, our model optimizes the signal-to-noise ratio improving the detection of C-to-U editing sites with high accuracy, over 90% in all samples tested. …”
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Using machine learning techniques to evaluate the impact of future climate change on wheat yields in Xinjiang, China by Xuehui Gao, Jian Liu, Haixia Lin, Tehseen Javed, Feihu Yin, Rui Chen, Yue Wen, Jinzhu Zhang, Kefan Yi, Zhenhua Wang

“…These findings highlight the need for adaptive measures, such as enhanced water management, optimized sowing dates, and improved soil quality, to support resilient wheat production and sustainable development in Xinjiang or similar arid areas amid climate change.…”
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Using Geospatial Intelligence to Enhance Voting Access in Local Elections for People with Disabilities by A. Cohen, S. Dalyot

“…This study leverages geospatial intelligence to enhance voting accessibility by developing an algorithmic approach that helps individuals locate the nearest Accessible Polling Station (APS). …”
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Research on machine vision online monitoring system for egg production and quality in cage environment by Zhenlong Wu, Hengyuan Zhang, Cheng Fang

“…To diverse operational needs, two distinct post-processing algorithms were developed: one for counting eggs and detecting abnormalities during robotic patrols, and another for assessing egg quality through fixed video streams, which measured crucial parameters such as egg dimensions and shape indexes. …”
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An Intelligent LoRaWAN-Based IoT Device for Monitoring and Control Solutions in Smart Farming Through Anomaly Detection Integrated With Unsupervised Machine Learning by Maram Fahaad Almufareh, Mamoona Humayun, Zulfiqar Ahmad, Asfandyar Khan

“…Therefore, the implementation of IoT devices would give the farmer access to current readings when needed for making decisions and optimizing their resources on the most important parameters for agricultural activity. …”
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A Promising Methodological Approach to Identifying Areas with the Greatest Potential for the Development of the City Cycling Infrastructure by O. А. Grishina, A. I. Grishin, I. A. Stroganov

“…This problem is among the most urgent in modern urban planning, giving the context of the issues of “green” and “sharing” economies that influence the practice of planning and development of CI. …”
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Impact of imbalanced features on large datasets by Waleed Albattah, Rehan Ullah Khan

“…Distributed Gaussian (D-GA) and Distributed Poisson (D-PO) are found to be the most effective techniques, especially in improving Random Forest (RF) and SVM models. …”
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Machine-learning-based reconstruction of long-term global terrestrial water storage anomalies from observed, satellite and land-surface model data by N. Mandal, P. Das, K. Chanda, K. Chanda

“…The most effective machine learning (ML) algorithms among convolutional neural network (CNN), support vector regression (SVR), extra trees regressor (ETR) and stacking ensemble regression (SER) models are evaluated at each grid cell to achieve optimal reproducibility. …”
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A Lightweight Direction-Aware Network for Vehicle Detection by Luxia Yang, Yilin Hou, Hongrui Zhang, Chuanghui Zhang

“…However, most high-precision vehicle detection algorithms suffer from high computational effort and slow detection speeds, resulting in the challenging task of deploying these algorithms on mobile devices. …”
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Machine learning as a tool for diagnostic and prognostic research in coronary artery disease by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, V. Yu. Rublev

“…It is assumed that the improvement of ML-based models and their introduction into clinical practice will help support medical decision-making, increase the effectiveness of treatment and optimize health care costs.…”
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CONSTRUCTION OF SUBSTITUTION BOX (S-BOX) BASED ON IRREDUCIBLE POLYNOMIALS ON GF(2^8) by Faldy Tita, Adi Setiawan, Bambang Susanto

“…The main goal is to determine the most optimal S-Box structure to minimize correlation, thereby improving the security and unpredictability of the cryptographic system. …”
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