Precision Agriculture: Utilizing Machine Learning for Accurate Plant Disease Diagnosis by Divya Banti, Tandan Gajendra

“…Mobile applications with ML algorithms also enable on the spot plant disease diagnosis from the smartphone camera, enabling site rather than later intervention. …”
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AI-powered Somatic Cancer Cell Analysis for Early Detection of Metastasis: The 62 principal Cancer Types by Sandile Buthelezi, Solly Matshonisa Seeletse, Taurai Hungwe, Vimbai Mbirimi-Hungwe

“…Objective: To emphasize the importance of early metastasis detection in improving cancer patient outcomes, and to highlight that recent advancements in AI-powered somatic cancer cell analysis may enhance early detection and personalize treatment strategies. …”
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Beyond the STI clinic: Use of administrative claims data and machine learning to develop and validate patient-level prediction models for gonorrhea by Lorenzo Argante, Germain Lonnet, Emmanuel Aris, Jane Whelan

“…ML classification models were constructed based on logistic regression and tree-based algorithms. Results Models constructed using tree-based algorithms such as XGBoost provided the best discriminatory results, but simpler ridge regressions models with splines also achieved reasonable discrimination, allowing for the identification of population subsets at increased risk of gonorrhea infection. …”
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Performance Comparison of Support Vector Machine (SVM) and k-Nearest Neighbors (kNN) in Verifying Material Orientation by Eldio Utama, Eko Rudiawan Jamzuri

“…For instance, in the beverage industry, incorrect orientation of materials, such as bottle caps, can lead to failures in the packaging process, resulting in improperly sealed bottles that may compromise product quality and safety. This study compares the performance of Support Vector Machine (SVM) and k-Nearest Neighbors algorithms for verifying material orientation verification through automated optical inspection. …”
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Teaching a neural network modeling socio-economic development of the region by S. V. Romanchukov, O. G. Berestneva, L. A. Petrova

“…At the same time, however, it should be noted that the resources of an individual research team may be (and most likely will be) insufficient to create their own software solution for the implementation of machine learning algorithms from scratch. …”
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Recent Results on the Use of Artificial Intelligence Techniques Applied to Wireless Power Transfer Systems by Federico Amadei, Michele Quercio, Francesco Riganti Fulginei

“…Additionally, ML is being used for foreign object detection (FOD) to ensure safety by identifying metallic and living objects that may interfere with power transmission. The article discusses various approaches, including supervised learning, regression models, and Q-learning algorithms, highlighting their ability to reduce design time, improving system efficiency, and mitigate risks associated with misalignment and object interference. …”
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Prediction of ultimate load capacity of demountable shear stud connectors using machine learning techniques by Ahmed I. Saleh, Nabil S. Mahmoud, Fikry A. Salem, Mohamed Ghannam

“…Despite the robust performance of advanced algorithms, the study acknowledges challenges such as data imbalance and minimal influence of certain parameters, which may affect model generalizability.…”
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Stochastic blockmodeling of the modules and core of the Caenorhabditis elegans connectome. by Dragana M Pavlovic, Petra E Vértes, Edward T Bullmore, William R Schafer, Thomas E Nichols

“…The deterministic algorithms derived communities with 4-5 modules, defined by sparse inter-connectivity between all modules. …”
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Development and validation of a population pharmacokinetic model to guide perioperative tacrolimus dosing after lung transplantation by Todd A. Miano, PharmD, PhD, Athena F. Zuppa, MD, MSCE, Rui Feng, PhD, Stephen Griffiths, BS, Laurel Kalman, BA, Michelle Oyster, MS, Edward Cantu, MD, MSCE, Wei Yang, PhD, Joshua M. Diamond, MD, MSCE, Jason D. Christie, MD, MSCE, Marc H. Scheetz, PharmD, MSC, Michael G.S. Shashaty, MD, MSCE

“…Population PK models that include lung-transplant–specific covariates may enable precision dosing algorithms that account for this highly dynamic clearance. …”
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CORE-MD clinical risk score for regulatory evaluation of artificial intelligence-based medical device software by Frank E. Rademakers, Elisabetta Biasin, Nico Bruining, Enrico G. Caiani, Rhodri H. Davies, Stephen H. Gilbert, Eric Kamenjasevic, Gearóid McGauran, Gearóid O’Connor, Jean-Baptiste Rouffet, Baptiste Vasey, Alan G. Fraser

“…Abstract The European CORE–MD consortium (Coordinating Research and Evidence for Medical Devices) proposes a score for medical devices incorporating artificial intelligence or machine learning algorithms. Its domains are summarised as valid clinical association, technical performance, and clinical performance. …”
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A Review of Research on SLAM Technology Based on the Fusion of LiDAR and Vision by Peng Chen, Xinyu Zhao, Lina Zeng, Luxinyu Liu, Shengjie Liu, Li Sun, Zaijin Li, Hao Chen, Guojun Liu, Zhongliang Qiao, Yi Qu, Dongxin Xu, Lianhe Li, Lin Li

“…This paper analyzes the research status, including the main research results and findings, of the early single-sensor SLAM technology and the current stage of LiDAR and vision fusion SLAM. …”
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A comprehensive review on safe reinforcement learning for autonomous vehicle control in dynamic environments by Rohan Inamdar, S. Kavin Sundarr, Deepen Khandelwal, Varun Dev Sahu, Nitish Katal

