Deep Learning in Written Arabic Linguistic Studies: A Comprehensive Survey by Manar Almanea

“…This article presents a comprehensive survey on recent applications of deep learning (DL) algorithms to written Arabic. Despite the increasing amount of user-generated content in Arabic, linguistic studies focusing on Arabic suffer from low analytical resources. …”
Get full text

Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census by Yilin Li, Cen Chen, Xiaoyu Ji, Ningxiao Jiang, Fei Wang, Xiangqian Gao, Weiwei Chen, Qiang Tang, Yan Li, Shinan Zhang, Gaofeng Qin, Yingjiang Xu, Yanlin Wang, Lingwen Kong, Lei Han, Jie Mei

“…We then developed the CSCI to predict the prognosis and response to immunotherapy in ovarian cancer patients using advanced machine learning algorithms. …”
Get full text

ML-Based Materials Evaluation in 3D Printing by Izabela Rojek, Dariusz Mikołajewski, Krzysztof Galas, Jakub Kopowski

“…Machine learning (ML) is transforming the evaluation of 3D printing materials, enabling more efficient and accurate assessment of material properties, including their sustainable life cycle. ML algorithms can analyze vast amounts of data from previous printing processes to predict the performance of different materials (including those used in multi-material printing) under different conditions. …”
Get full text

Monthly Electricity Generatıon Forecast in Solar Power Plants with LSTM by Ali Hakan Isık, Ömer Çetin

“…In the study, predictions and analyses were made using the LSTM (Long Short-Term Memory) method, which is one of the artificial neural networks. …”
Get full text

Artificial Intelligence—What to Expect From Machine Learning and Deep Learning in Hernia Surgery by Robert Vogel, Björn Mück

“…The term AI incorporates various technologies including ML, Neural Networks (NN), and DL. Classical ML algorithms depend on structured, labeled data for predictions, requiring significant human oversight. …”
Get full text

Optimizing Wheat Yields: AI and IoT Techniques for Continuous Agricultural Monitoring by Nandy Manish, Afzal Md

“…This data is analyzed using AI algorithms developed predictive models and actionable insights. …”
Get full text

Computational Estimation of Football Player Wages by Yaldo L., Shamir L.

“…The method is based on the application of pattern recognition algorithms to performance (e.g., scoring), behavior (e.g., aggression), and abilities (e.g., acceleration) data of football players. …”
Get full text

Artificial Intelligence and Machine Learning Approaches for Target-Based Drug Discovery: A Focus on GPCR-Ligand Interactions by M. O. Otun

“…We discuss various AI/ML algorithms, including supervised learning, deep learning, and reinforcement learning, and their applications in ligand-based and structure-based drug design. …”
Get full text

Opportunities and challenges of AI-systems in political decision-making contexts by Max Tretter

“…Furthermore, some of them have the power to carry out in-depth simulations with varying parameters, predicting the consequences of various political decisions, and thereby providing new certainties. …”
Get full text

Artificial Intelligence Applications in Pediatric Craniofacial Surgery by Lucas M. Harrison, Ragan L. Edison, Rami R. Hallac

“…Machine learning and deep learning models are increasingly used to analyze complex craniofacial imaging, enabling early detection of congenital anomalies such as craniosynostosis, and cleft lip and palate. AI-driven algorithms assist in preoperative planning by identifying anatomical abnormalities, predicting surgical outcomes, and guiding personalized treatment strategies. …”
Get full text

Predictors of Successful Testicular Sperm Extraction: A New Era for Men with Non-Obstructive Azoospermia by Aris Kaltsas, Sofoklis Stavros, Zisis Kratiras, Athanasios Zikopoulos, Nikolaos Machairiotis, Anastasios Potiris, Fotios Dimitriadis, Nikolaos Sofikitis, Michael Chrisofos, Athanasios Zachariou

“…Integrating molecular biomarkers with artificial intelligence and machine learning algorithms may enhance predictive accuracy. <b>Conclusions</b>: Predicting TESE outcomes in men with NOA remains challenging using conventional clinical and hormonal parameters. …”
Get full text

Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease by Daryll Philip, Rebecca Hodgkiss, Swarnima Kollampallath Radhakrishnan, Akshat Sinha, Animesh Acharjee

