Transforming Manufacturing Quality Management with Cognitive Twins: A Data-Driven, Predictive Approach to Real-Time Optimization of Quality by Asif Ullah, Muhammad Younas, Mohd Shahneel Saharudin

“…By utilizing the power of machine learning algorithms, the cognitive twin constantly monitors and then analyzes real-time data. …”
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Artificial intelligence for diagnosing rare bone diseases: a global survey of healthcare professionals by Behnam Javanmardi, Rebekah L. Waikel, Tinatin Tkemaladze, Shahida Moosa, Alexander Küsshauer, Jean Tori Pantel, Minu Fardipour, Peter Krawitz, Benjamin D. Solomon, Klaus Mohnike

“…Although around half of the participants (n = 45) have concerns about AI-related errors and consider the explainability of AI algorithms to be very (42/103) or extremely (9/103) important, 81% of the respondents report that they are somewhat (n = 39) or extremely (n = 45) likely to consider integrating image recognition AI into their current diagnostic workflow. …”
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Problems and perspectives of family doctors training on the undergraduate stage by Yu. M. Kolesnik, V. D. Syvolap, N. S. Mikhaylovskaya, T.O. Kulinich

“…In the educational process teaching materials consist of the work program on the subject, methodological recommendations for independent work and workshops, for practical skills and algorithms for their implementation, tests of initial, current and final knowledge control, samples of basic records of general practice - family medicine, education and qualification characteristics of family doctor, a list of basic regulatory documents, educational literature. …”
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Analysis and reduction of topographic effect induced errors in land surface temperature retrieval over the Tibetan Plateau by Yuejie Zhang, Qinghong Sheng, Kerui Li, Bo Wang, Jun Li, Xiao Ling, Fan Gao

“…However, most retrieval algorithms assume a flat-surface thermal infrared radiation transfer equation (TIRTE), which introduces inevitable topographic induced in the TP’s complex terrain. …”
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An evaluation methodology for machine learning-based tandem mass spectra similarity prediction by Michael Strobel, Alberto Gil-de-la-Fuente, Mohammad Reza Zare Shahneh, Yasin El Abiead, Roman Bushuiev, Anton Bushuiev, Tomáš Pluskal, Mingxun Wang

“…Machine learning (ML) approaches have emerged as a promising technique to predict structural similarity from MS/MS that may surpass the current state-of-the-art algorithmic methods. However, the comparison between these different ML methods remains a challenge because there is a lack of standardization to benchmark, evaluate, and compare MS/MS similarity methods, and there are no methods that address data leakage between training and test data in order to analyze model generalizability. …”
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A Survey on Adversarial Attacks for Malware Analysis by Kshitiz Aryal, Maanak Gupta, Mahmoud Abdelsalam, Pradip Kunwar, Bhavani Thuraisingham

“…We systematically analyze adversarial generation algorithms from broader domains adapted to malware evasion attacks, proposing a taxonomy of adversarial evasion attacks within malware detection based on target domains(Windows, Android and PDF). …”
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Opening closed doors: using machine learning to explore factors associated with marital sexual violence in a cross-sectional study from India by Anita Raj, Abhishek Singh, Nandita Bhan, Lotus McDougal, Nabamallika Dehingia, Julian McAuley

“…Analyses included iterative thematic analysis (L-1 regularised regression followed by iterative qualitative thematic coding of L-2 regularised regression results) and neural network modelling.Outcome measure Participants reported their experiences of sexual violence perpetrated by their current (or most recent) husband in the previous 12 months. …”
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Research progress on shale gas productivity evaluation: concepts, methods and future directions by ZHU Suyang, PENG Zhen, DI Yunting, PENG Xiaolong, LIU Dongchen, GUAN Wenjie

“…In addition, further work is needed to incorporate mechanism-informed constraints into machine learning algorithms, enhance model transparency through causal inference, and improve interpretability. …”
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Fuzzy Controlled MPPT to Grid Connected PV Systems by Sukumar G. Durga, Prasad R. Ramanjan, Vardhan R. Harsha, Pakkiraiah B., Krishna Ch. Leela