“…However, traditional RL algorithms are unsuitable for safety-critical applications, as they may explore unsafe actions, potentially resulting in accidents. …”
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Ethics, Animal Welfare, and Artificial Intelligence in Livestock: A Bibliometric Review by Taize Calvacante Santana, Cristiane Guiselini, Héliton Pandorfi, Ricardo Brauer Vigoderis, José Antônio Delfino Barbosa Filho, Rodrigo Gabriel Ferreira Soares, Maria de Fátima Araújo, Nicoly Farias Gomes, Leandro Dias de Lima, Paulo César da Silva Santos

“…Keyword co-occurrence and bibliographic coupling analyses revealed the formation of four main thematic clusters, covering technical applications in precision livestock farming as well as reflections on governance, animal welfare, and algorithmic justice. …”
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Early diagnosis of acute myocardial infarction via hub genes identified by integrated weighted gene co-expression network analysis by Kun Huang, Feng Wen, Jingyi Li, Wenhao Niu, Hui Chen, Shilei Wan, Fupeng Yang, Yihong Chen, Chun Liang

“…A weighted gene co-expression network analysis (WGCNA) was performed to explore the key modules connected with AMI. Next, main roles of the pathological states in AMI were analyzed using GO and KEGG and PPI networks. …”
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Robust Semantic Segmentation of Wafer Transmission Electron Microscopy Image Using Multi-Task Learning With Edge Detection by Yongwon Jo, Jinsoo Bae, Hansam Cho, Sungsu Kim, Heejoong Roh, Kyunghye Kim, Munki Jo, Munuk Kim, Jaeung Tae, Seoung Bum Kim

“…However, the automated measurement of wafer TEM images presents three main challenges: difficulty in image acquisition, significant noise, and ambiguous object boundaries. …”
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Forecasting Surface Velocity Fields Associated With Laboratory Seismic Cycles Using Deep Learning by G. Mastella, F. Corbi, J. Bedford, F. Funiciello, M. Rosenau

“…This laboratory‐based study may open new avenues for transfer learning applications with data from natural subduction zones.…”
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Estimation of Coupled Ocean/Atmosphere Impacts to the Satellite Detection of Nocturnal Maritime Low Clouds by Jesse D. Turner, Steven D. Miller, Yoo‐Jeong Noh, J. Christine Chiu, William E. Line, Christian D. Kummerow, Ryan G. Smith

“…Insights from this research can help forecasters and researchers determine which regions and conditions are prone to nighttime FLCs and thus may require either refinement of detection algorithms or independent sensor assessments.…”
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Future global distribution and climatic suitability of Anopheles stephensi by Andre Luis Acosta, Marcia C. Castro, Gabriel Z. Laporta, Jan E. Conn, Maria Anice M. Sallum

“…Using a robust multi-model framework with eight algorithms and high-resolution climate data, this study assessed and mapped current and future global climate suitability for the species, incorporating demographic data to estimate populations at risk in different scenarios. …”
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A Heliocentric-orbiting Objects Processing System (HOPS) for the Wide Field Survey Telescope: Architecture, Processing Workflow, and Preliminary Results by Shao-Han Wang, Bing-Xue Fu, Jun-Qiang Lu, LuLu Fan, Min-Xuan Cai, Ze-Lin Xu, Xu Kong, Haibin Zhao, Bin Li, Ya-Ting Liu, Qing-feng Zhu, Xu Zhou, Zhen Wan, Jingquan Cheng, Ji-an Jiang, Feng Li, Ming Liang, Hao Liu, Wentao Luo, Zheng Lou, Hairen Wang, Jian Wang, Tinggui Wang, Yongquan Xue, Hongfei Zhang, Wen Zhao

“…HOPS integrates HelioLinC3D, an algorithm well suited for the WFST survey cadence, characterized by revisiting the same sky field twice on the majority of nights. …”
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A large-scale ENIGMA multisite replication study of brain age in depression by Laura K.M. Han, Richard Dinga, Ramona Leenings, Tim Hahn, James H. Cole, Lyubomir I. Aftanas, Alyssa R. Amod, Bianca Besteher, Romain Colle, Emmanuelle Corruble, Baptiste Couvy-Duchesne, Konstantin V. Danilenko, Paola Fuentes-Claramonte, Ali Saffet Gonul, Ian H. Gotlib, Roberto Goya-Maldonado, Nynke A. Groenewold, Paul Hamilton, Naho Ichikawa, Jonathan C. Ipser, Eri Itai, Sheri-Michelle Koopowitz, Meng Li, Go Okada, Yasumasa Okamoto, Olga S. Churikova, Evgeny A. Osipov, Brenda W.J.H. Penninx, Edith Pomarol-Clotet, Elena Rodríguez-Cano, Matthew D. Sacchet, Hotaka Shinzato, Kang Sim, Dan J. Stein, Aslihan Uyar-Demir, Dick J. Veltman, Lianne Schmaal

“…Future studies are needed to identify factors that may further explain the brain age gap variance between cohorts.…”
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