MSF-GhostNet: Computationally Efficient YOLO for Detecting Drones in Low-Light Conditions by Maham Misbah, Misha Urooj Khan, Zeeshan Kaleem, Ali Muqaibel, Muhamad Zeshan Alam, Ran Liu, Chau Yuen

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Effect of phosphorus fractions on benthic chlorophyll-a: Insight from the machine learning models by Yuting Wang, Sangar Khan, Zongwei Lin, Xinxin Qi, Kamel M. Eltohamy, Collins Oduro, Chao Gao, Paul J. Milham, Naicheng Wu

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Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis by Xingren Liu, Junmei Song, Shujin Guo, Yi Liao, Jun Zou, Liqing Yang, Caiyu Jiang

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The prevalence of resistance-associated mutations to protease and reverse transcriptase inhibitors in treatment-naïve (HIV1)-infected individuals in Casablanca, Morocco by Khadija Bakhouch, Ahd Oulad-Lahcen, Rajae Bensghir, Mohamed Blaghen, Kamal Marhoum Elfilali, Sayeh Ezzikouri, Omar Abidi, Mohamed Hassar, Lahcen Wakrim

“…National Agency for AIDS Research (ANRS) and Stanford HIV database algorithms were used for interpretation of resistance data. …”
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Quantitative Analysis of Lithium in Natural Brines from the Lithium Triangle by Laser-Induced Breakdown Spectroscopy by Juan Molina M., Carisa Sarchi, Alvaro Y. Tesio, César Costa-Vera, Diego M. Díaz Pace

“…Broadband emission spectra (180–900 nm) were recorded and spectrally analyzed by specially designed computational algorithms. The laser-induced plasmas were characterized by calculating the electron density and the temperature. …”
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Orchard-Wide Visual Perception and Autonomous Operation of Fruit Picking Robots: A Review by CHEN Mingyou, LUO Lufeng, LIU Wei, WEI Huiling, WANG Jinhai, LU Qinghua, LUO Shaoming

“…Each of these approaches incorporates advanced algorithms and sensor technologies for cluttered orchard environments. …”
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Cell‐free epigenomes enhanced fragmentomics‐based model for early detection of lung cancer by Yadong Wang, Qiang Guo, Zhicheng Huang, Liyang Song, Fei Zhao, Tiantian Gu, Zhe Feng, Haibo Wang, Bowen Li, Daoyun Wang, Bin Zhou, Chao Guo, Yuan Xu, Yang Song, Zhibo Zheng, Zhongxing Bing, Haochen Li, Xiaoqing Yu, Ka Luk Fung, Heqing Xu, Jianhong Shi, Meng Chen, Shuai Hong, Haoxuan Jin, Shiyuan Tong, Sibo Zhu, Chen Zhu, Jinlei Song, Jing Liu, Shanqing Li, Hefei Li, Xueguang Sun, Naixin Liang

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Machine Learning Model Based on Prognostic Nutritional Index for Predicting Long‐Term Outcomes in Patients With HCC Undergoing Ablation by Nan Zhang, Ke Lin, Bin Qiao, Liwei Yan, Dongdong Jin, Daopeng Yang, Yue Yang, Xiaohua Xie, Xiaoyan Xie, Bowen Zhuang

“…Conclusion The PNI‐based Aorsf model effectively predicts long‐term survival outcomes after ablation therapy, making a significant contribution to HCC research by improving surveillance, prevention, and treatment strategies.…”
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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

“…Given that lung cancer is a leading cause of cancer-related deaths globally and NSCLC accounts for the majority of lung cancer cases, understanding the relationship between TME and metabolic pathways in NSCLC is crucial for developing new treatment strategies.MethodsFinally, machine learning algorithms were employed to construct a risk signature with strong predictive power across multiple independent cohorts. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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Comparison of different downscaling schemes for obtaining regional high-resolution soil moisture data by Yulin Shangguan, Cheng Tong, Zhou Shi, Hongquan Wang, Xiaodong Deng

