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

“…In contrast, DL, a subset of ML, generally leverages unlabeled, raw data such as images and videos to autonomously identify patterns and make intricate deductions. This process is enabled by neural networks used in DL, where hidden layers between the input and output capture complex data patterns. …”
Get full text

Dynamic Network Plasticity and Sample Efficiency in Biological Neural Cultures: A Comparative Study with Deep Reinforcement Learning by Moein Khajehnejad, Forough Habibollahi, Alon Loeffler, Aswin Paul, Adeel Razi, Brett J. Kagan

Get full text

An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

Get full text

Application of artificial intelligence in insect pest identification - A review by Sourav Chakrabarty, Chandan Kumar Deb, Sudeep Marwaha, Md. Ashraful Haque, Deeba Kamil, Raju Bheemanahalli, Pathour Rajendra Shashank

“…AI-based detection methods use machine learning, deep learning algorithms, and computer vision techniques to automate and improve the identification of insects. …”
Get full text

Identification and validation of hub genes related to neutrophil extracellular traps-mediated cell damage and immune recruitment during abdominal aortic aneurysm by Chuanlong Lu, Heng Wang, Maolin Qiao, Runze Chang, Jinshan Chen, Lizheng Li, Keyi Fan, Sheng Yan, Ruijing Zhang, Honglin Dong

“…We performed an analysis on the infiltration of immune cells within the AAA transcriptome dataset, employing CIBERSORT and ssGSEA algorithms (GSE183464). Next, the gene expression patterns associated with NETs formation (GSE178883) were utilized to examine the physiological processes in peripheral blood neutrophils post-PMA (Phorbol 12-myristate 13-acetate) induction. …”
Get full text

Study Comparison Deep Learning and Support Vector Machine for Face Mask Detection by Rani Kurnia Putri, Muhammad Athoillah*

“…Both algorithms have proven to be powerful tools for any classification problem specially to classify or identify image patterns. …”
Get full text

Enhancing convolutional neural networks in electroencephalogram driver drowsiness detection using human inspired optimizers by Anupam Yadav, Rifat Hussain, Madhu Shukla, Jayaprakash B, Rishiv Kalia, S. Prince Mary, Chou-Yi Hsu, Manoj Kumar Mishra, Kashif Saleem, Mohammed El-Meligy

“…To address this issue, researchers have explored electroencephalogram (EEG)-based detection systems. …”
Get full text

Application of artificial intelligence in modern healthcare for diagnosis of autism spectrum disorder by Abdullah H. Al-Nefaie, Abdullah H. Al-Nefaie, Theyazn H. H. Aldhyani, Theyazn H. H. Aldhyani, Sultan Ahmad, Eidah M. Alzahrani

“…In this research, ResNet50, Inception-V3, and VGG-19 models were used to identify autism based on the facial traits of children. …”
Get full text

EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…AI-based recommendation platforms such as Semantic Scholar and Scite simplify scientists' ability to locate pertinent literature by analyzing citation patterns and trend research. Open-access journals also leverage AI to increase content published therein and make it more accessible and readable to audiences, thereby democratizing knowledge dissemination. …”
Get full text

Advancing Neurodegenerative Disease Management: Technical, Ethical, and Regulatory Insights from the NeuroPredict Platform by Marilena Ianculescu, Lidia Băjenaru, Ana-Mihaela Vasilevschi, Maria Gheorghe-Moisii, Cristina-Gabriela Gheorghe

“…Through the integration of wearable physiological sensors, motion sensors, and neurological assessment tools, the NeuroPredict platform harnesses AI and smart sensor technologies to enhance the management of specific neurodegenerative diseases. Machine learning algorithms process these data flows to find patterns that point out disease evolution. …”
Get full text

Supervised Anomaly Detection in Univariate Time-Series Using 1D Convolutional Siamese Networks by Ayan Chatterjee, Vajira Thambawita, Michael A. Riegler, Pal Halvorsen

“…The model uses a contrastive loss function to compare input sequences and adjusts network weights iteratively during training to recognize intricate patterns. Additionally, we evaluated various univariate time-series forecasting algorithms on datasets with and without anomalies. …”
Get full text

Backfire Effect Reveals Early Controversy in Online Media by Songtao Peng, Tao Jin, Kailun Zhu, Qi Xuan, Yong Min

“…Our work highlights a new psychological perspective on conflict behavior in online discussions and bridges behavioral patterns and computational modeling.…”
Get full text

Multi-Stage Data-Driven Framework for Customer Journey Optimization and Operational Resilience by Tzu-Chien Wang, Ruey-Shan Guo, Chialin Chen, Chia-Kai Li

“…Optimizing customer journeys is a critical challenge in e-commerce and financial services, attracting attention from marketing, operations research, and business analytics. Traditional customer analytics models, such as rule-based segmentation and regression models, rely heavily on structured transactional data, limiting their ability to capture latent behavioral patterns and adapt to multi-channel dynamics. …”
Get full text

Adaptation of k-means to automated forecasting of poorly structured time series of economic dynamics by Dunskaia Lada, Popova Elena

“…We confirmed that use and integration of well-known clustering methods into the linear cellular automaton algorithm allows to identify patterns and improve the quality of the forecast. …”
Get full text

ADPO: Adaptive DRAM Controller for Performance Optimization by Zhuorui Liu, Yan Li, Xiaoyang Zeng

“…The research methodology involves implementing a rank-level timing aware read/write turnaround arbiter and setting read/write queue thresholds and read/write turnaround settings based on observed patterns. …”
Get full text

A Comprehensive Approach to Synthetic Distribution Grid Generation: Erdős–Rényi to Barabási-Albert by Mohammad Shahraeini

“…To address these limitations and push the research forward, the new algorithm utilizes the Barabási-Albert model to provide more control over the structural features of the generated graphs through the introduction of a novel tuning parameter known as the “richness index”. …”
Get full text

A predictive analytics framework for opportunity sensing in stock market by Shruti Mittal, C.K. Nagpal

“…Thus research papers in this area suffer from multiple limitations: Very short prediction period from one day to one week, consideration of few stocks only instead of whole of stock market spectrum, exploration of more suitable machine learning algorithms. …”
Get full text

Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture by Saha Laboni, Dubey Ahilya

“…The objective of this research is to explore the use of advanced artificial intelligence (AI) technologies for creating smart irrigation system to enhance water efficacy in agriculture. …”
Get full text

Causal estimation of the relationship between reproductive performance and the fecal bacteriome in cattle by Yutaka Taguchi, Haruki Yamano, Yudai Inabu, Hirokuni Miyamoto, Koki Hayasaki, Noriyuki Maeda, Yoshiro Kanmera, Seiji Yamasaki, Noboru Ota, Kenji Mukawa, Atsushi Kurotani, Shigeharu Moriya, Teruno Nakaguma, Chitose Ishii, Makiko Matsuura, Tetsuji Etoh, Yuji Shiotsuka, Ryoichi Fujino, Motoaki Udagawa, Satoshi Wada, Jun Kikuchi, Hiroshi Ohno, Hideyuki Takahashi

Get full text

A Novel Detection-and-Replacement-Based Order-Operator for Differential Evolution in Solving Complex Bound Constrained Optimization Problems by Sichen Tao, Sicheng Liu, Shoya Ohta, Ruihan Zhao, Zheng Tang, Yifei Yang

“…The design of differential evolution (DE) operators has long been a key topic in the research of metaheuristic algorithms. This paper systematically reviews the functional differences between mechanism improvements and operator improvements in terms of exploration and exploitation capabilities, based on the general patterns of algorithm enhancements. …”
Get full text