Integrating transcriptomics and hybrid machine learning enables high-accuracy diagnostic modeling for nasopharyngeal carcinoma by Hehe Wang, Junge Zhang, Peng Cheng, Lujie Yu, Chunlin Li, Yaowen Wang

“…Differential expression analysis identified 293 differentially expressed genes (DEGs). Twelve ML algorithms (including Stepglm, glmBoost, and RF) were systematically combined into 113 distinct models to classify NPC versus normal tissues. …”
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Deep learning and hyperspectral features for seedling stage identification of barnyard grass in paddy field by Siqiao Tan, Qiang Xie, Wenshuai Zhu, Yangjun Deng, Lei Zhu, Xiaoqiao Yu, Zheming Yuan, Zheming Yuan, Yuan Chen, Yuan Chen

“…Notably, this surpasses the capabilities of other models that rely on amalgamations of machine learning algorithms and feature dimensionality reduction methods. …”
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A Hybrid Speech Enhancement Technique Based on Discrete Wavelet Transform and Spectral Subtraction by Yasir Iqbal, Tao Zhang, Teddy Surya Gunawan, Agus Pratondo, Xin Zhao, Yanzhang Geng, Mira Kartiwi, Nasir Saleem, Sami Bourouis

“…In low Signal-to-Noise Ratio (SNR) conditions, various approaches and algorithms are applied to improve speech quality and intelligibility. …”
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Xpert Ultra stool testing to diagnose tuberculosis in children in Ethiopia and Indonesia: a model-based cost-effectiveness analysis by Peter J Dodd, Nyashadzaishe Mafirakureva, Rina Triasih, Debebe Shaweno, Jens Levy, Eveline Klinkenberg, Petra de Haas, Ineke Spruijt, Nastiti Kaswandani, Ahmed Bedru, Melaku Gebremichael, Edine W Tiemersma

“…The intervention remained cost-effective under sensitivity analyses.Conclusions The addition of the SOS stool method to national algorithms for diagnosing TB in children is likely to be cost-effective in both Ethiopia and Indonesia.…”
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Equitable and effective clinical guidance development and dissemination: trauma aims to lead the way by Deborah M Stein, Elliott R Haut, Eileen M Bulger, Vanessa P Ho, Andres M Rubiano, Ashley Farley, Lacey N LaGrone, Danielle J Wilson, Maria Michaels, Meghan B Lane-Fall, Michael A Person, Linda Reinhart

“…The Institute of Medicine and the National Academies of Science, Engineering and Medicine have called for learning health systems, with emphasis on clinical practice guidelines (CPGs) as a means of limiting preventable deaths. Reduction in mortality has been demonstrated when evidence-based trauma CPGs are adhered to; however, guidelines are variably updated, redundant, absent, inaccessible, or perceived as irrelevant. …”
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Multi-Camera Machine Learning for Salt Marsh Species Classification and Mapping by Marco Moreno, Sagar Dalai, Grace Cott, Ben Bartlett, Matheus Santos, Tom Dorian, James Riordan, Chris McGonigle, Fabio Sacchetti, Gerard Dooly

“…This demonstrates that data fusion and band reduction techniques improve species differentiation, particularly for vegetation with overlapping spectral signatures. …”
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Digital Academic Leadership in Higher Education Institutions: A Bibliometric Review Based on CiteSpace by Olaniyi Joshua Olabiyi, Carl Jansen van Vuuren, Marieta Du Plessis, Yujie Xue, Chang Zhu

“…R1-64 bit), we analyzed 5837 documents, identifying 24 key publications that formed a network of 90 nodes and 256 links. The reduction to 24 publications occurred as part of a structured bibliometric analysis using CiteSpace, which employs algorithmic thresholds to identify the most influential and structurally significant publications within a large corpus. …”
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MINIMIZATION OF RISK OF THE ERRONEOUS DECISION IN THE ASSESSMENT OF THE IMPORTANCE OF STATISTICAL RELATIONS OF TECHNICAL AND ECONOMIC INDICATORS OF THE OBJECTS OF ELECTRIC POWER SY... by E. M. Farhadzadeh, A. Z. Muradaliyev, Yu. Z. Farzaliyev, T. K. Rafiyeva, S. A. Abdullayeva

“…Traditionally, increase of reliability of the decision is reached by reduction of a Type I error. Usually it is accepted to be equal to 5%, occasionally – to 1%, and at researches – even to 0.5 %. …”
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Helicobacter pylori eradication treatment for gastric carcinoma prevention in asymptomatic or dyspeptic adults: systematic review and Bayesian meta-analysis of randomised controlle... by Teruhiko Terasawa, Isao Miyashiro, Katsuaki Kato, Takaki Yoshikawa, Reo Takaku, Hiroshi Nishida

