Reliability Assessment of PM2.5 Concentration Monitoring Data: A Case Study of China by Hongyan Duan, Wenfu Yue, Weidong Li

“…These models effectively captured complex patterns and detected anomalies related to both natural environmental and socioeconomic factors, as well as potential data manipulation. …”
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Intra- and peri-tumoral radiomics based on dynamic contrast-enhanced MRI for prediction of benign disease in BI-RADS 4 breast lesions: a multicentre study by Yalan Hu, Zhenhai Cai, Nijiati Aierken, Yueqi Liu, Nan Shao, Yawei Shi, Mengmeng Zhang, Yangling Hu, Xiaoling Zhang, Ying Lin

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Quantifying nocturnal thrush migration using sensor data fusion between acoustics and vertical‐looking radar by Silvia Giuntini, Juha Saari, Adriano Martinoli, Damiano G. Preatoni, Birgen Haest, Baptiste Schmid, Nadja Weisshaupt

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Flexible imputation toolkit for electronic health records by Alireza Vafaei Sadr, Jiang Li, Wenke Hwang, Mohammed Yeasin, Ming Wang, Harold Lehmann, Ramin Zand, Vida Abedi

“…This study highlights the importance of considering data distribution patterns when selecting imputation algorithms. Pympute addresses this challenge by offering a versatile and user-friendly solution for diverse EHR data scenarios.…”
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A Prediction–Interaction–Driving Framework for Ecosystem Services Under Climate Change and Human Activities: A Case Study of Zoigê Plateau by Wanting Zeng, Li He, Zhengwei He, Yang Zhao, Yan Yuan, Jintai Pang, Jiahua Zhao

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A bibliometric analysis of artificial intelligence applied to cervical cancer by Qiang Huang, Wenmei Su, Shujun Li, Yanming Lin, Zhen Cheng, Yuting Chen, Yanli Mo

“…Bibliometric analysis was performed using CiteSpace and VOSviewer to assess publication trends, authorship, country and institutional contributions, journal sources, and keyword co-occurrence patterns.ResultsFrom 1996 to 2024, our analysis of 770 publications on cervical cancer and AI showed a surge in research, with 86% published in the last 5 years. …”
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Tracking Poultry Drinking Behavior and Floor Eggs in Cage-Free Houses with Innovative Depth Anything Model by Xiao Yang, Guoyu Lu, Jinchang Zhang, Bidur Paneru, Anjan Dhungana, Samin Dahal, Ramesh Bahadur Bist, Lilong Chai

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Exploring the VAK model to predict student learning styles based on learning activity by Ahmed Rashad Sayed, Mohamed Helmy Khafagy, Mostafa Ali, Marwa Hussien Mohamed

“…To accomplish this goal, we have proposed an integrated system which encompasses the use of machine learning (ML) algorithms. This hybrid model is aimed at linking various activities to VAK model of learning and hence place students in their various class learning preferences derived from their activities and the patterns created during the learning processes. …”
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Prediction of Rice Yields in a Changing Climate Using the Mobile Rice Yield Prediction Application by Mohamad Farhan Mohamad Mohsin, Mohamad Ghozali Hassan, Kamal Imran Mohd Sharif, Mohd Azril Ismail, Liew Jun Hong, Muhammad Khalifa Umana, Hairazi Rahim@Abdul Rahim

“… In Malaysia, rice production is crucial for national food security but faces significant challenges due to unpredictable climate patterns and climate change. Traditional prediction methods often struggle to capture the complex interaction between climatic and agricultural factors that cause a critical gap in accurately forecasting rice yields. …”
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Leveraging Artificial Intelligence and Radiomics for Improved Nasopharyngeal Carcinoma Prognostication by Nicholas Brian Shannon, Narayanan Gopalakrishna lyer, Melvin Lee Kiang Chua

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EsoDetect: computational validation and algorithm development of a novel diagnostic and prognostic tool for dysplasia in Barrett’s esophagus by Migla Miskinyte, Benilde Pondeca, José B. Pereira-Leal, Joana Cardoso

