Hyperspectral Imaging Combined with Deep Learning for the Early Detection of Strawberry Leaf Gray Mold Disease by Yunmeng Ou, Jingyi Yan, Zhiyan Liang, Baohua Zhang

“…Overall, the fused feature-based model can reduce the dimensionality of the classification data and effectively improve the predicting accuracy and precision of the classification algorithm.…”
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Heisenberg-Limited Adaptive Gradient Estimation for Multiple Observables by Kaito Wada, Naoki Yamamoto, Nobuyuki Yoshioka

“…The proposed method is an adaptive version of the quantum gradient-estimation algorithm and has a resource-efficient implementation due to its adaptiveness. …”
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In-silico and in-vitro morphometric analysis of intestinal organoids. by Sandra Montes-Olivas, Danny Legge, Abbie Lund, Alexander G Fletcher, Ann C Williams, Lucia Marucci, Martin Homer

“…Here, we developed an algorithm to automate crypt-like structure counting on intestinal organoids in both in-vitro and in-silico images. …”
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Constrained Uncertain System Stabilization with Enlargement of Invariant Sets by Walid Hamdi, Wissal Bey, Naceur Benhadj Braiek

“…The proposed approach is based on robust model predictive control (RMPC) and enhanced maximized sets algorithm (EMSA), which are applied to improve the performance of the closed-loop system and achieve less conservative results. …”
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Computerized Adaptive Testing Framework Based on Excitation Block and Gumbel-Softmax by Chengsong Liu, Yan Wei

“…In addition, most algorithms primarily focus on accurately predicting students’ abilities, neglecting critical factors such as concept diversity and question exposure rate, which are essential for model effectiveness. …”
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Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis by Onur Baser, Gabriela Samayoa, Nehir Yapar, Erdem Baser

“…We performed a claims data analysis using a machine learning algorithm. To build our model, the study population was randomly divided into an 80% training subset and a 20% testing subset and tested and trained using a cross-validation technique. …”
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The Persistent Threat of Chronic Inflammation on the Mortality Among Cervical Cancer Survivors: A Mendelian Randomization and Machine Learning Analysis Using UK Biobank and Chinese... by Wang J, Chen Z, Guan M, Ma Z, Peng L, Chen J, Fiori PL, Carru C, Capobianco G, Coradduzza D, Zhou L

“…After feature selection with 3 algorithms (LASSO regression, Boruta and Support vector machines), the gradient boosting machine (GBM) model outperformed other models by achieving an area under the curve (AUC) of 0.930 and a Brier score of 0.027 in 1-year overall survival (OS) prediction. …”
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Large Language Models and Artificial Neural Networks for Assessing 1-Year Mortality in Patients With Myocardial Infarction: Analysis From the Medical Information Mart for Intensive... by Boqun Shi, Liangguo Chen, Shuo Pang, Yue Wang, Shen Wang, Fadong Li, Wenxin Zhao, Pengrong Guo, Leli Zhang, Chu Fan, Yi Zou, Xiaofan Wu

“…An artificial neural network (ANN) algorithm derived from the SWEDEHEART (Swedish Web System for Enhancement and Development of Evidence-Based Care in Heart Disease Evaluated According to Recommended Therapies) registry, termed SWEDEHEART-AI, can predict patient prognosis following acute myocardial infarction (AMI). …”
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A prognostic model of 8-T/B cell receptor-related signatures for hepatocellular carcinoma by Xuan Zuo, Hui Li, Shi Xie, Mengfen Shi, Yujuan Guan, Huiyuan Liu, Rong Yan, Anqi Zheng, Xueying Li, Jiabang Liu, Yifan Gan, Haiyan Shi, Keng Chen, Shijie Jia, Guanmei Chen, Min Liao, Zhanhui Wang, Yanyan Han, Baolin Liao

“…Methods In this study, we categorized gene expression data of HCC patients from The Cancer Genome Altas and identified TCR related genes by the Least Absolute Shrinkage and Selection Operator and multivariate Cox regression analysis. Both the CIBERSORT algorithm and the TB tools were used to analyze the features and heterogeneity of the tumor microenvironment. …”
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Improving early epidemiological assessment of emerging Aedes-transmitted epidemics using historical data. by Julien Riou, Chiara Poletto, Pierre-Yves Boëlle

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Multidisciplinary analysis of the prognosis and biological function of NUBPL in gastric cancer by Luqian Liu, Fengyu Zhang, Jiaye Yu, Pingping Dong, Jing Deng, Weiwei Liu, Xinlei Cao, Juanjuan Huang, Xiaoming Lin, Xiangyang Xue

“…Meanwhile, the ESTIMATE algorithm was used for immune infiltration analysis and prediction of immunotherapy response, and the Genomics of Drug Sensitivity in Cancer (GDSC) database was utilized for the drug sensitivity analysis of NUBPL. …”
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Multi-Target Mechanism of Compound Qingdai Capsule for Treatment of Psoriasis: Multi-Omics Analysis and Experimental Verification by Qiao Y, Li C, Chen C, Wu P, Yang Y, Xie M, Liu N, Gu J