“…Objectives Recent meta-analyses of eradication therapy in Helicobacter pylori-infected adults reported significant reductions in gastric carcinoma risk. However, concerns about supporting unfocused screening and eradication programme in healthy, asymptomatic populations have arisen. …”
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Artificial intelligence in atrial fibrillation: emerging applications, research directions and ethical considerations by Ibrahim Antoun, Ibrahim Antoun, Ahmed Abdelrazik, Mahmoud Eldesouky, Xin Li, Georgia R. Layton, Georgia R. Layton, Georgia R. Layton, Mustafa Zakkar, Mustafa Zakkar, Mustafa Zakkar, Riyaz Somani, Riyaz Somani, G. André Ng, G. André Ng, G. André Ng

“…This scoping review examines the applications of AI across key domains: detection, risk prediction, treatment optimisation, and remote monitoring. …”
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A data-driven group retrosynthesis planning model inspired by neurosymbolic programming by Xuefeng Zhang, Haowei Lin, Muhan Zhang, Yuan Zhou, Jianzhu Ma

“…Inspired by human learning, our algorithm, akin to neurosymbolic programming, builds upon commonly used multi-step concepts such as cascade and complementary reactions and can evolve from practical experiences, enhancing the prediction model for fundamental and compositional reaction templates. …”
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Integrated phenotypic and transcriptomic characterization of desmin-related cardiomyopathy in hiPSC-derived cardiomyocytes and machine learning-based classification of disease feat... by Vivien Batoumeni, Yeranuhi Hovhannisyan, Bénédicte Gobert, Keyhan Alvandipour, Jennifer Arthur Ataam, Ombline Conrad, David Hoffmann, Nicolas Wiest-Daesslé, Jochen Dobner, José Américo Nabuco Leva Ferreira Freitas, Hakim Hocini, Zhenlin Li, Laurent Brino, Andrea Rossi, Onnik Agbulut, Peter Sommer, Pierre Joanne, Konstantinos Gkatzis

“…Finaly, we developed a machine learning prediction model to classify cellular phenotypes, which can be used for translational research, including drug candidate screening. …”
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Simulation analysis of path planning for workpiece clamping robots based on digital twin technology by Xin PAN, Min LIANG, Yanchao YIN, Zhong CHEN

“…Comparative experiments with two baseline algorithms, RRT*-Connect and an improved RRT*-FN algorithm, highlight the superior performance of the proposed method. …”
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Simulations of Microwave Land Surface Emissivity Using FengYun-3D Microwave Radiation Imager Data: A Case in the Tibetan Plateau by Yonghong Liu, Fuzhong Weng, Fei Tang, Rui Li, Yongming Xu, Yang Han, Jun Yang, Qingyang Liu

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Optimalisasi Prediksi Harga Ihsg Menggunakan Hybrid Weighted Fuzzy Time Series Hidden Markov Model Dengan Algoritma Evolusi Differensial by Alya Fitri Syalsabilla, Suci Astutik, Agus Fachrur Rozy

“…Forecasting from the Hybrid WFTS-HMM Model with the DE Algorithm has lower prediction error (1.45%) compared to the model without DE (1.49%). …”
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Optimal design strategy of traditional courtyard based on performance and data-driven method—A case study of Yanshen ancient town, China by Zhixin Xu, Xin Zheng, Xiangfeng Li

“…Based on the learning rates and various evaluation indicators, XGBoost is ultimately selected to classify and predict the overall building performance. Results indicate that the model achieves an average prediction accuracy of 83.6%. …”
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The quantification of percentage filling of gutta-percha in obturated root canal using image processing and analysis by Pravin R. Lokhande, S. Balaguru

“…Percentage filling of the obturated root canal using X-ray radiography (Dentist's prediction) and proposed algorithm results of the present study were compared. …”
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Error Data Analytics on RSS Range-Based Localization by Shuhui Yang, Zimu Yuan, Wei Li

“…The significance of our discovery has two folds: First, we present a general expression for localization error data analytics, which can explain and predict the accuracy of range-based localization algorithms; second, the further study on the general analytics expression and its minimum can be used to optimize current localization algorithms.…”
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Machine Learning-Based Cost Estimation Models for Office Buildings by Guolong Chen, Simin Zheng, Xiaorui He, Xian Liang, Xiaohui Liao

“…This paper explores the application of algorithm-optimized back propagation neural networks and support vector machines in predicting the costs of office buildings. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…Dear Editor Diabetes remains a significant public health challenge, and the integration of artificial intelligence (AI) presents remarkable opportunities to enhance early diagnosis, personalized treatment, and effective prevention strategies.1 AI algorithms, including supervised learning and convolutional neural networks, can efficiently analyze large datasets to identify patterns and risk factors associated with diabetes, surpassing the capabilities of traditional methods.2 This advanced analysis enables healthcare providers to predict the likelihood of diabetes in individuals and populations, facilitating timely interventions and customized prevention strategies. …”
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