“…Datasets containing gene expression data from metaplastic and dysplastic BE, as well as EAC tissue samples, were collected from public databases and used to explore gene expression patterns that differentiate between non-dysplastic (ND) and LGD BE (for diagnostic purposes) and between non-progressed and progressed BE (for prognostic purposes). …”
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Assessment of Large‐Scale Reservoirs' Impact on the Local Precipitation by Han Zhou, Jun Qiu, Mengjia Li, Houliang Lu, Fangfang Li

“…Further comparisons suggest that reservoir operation shifts the key influencing factors of local precipitation patterns from those characterized by high variability to those characterized by low variability. …”
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Klasifikasi Metode Data Mining untuk Prediksi Kelulusan Tepat Waktu Mahasiswa dengan Algoritma Naïve Bayes, Random Forest, Support Vector Machine (SVM) dan Artificial Neural Nerwor... by Satrio Junaidi, Rani Valicia Anggela, Delsi Kariman

“…So, to deal with this problem, data mining classification is carried out to predict student graduation on time to find patterns for student on-time graduation predictions. …”
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Personalized diagnosis of radiation pneumonitis in breast cancer patients based on radiomics by Xiaobo Wen, Xiaobo Wen, Xiaobo Wen, Yutao Zhao, Wen Dong, Congbo Yang, Jinzhi Li, Li Sun, Yutao Xiu, Chang’e Gao, Ming Zhang

“…Five texture-oriented and four first-order features were retained, underscoring the importance of texture-focused extractors [wavelet and local binary pattern (LBP)].ConclusionCT-derived radiomic signatures combined with machine learning classifiers enable the accurate detection of RP in breast cancer patients. …”
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Accurate Detection of scutellata‐Hybrids (Africanized Bees) Using a SNP‐Based Diagnostic Assay by Kathleen A. Dogantzis, Harshilkumar Patel, Stephen Rose, Ida M. Conflitti, Alivia Dey, Tanushree Tiwari, Nadine C. Chapman, Samir M. Kadri, Harland M. Patch, Elliud M. Muli, Abdulaziz S. Alqarni, Michael H. Allsopp, Amro Zayed

“…Here, we used an extensive population genomic dataset to assess the genomic composition of Apis mellifera native populations and patterns of genetic admixture in North and South American commercial honey bees. …”
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Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

“…The integration of SHAP enabled transparent feature attribution, revealing distinctive exposure patterns linked to urban topology, population density, and built environment metrics. …”
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Optimizing Air Pollution Forecasting Across Temporal Scales: A Case Study in Salamanca, Mexico by Francisco-Javier Moreno-Vazquez, Felipe Trujillo-Romero, Amanda Enriqueta Violante Gavira

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Regulatory T cells and matrix-producing cancer associated fibroblasts contribute on the immune resistance and progression of prognosis related tumor subtypes in ccRCC by Chao Zhang, Yisu Song, Xiaobo Cui, Yina Wang, Jiang Liu, Zhouji Shen

“…The distinct activated transcription factor patterns were uncovered as well as the essential ligand-receptor pairs in the interactions among different cell subtypes, such as CXCL12-CXCR4 and COL6A2-SDC4. …”
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The Use of Artificial Intelligence to Analyze the Exposome in the Development of Chronic Diseases: A Review of the Current Literature by Stefania Isola, Giuseppe Murdaca, Silvia Brunetto, Emanuela Zumbo, Alessandro Tonacci, Sebastiano Gangemi

“…Under such premises, this study reviews the use of AI in analyzing the exposome to understand its role in the development of chronic diseases, focusing on how AI can identify patterns in exposure-related data and support prevention strategies. …”
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Obstacle Avoidance in Healthy Adults and People With Multiple Sclerosis: Preliminary fNIRS Study by Fares Al-Shargie, Michael Glassen, John DeLuca, Soha Saleh

“…The findings revealed distinct patterns of cortical activation and connectivity for each task condition in both groups. …”
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