Sentiment analysis of the Hamas-Israel war on YouTube comments using deep learning by Ashagrew Liyih, Shegaw Anagaw, Minichel Yibeyin, Yitayal Tehone

“…For classification model building, commonly used classification algorithms LSTM, Bi-LSTM, GRU, and Hybrid of CNN and Bi-LSTM were applied, and their performance is compared. …”
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Leveraging mRNA technology for antigen based immuno-oncology therapies by Wei Zheng, Michele Ceccarelli, Charalampos S Floudas, Siranush Sarkizova

“…The identification and prioritization of patient-specific tumor neoantigens are based on advanced computational algorithms taking advantage of the profiling with next-generation sequencing considering factors involved in human leukocyte antigen (HLA)-peptide-T-cell receptor (TCR) complex formation, including peptide presentation, HLA-peptide affinity, and TCR recognition. …”
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PaleAle 6.0: Prediction of Protein Relative Solvent Accessibility by Leveraging Pre-Trained Language Models (PLMs) by Wafa Alanazi, Di Meng, Gianluca Pollastri

“…In particular, recent breakthroughs in deep learning—driven by the integration of natural language processing (NLP) algorithms—have significantly advanced the field of protein research. …”
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Wireless sensor networks and structural health monitoring: Experiences with slab track infrastructures by Eduardo Cañete, Jaime Chen, Manuel Díaz, Luis Llopis, Bartolomé Rubio

“…On arrival at the station, the data are stored in a database, which is queried by an application to extract relevant information by means of analysis algorithms to detect and predict failures. The first real scenario tests the limits of the system under stress situations. …”
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Model of forecasting of material resources and estimated cost at early stages of life cycle of construction objects by M. V. Gureev, A. N. Makarov

“…To prepare and train AI models based on Python, the methods of the scikit-learn library were selected to compare the following mathematical models: decision trees, regressions and algorithms based on boosting.Results. The training and research were conducted using the automated machine learning (AutoML) method. …”
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Metabolic Syndrome Prediction Using Machine Learning Models with Genetic and Clinical Information from a Nonobese Healthy Population by Eun Kyung Choe, Hwanseok Rhee, Seungjae Lee, Eunsoon Shin, Seung-Won Oh, Jong-Eun Lee, Seung Ho Choi

“…A prediction model for MS was designed for a nonobese population using clinical and genetic polymorphism information with five machine learning algorithms, including naïve Bayes classification (NB). …”
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Optimizing Hydrogen Production in the Co-Gasification Process: Comparison of Explainable Regression Models Using Shapley Additive Explanations by Thavavel Vaiyapuri

“…This study aims to bridge these gaps through two primary objectives: (1) modeling the co-gasification process using seven different ML algorithms, and (2) developing a framework for evaluating model interpretability, ultimately identifying the most suitable model for process optimization. …”
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Zooming into Berlin: tracking street-scale CO2 emissions based on high-resolution traffic modeling using machine learning by Max Anjos, Fred Meier

“…Here, we introduce a ML-based bottom-up framework to predict hourly CO2 emissions from vehicular traffic at fine spatial resolution (30 × 30 m). Using data-driven algorithms, traffic counts, spatio-temporal features, and meteorological data, our model predicted hourly traffic flow, average speed, and CO2 emissions for passenger cars (PC) and heavy-duty trucks (HDT) at the street scale in Berlin. …”
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Autopilot control unmanned aerial vehicle system for sewage defect detection using deep learning by Binay Kumar Pandey, Digvijay Pandey, S. K. Sahani

“…In order to get rid of the false negative outcome or false positive outcome, a guided image filter (GIF) is implemented in this proposed method during the pre‐processing stage. Afterwards, the algorithms Gabor transform (GT) and stroke width transform (SWT) were used to obtain the features of the UAV‐captured surveillance image. …”
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Real-Time Compression Scheme for Urban Rail Transit Train Operation Data by LI Dexiang, WANG Linmei, WANG Shu

“…The scheme is proved to be effective by the real-time verification test of algorithms and the verification test of the actual train operation data. …”
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Design and Analysis of a Serial Manipulator for Pick and Drop Objects for Material Handling at Uiri Metal Forming Workshop. by Behangana, Abert