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Accuracy of warm ischemia time measurement using a surgical intelligence software in partial nephrectomies: A validation study by Archan Khandekar, Joao G. Porto, Jean C. Daher, Pedro F. S. Freitas, Dotan Asselman, Maritza M. Suarez, Mark L. Gonzalgo, Dipen J. Parekh, Sanoj Punnen

“…The platform utilized computer vision algorithms to detect clamp placement and removal, enabling precise WIT measurement. …”
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Using machine learning methods to investigate the role of volatile organic compounds in non-alcoholic fatty liver disease by Chih-Hao Shen, Ruei-Hao Huang, Yaw-Kuen Li, Ta-Wei Chu, Ta-Wei Chu, Dee Pei, Dee Pei

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Causes of embryo implantation failure: A systematic review and metaanalysis of procedures to increase embryo implantation potential by Francesco M. Bulletti, Romualdo Sciorio, Alessandro Conforti, Roberto De Luca, Carlo Bulletti, Antonio Palagiano, Marco Berrettini, Giulia Scaravelli, Roger A. Pierson

“…Subsequent studies ought to concentrate on modulating endometrial responses immunologically and developing algorithms to improve the precision of predicting implantation success; as well as the timing of endometrial receptivity and the occurrence of dormant embryo phenomena also warrants further investigation.…”
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Comprehensive profiling of chemokine and NETosis-associated genes in sarcopenia: construction of a machine learning-based diagnostic nomogram by Yingwei Wang, Le Wang, Yan Zhang, Minghui Wang, Huaying Zhao, Cheng Huang, Huaiyang Cai, Shuangyang Mo

“…Two machine learning algorithms and univariate analysis were integrated to screen signature genes, which were subsequently used to construct diagnostic nomogram models for sarcopenia. …”
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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review by Avneet Kaur, Gurjit S. Randhawa, Farhat Abbas, Mumtaz Ali, Travis J. Esau, Aitazaz A. Farooque, Rajandeep Singh

“…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. …”
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Identification of cellular senescence-associated genes for predicting the diagnosis, prognosis and immunotherapy response in lung adenocarcinoma via a 113-combination machine learn... by Ting Ge, Guixin He, Qian Cui, Shuangcui Wang, Zekun Wang, Yingying Xie, Yuanyuan Tian, Juyue Zhou, Jianchun Yu, Jinmin Hu, Wentao Li

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SbD4Skin by EosCloud: Integrating multi-view molecular representation for predicting skin sensitization, irritation, and acute dermal toxicity by Nikoletta-Maria Koutroumpa, Dimitra-Danai Varsou, Panagiotis D. Kolokathis, Maria Antoniou, Konstantinos D. Papavasileiou, Eleni Papadopoulou, Anastasios G. Papadiamantis, Andreas Tsoumanis, Georgia Melagraki, Milica Velimirovic, Antreas Afantitis

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Analysis of soil salinization and land use change under water conservation retrofit in the Hetao irrigation district by Yi Zhao, Shuya Yang, Haibin Shi, Haoqi Han, Yunlei Dong, Xianyue Li, Jianwen Yan, Yan Yan, Xu Dou, Feng Tian, Qingfeng Miao

“…We establish soil sampling sites in this region, employ Google Earth Engine algorithms to develop models for soil salinity inversion and land use classification, and analyze the change patterns of land salinization and land use types. …”
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Novel Insights into Non-Invasive Diagnostic Techniques for Cardiac Amyloidosis: A Critical Review by Marco Maria Dicorato, Paolo Basile, Giuseppe Muscogiuri, Maria Cristina Carella, Maria Ludovica Naccarati, Ilaria Dentamaro, Marco Guglielmo, Andrea Baggiano, Saima Mushtaq, Laura Fusini, Gianluca Pontone, Cinzia Forleo, Marco Matteo Ciccone, Andrea Igoren Guaricci

“…Finally, machine learning and artificial intelligence-derived algorithms are gaining ground in this scenario and provide the basis for future research. …”
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