“…These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. …”
Get full text

On the Extrapolation of Generative Adversarial Networks for Downscaling Precipitation Extremes in Warmer Climates by Neelesh Rampal, Peter B. Gibson, Steven Sherwood, Gab Abramowitz

“…Abstract While deep‐learning downscaling algorithms can generate fine‐scale climate projections cost‐effectively, it is unclear how effectively they extrapolate to unobserved climates. …”
Get full text

Breeding of Solanaceous Crops Using AI: Machine Learning and Deep Learning Approaches—A Critical Review by Maria Gerakari, Anastasios Katsileros, Konstantina Kleftogianni, Eleni Tani, Penelope J. Bebeli, Vasileios Papasotiropoulos

“…AI has emerged as a powerful solution to overcome the limitations of traditional breeding techniques, which often involve time-consuming, resource-intensive processes with limited predictive accuracy. Through advanced algorithms and predictive models, ML and DL facilitate the identification and optimization of key traits, including higher yield, improved quality, pest resistance, and tolerance to extreme climatic conditions. …”
Get full text

Applications of machine learning-assisted extracellular vesicles analysis technology in tumor diagnosis by Liang Xu, Jing Li, Wei Gong

“…In recent years, machine learning (ML) technology in the medical field has gained momentum, which utilize various algorithms to analyze input data, identify potential patterns and trends, develop predictive models, and generate high-precision predictions of unknown data, demonstrating its clinical potential in disease diagnosis. …”
Get full text

A new method for internal urinary metabolite exposure and dietary exposure association assessment of 3-MCPD and glycidol and their esters based on machine learning by Yimei Tian, Sunan Gao, Fan Zhang, Xuzhi Wan, Wei Jia, Jingjing Jiao, Yilei Fan, Yu Zhang

“…We collected demographic data from 1587 participants and developed seven models using machine-learning algorithms to investigate urinary metabolite exposure and dietary exposure associations of 3-MCPD and glycidol and their esters. …”
Get full text

Estimating Import Lead Times Using Business Intelligence and Machine Learning Within the CRISP-DM Framework: A Case Study in Oil and Gas Services Industry by Mohamed Annis Souames, Larbi Abderrahmane Mohammedi, Iskander Zouaghi, Angappa Gunasekaran, Samia Beldjoudi, Abderrazak Laghouag

“…Addressing the challenge of limited data availability, we employ data synthesis techniques alongside machine learning algorithms to model and predict lead times accurately across diverse import scenarios. …”
Get full text

Applied Artificial Intelligence in Materials Science and Material Design by Emigdio Chávez‐Angel, Martin Børstad Eriksen, Alejandro Castro‐Alvarez, Jose H. Garcia, Marc Botifoll, Oscar Avalos‐Ovando, Jordi Arbiol, Aitor Mugarza

“…By leveraging large datasets, AI algorithms can identify patterns, reduce noise, and predict material behavior with unprecedented accuracy. …”
Get full text

Model Design for Personnel Selection with Data Mining Approach (Case Study: A Commerce Bank of Iran) by Adel Azar, Parviz Ahmadi, Mohammad Vahid Sebt

“…Rules Derivation has been accomplished by the QUEST, CHAID, C5.0 and CART algorithms. The objective and the appropriate algorithms are determined based on seemingly “irrelevant” components, which the Commerce Bank Human Resources management experts described. …”
Get full text

Gesture recognition based on flexible solar cells and ultrathin hydrogel film by Rucheng WU, Wenbo DING, Xiaomin XU, Linqi SONG, Weitao XU

“…Daily life involves various gestures, and combining these with smart wearable devices is crucial for improving quality of life.One effective solution to the challenges of gesture recognition and device energy consumption isutilizing the photoelectric conversion characteristics of solar energy-related devices.The data of five commonly used gestures were collected in the research of the combination of flexible solar cells and gesture recognition.Z-Score, low-pass filter, sliding window techniques for signal processing were applied, and successfully achieved 100% predicted accuracy using random forest, support vector machine and neural network algorithms even with small samples which showed that this method had significant advantages in the application of gesture recognition.…”
Get full text