“…Future recommendations include refining control algorithms, integrating advanced safety features, and exploring innovative materials to improve performance. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. …”
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Regulation of reactive oxygen species and the role of mitochondrial apoptotic-related genes in rheumatoid arthritis by Conghui Gao, Chengqiang Zhang, Lixing Wen, Gailian Zhang, Xiaoping Liu, Jie Wang, Luping Cui, Rui Li, Tingting Nie, Jiaoniu Duan, Yingying Guo

“…Gene Expression Ontology (GEO)-derived RA datasets were used to identify differentially expressed genes (DEGs) compared to normal controls, intersected with MARGs to obtain differentially expressed mitochondrial apoptosis-related genes (DE-MARGs). Three ML algorithms screened diagnostic biomarkers. A nomogram was built and validated by receiver operating characteristic (ROC) analysis. …”
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REVOLUTIONIZING LUXURY: THE ROLE OF AI AND MACHINE LEARNING IN ENHANCING MARKETING STRATEGIES WITHIN THE TOURISM AND HOSPITALITY LUXURY SECTORS by Maria Nascimento CUNHA, Manuel PEREIRA, António CARDOSO, Jorge FIGUEIREDO, Isabel OLIVEIRA

“…While the industry benefits from technological advancements, there are ongoing challenges such as concerns over data privacy and the need for constant updates to algorithms to keep pace with evolving market conditions.…”
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Control of multi-level quadratic DC-DC boost converter for photovoltaic systems using type-2 fuzzy logic technique-based MPPT approaches by Souheyb Mohammed Belhadj, Bouziane Meliani, Habib Benbouhenni, Sarra Zaidi, Z.M.S. Elbarbary, Mohammed M. Alammer

“…The proposed MPPT-T2FLC addresses key limitations of traditional MPPT methods, including the oscillations near the maximum power point (MPP) in incremental conductance (IC) algorithms and the reduced precision of type-1 fuzzy logic (T1FL) controllers under uncertain environmental conditions. …”
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MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects by Domenico Lofù, Paolo Sorino, Tommaso Colafiglio, Caterina Bonfiglio, Rossella Donghia, Gianluigi Giannelli, Angela Lombardi, Tommaso Di Noia, Eugenio Di Sciascio, Fedelucio Narducci

“…This selection is achieved through Recursive Feature Elimination (RFE) using a Random Forest (RF) to train Machine Learning (ML) algorithms and provide a mortality risk (Yes/No) output. …”
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Molecularly redefining small bowel adenocarcinoma to accelerate precision patient care – protocol of a multicenter observational cohort biomarker study by Rasmus Haunstrup Døssing, Julia Johanna Almer Broman, Colm J. O’Rourke, Elizaveta Mitkina Tabaksblat, Jesper Bøje Andersen, Carsten Palnæs Hansen, Tim Svenstrup Poulsen, Estrid V. S. Høgdall, Jakob Hagen Vasehus Schou, Dan Høgdall

“…Secondary outcomes include correlating these subgroups with clinical features, treatment responses, and patient outcomes. Machine learning algorithms will be employed for bioinformatic analyses to interpret molecular data. …”
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Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach by Shuai Liu, Peng Zhang, Anbin Wang, Keke Tang, Shuo Chen, Chensen Lin

“…This leads to significant economic and time costs, while the complexity of instruments and algorithms further raises the barrier for DLD design and optimization. …”
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Optimization Techniques for Physician Scheduling Problem: A Systematic Review of Recent Advancements and Future Directions by Norizal Abdullah, Masri Ayob, Meng Chun Lam, Nasser R. Sabar, Graham Kendall, Mohamad Khairulamirin Md Razali

“…Future research directions are outlined, emphasizing the need for more scalable algorithms, real-time scheduling capabilities, improved user interfaces, and comprehensive validation studies. …”
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Leveraging AI to improve disease screening among American Indians: insights from the Strong Heart Study by Paul Rogers, Thomas McCall, Ying Zhang, Jessica Reese, Dong Wang, Weida Tong

“…Research projects into the health of the American Indian frequently develop Machine learning algorithms as predictors of conditions in this population. …”
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