“…The FLC-based MPPT system adeptly adjusts the PV system’s voltage, current, and power settings to harness the maximum feasible power output from the photovoltaic panels. …”
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The large, viscous thrombus is aspirated by using the cyclic suction technique by Lin Shenqi, Yu Ling, Hong Ruiting, Dong Runcheng, Liu Bohao, Ruan Wencong, Sun Tao, Zhou Dongqing, Zhou Yixuan, Chen Shi

“…Cardiovascular disease (CVD) risk factors have a growing impact on public health, and the incidence of CVD continues to rise. Current research focuses mainly on improving the safety and effectiveness of thrombectomy devices and reducing complications during surgical procedures. …”
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Self-Organizing Wireless Sensor Networks Solving the Coverage Problem: Game-Theoretic Learning Automata and Cellular Automata-Based Approaches by Franciszek Seredynski, Miroslaw Szaban, Jaroslaw Skaruz, Piotr Switalski, Michal Seredynski

“…In this paper, we focus on developing self-organizing algorithms aimed at solving, in a distributed way, the coverage problem in Wireless Sensor Networks (WSNs). …”
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Linking online activity to offline behavior: A meta-review of three decades of online-to-offline scholarship with future implications for AI by Scott Leo Renshaw, Kathleen M. Carley

“…As society grapples with the emerging significance and implications of Large Language Models (LLMs), such as OpenAI’s ChatGPT, or Google’s Gemini, as well as other advancements in modern generative Artificial Intelligence (AI), it is crucial to recognize the existing role that data, algorithms, and online social networks have already played in shaping our contemporary society. …”
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Energy Consumption Analysis of 5G C-V2X Sensor Sharing for Tele-Operated Driving by Hanyoung Park, Yongjae Jang, Kanghyun Ko, Ji-Woong Choi

“…However, due to the imperfections in current autonomous driving systems, incidents still occur, highlighting the challenges of full driverless services. …”
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Correspondence distribution over a network in designing public urban passenger transportation tasks by A. I. Fadeev, A. M. Iliankov, V. V. Ukaderov

“…The formation acceptable routes on the transport network can be carried out by means of the algorithms developed, for example, in the framework of solving TNDP and TNDFSP tasks. …”
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Schizophrenia Detection and Classification: A Systematic Review of the Last Decade by Arghyasree Saha, Seungmin Park, Zong Woo Geem, Pawan Kumar Singh

“…Background/Objectives: Artificial Intelligence (AI) in healthcare employs advanced algorithms to analyze complex and large-scale datasets, mimicking aspects of human cognition. …”
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Using fishery-related data, scientific expertise, and machine learning to improve marine habitat mapping in northeastern Mediterranean waters by Loukas Katikas, Sofia Reizopoulou, Paraskevi Drakopoulou, Vassiliki Vassilopoulou

“…The vast majority of marine seabed priority habitats in the study area appeared to fall outside the borders of the current Natura 2000 sites, which served as the baseline for the declared trawl bans in Greek waters, following the provisions of the EU Marine Action Plan.…”
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Monitoring the antibiotic resistance in the intensive care unit of a multidisciplinary hospital by V. Yu. Zemko, V. K. Okulich, A. M. Dzyadz’ko

“…It is necessary to monitor the resistance of common microorganisms to certain antibiotics in order to develop algorithms for rational antibacterial treatment in each hospital.…”
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Mental health promotion in disasters: exploring the synergy of artificial intelligence, spirituality, and psychology: a SWOT analysis by Rasoul Fattahipour, Simintaj Sharififar, Fatemeh Teymouri, Maryam Azizi, Milad Ahmadi Marzaleh

“…In contrast, threats such as data privacy risks, algorithmic biases, and ethical concerns around informed consent and over-standardization of care are also addressed. …”
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Practical applications of methods to incorporate patient preferences into medical decision models: a scoping review by Jakub Fusiak, Kousha Sarpari, Inger Ma, Ulrich Mansmann, Verena S. Hoffmann

“…Abstract Background Algorithms and models increasingly support clinical and shared decision-making. …”
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Ultrasound-based machine learning model to predict the risk of endometrial cancer among postmenopausal women by Yi-Xin Li, Yu Lu, Zhe-Ming Song, Yu-Ting Shen, Wen Lu, Min Ren

“…Three models were developed: (1) R model: radiomics-based machine learning (ML) algorithms; (2) CNN model: image-based CNN algorithms; (3) DLR model: a hybrid model combining radiomics and deep learning features with ML algorithms. …”
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