Cross-species AI: shifting a convolutional neural network from pigs to lambs to detect pneumonia at slaughter by Anastasia Romano, Antonio De Camillis, Domenico Sciota, Simona Baghini, Andrea Di Provvido, Alfonso Rosamilia, Andrea Capobianco Dondona, Nicola Bernabò, Francesca Vaccarelli, Attilio Corradi, Giuseppe Marruchella

“…However, the systematic detection and recording of lesions at postmortem inspection are expensive, time consuming, somewhat biased by inter- and/or intra-observers’ variability. …”
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Enhancing Water Bodies Detection in the Highland and Coastal Zones Through Multisensor Spectral Data Fusion and Deep Learning by Xiaofei Han, Nazih Y. Rebouh, Yasmeen Ahmed, Muhammad Nasar Ahmad, Zainab Tahir, Yahia Said, Ishfaq Gujree

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TransLIBS-CRS: Integrating LIBS with transfer learning for accurate cross-regional soil total nitrogen detection by Peng Lin, Shixiang Ma, Zhizheng Shi, Peiying Li, Leizi Jiao, Hongwu Tian, Zhen Xing, Chunjiang Zhao, Daming Dong

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DSCnet: detection of drug and alcohol addiction mechanisms based on multi-angle feature learning from the hybrid representation of EEG by Jing Wu, Nan Zhang, Qilei Ye, Xiaorui Zheng, Minmin Shao, Xian Chen, Hui Huang

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Non-Destructive Detection of Fillet Fish Quality Using MQ135 Gas Sensor and Neutrosophic Logic-Enhanced System by M. Y. Shams, M. R. Darwesh, Roheet Bhatnagar, N. S. A. Al-Sattary, A. A. Salama, M. S. Ghoname

“…These methods, combining electronic nose technology, artificial intelligence, and neutrosophic inference, provide a robust, non-destructive, and cost-effective approach to detecting spoilage in fillet fish. …”
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Integrating AIoT Technologies in Aquaculture: A Systematic Review by Fahmida Wazed Tina, Nasrin Afsarimanesh, Anindya Nag, Md Eshrat E. Alahi

“…This review explores the transformative role of the Artificial Intelligence of Things (AIoT) in mitigating these challenges. …”
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Biomarker discovery and development of prognostic prediction model using metabolomic panel in breast cancer patients: a hybrid methodology integrating machine learning and explaina... by Fatma Hilal Yagin, Yasin Gormez, Fahaid Al-Hashem, Irshad Ahmad, Fuzail Ahmad, Luca Paolo Ardigò

“…Although the important role of metabolism in the molecular pathogenesis of BC is known, there is still a need for robust metabolomic biomarkers and predictive models that will enable the detection and prognosis of BC. This study aims to identify targeted metabolomic biomarker candidates based on explainable artificial intelligence (XAI) for the specific detection of BC.MethodsData obtained after targeted metabolomics analyses using plasma samples from BC patients (n = 102) and healthy controls (n = 99) were used. …”
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Fault Detection and Diagnosis in Air-Handling Unit (AHU) Using Improved Hybrid 1D Convolutional Neural Network by Prince, Byungun Yoon, Prashant Kumar

“…While conventional convolutional neural networks (CNNs) effectively detect defects, incorporating more spatial variables could enhance their performance further. …”
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Deep learning analysis for rheumatologic imaging: current trends, future directions, and the role of human by Jucheol Moon, Pratik Jadhav, Sangtae Choi

“…Traditional imaging techniques, including plain radiography, ultrasounds, computed tomography, and magnetic resonance imaging (MRI), play a critical role in diagnosing and monitoring these conditions, but face limitations like inter-observer variability and time-consuming assessments. Recently, deep learning (DL), a subset of artificial intelligence, has emerged as a promising tool for enhancing medical imaging analysis. …”
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Deep Learning Techniques for Lung Cancer Diagnosis with Computed Tomography Imaging: A Systematic Review for Detection, Segmentation, and Classification by Kabiru Abdullahi, Kannan Ramakrishnan, Aziah Binti Ali

“…Computed tomography (CT) imaging plays a vital role in detection, and deep learning (DL) has emerged as a transformative tool to enhance diagnostic precision and enable early identification. …”
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Adaptive Global Dense Nested Reasoning Network into Small Target Detection in Large-Scale Hyperspectral Remote Sensing Image by Siyu Zhan, Yuxuan Yang, Muge Zhong, Guoming Lu, Xinyu Zhou

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Optimal Selection Criterion for Runoff Component Models Based on Benefit-Risk Balance by DING Xiao-ling, HU Wei-zhong, TANG Hai-hua, LUO Bin, FENG Kuai-le

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Emotional intelligence and its associated factors among case team leaders in health centers of East Gojam Zone, Northwest Ethiopia: an institutional based cross-sectional study by Endalew Minwuye Andargie, Seblewongel Gebretsadik Sertsewold, Tamiru Minwuye Andargie, Haimanot Wubale Tewabe, Asrat Kassaw, Yonas Fissha Adem, Wubshet D. Negash

“…Data was entered into Epi-Data version 4.6 and exported further into STATA version 14.0 for analysis. Multi-variable binary logistic regression model was employed to determine factors associated with EI, and statistical significance was detected with P-value < 0.05 and 95% CI. …”
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Advanced Deep Learning Approaches in Detection Technologies for Comprehensive Breast Cancer Assessment Based on WSIs: A Systematic Literature Review by Qiaoyi Xu, Afzan Adam, Azizi Abdullah, Nurkhairul Bariyah

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Conceptualizing Clinicians&#x2019; Trust in Artificial Intelligence as a Function of Their Expertise, Workload, Patient Outcome, Diagnosis Difficulty, and AI Accuracy: A Systems Th... by Hamid Shamszare, Zaira Chaudhry, Manijeh Berenji, Avishek Choudhury

“…This may be attributed to their enhanced ability to detect AI errors, allowing for more calibrated and resilient trust. …”
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Optimization of a multi-environmental detection model for tomato growth point buds based on multi-strategy improved YOLOv8 by Jiang Liu, Jingxin Yu, Changfu Zhang, Huankang Cui, Jinpeng Zhao, Wengang Zheng, Fan Xu, Xiaoming Wei

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A Novel Long Short-Term Memory-Based Approach for Microgrid Fault Detection and Classification Using the Wavelet Scattering Transform by Naema M. Mansour, Abdelazeem A. Abdelsalam, Ibrahim A. Awaad

“…During islanded operation, a common mode in microgrids, fault currents are often reduced, making fault detection and isolation even more difficult. These limitations underscore the urgent need for intelligent, adaptive, and fast-responding fault detection and classification algorithms tailored specifically to the nature of microgrids. …”
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Versatile waste sorting in small batch and flexible manufacturing industries using deep learning techniques by Arso M. Vukicevic, Milos Petrovic, Nebojsa Jurisevic, Marko Djapan, Nikola Knezevic, Aleksandar Novakovic, Kosta Jovanovic

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Status and perceptions of ChatGPT utilization among medical students: a survey-based study by Na Hu, Xiao Qin Jiang, Yi Da Wang, Yan Ming Kang, Zhen Xia, Hao Hui Chen, Sai Nan Duan, Dong Xu Chen

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Machine Learning-Based Prediction of No-Show Telemedicine Encounters by C. Mahony Reategui-Rivera, Wanting Cui, Stefan Escobar-Agreda, Leonardo Rojas-Mezarina, Joseph Finkelstein

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