“…Screening of CQC anti-psoriasis core targets using machine learning algorithm. Molecular docking confirmed good binding affinity between these targets and ingredients. …”
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Comparative analysis of the human microbiome from four different regions of China and machine learning-based geographical inference by Yinlei Lei, Min Li, Han Zhang, Yu Deng, Xinyu Dong, Pengyu Chen, Ye Li, Suhua Zhang, Chengtao Li, Shouyu Wang, Ruiyang Tao

“…Individuals from the four regions could be distinguished and predicted based on a model constructed using the random forest algorithm, with the predictive effect of palmar microbiota being better than that of oral and nasal cavities. …”
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Discovering biomarkers associated with infiltration of CD8+ T cells and tumor-associated fibrosis in colon adenocarcinoma using single-cell RNA sequencing and gene co-expression ne... by Jinning Zhang, Jinning Zhang, Ziquan Sun, Ziquan Sun, Guodong Li, Guodong Li, Lixian Ding, Zitong Wang, Ming Liu, Ming Liu

“…We utilized univariate Cox regression and LASSO analysis to create a prognostic model. The predictive model was assessed through Kaplan-Meier analysis, and a survival prediction nomogram was created. …”
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Whole genome sequencing improves tissue-of-origin diagnosis and treatment options for cancer of unknown primary by Richard J. Rebello, Atara Posner, Ruining Dong, Owen W. J. Prall, Tharani Sivakumaran, Camilla B. Mitchell, Aidan Flynn, Alex Caneborg, Catherine Mitchell, Sehrish Kanwal, Clare Fedele, Samantha Webb, Krista Fisher, Hui-Li Wong, Shiva Balachander, Wenying Zhu, Shannon Nicolson, Voula Dimitriadis, Nicholas Wilcken, Anna DeFazio, Bo Gao, Madhu Singh, Ian M. Collins, Christopher Steer, Mark Warren, Narayan Karanth, Huiling Xu, Andrew Fellowes, Rodney J. Hicks, Kym Pham Stewart, Charles Shale, Peter Priestley, Sarah-Jane Dawson, Joseph H. A. Vissers, Stephen B. Fox, Penelope Schofield, David Bowtell, Oliver Hofmann, Sean M. Grimmond, Linda Mileshkin, Richard W. Tothill

“…Curated WGTS features and a CUP prediction algorithm (CUPPA) trained on WGTS data of known cancer types informs TOO in 71% of cases otherwise undiagnosed by clinicopathology review. …”
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Explainable artificial intelligence visions on incident duration using eXtreme Gradient Boosting and SHapley Additive exPlanations by Khaled Hamad, Emran Alotaibi, Waleed Zeiada, Ghazi Al-Khateeb, Saleh Abu Dabous, Maher Omar, Bharadwaj R.K. Mantha, Mohamed G. Arab, Tarek Merabtene

“…The XGBoost algorithm's ability to handle multi-dimensional datasets was employed to identify crucial variables affecting incident durations. …”
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Strengthening health information in India: are artificial intelligence based solutions enough to manage health infodemic? by Rohit Jangra, Divya Sharma, Arun Kumar Aggarwal, Ashish Behera, Pankaj Arora, Mohit Kumar, Pulak Syal, Pritam Halder, Kapil Goel, Vineeth Rajagopal, Tanvi Kiran

“…This system should include advanced algorithms and AI to monitor and analyze health-related information, authoritative sources like the Ministry of Health and Family Welfare, public education initiatives, a robust legal and regulatory framework, and continuous research. …”
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A comprehensive machine learning for high throughput Tuberculosis sequence analysis, functional annotation, and visualization by Md. Saddam Hossain, Md. Parvez Khandocar, Farzana Akter Riti, Md. Yeakub Ali, Prithbey Raj Dey, S M Jahurul Haque, Amira Metouekel, Atrsaw Asrat Mengistie, Mohammed Bourhia, Farid Khallouki, Khalid S. Almaary

“…Such algorithms provided prediction accuracies of 0.963, 0.739, 0.773, 0.866, and 0.866 sequentially. …”
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Enhanced estimation of reference evapotranspiration using hybrid deep learning models and remote sensing variables by Tze Ying Fong, Yuk Feng Huang, Ren Jie Chin, Chai Hoon Koo

“…They managed to improve the accuracy of the prediction in most of the cases, with the highest R2 = 0.805 and the lowest prediction errors, MAE = 0.265 mm/day, RMSE = 0.343 mm/day and NRMSE = 0.096. …”
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LTL-Specification of Counter Machines by Egor V. Kuzmin

“…It is known that any algorithm (hypothetically) can be implemented in the form of a Minsky three-counter machine.…”
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