Unraveling the role of histone acetylation in sepsis biomarker discovery by Feng Cheng, Juxin Deng, Zhaoyang Du, Lei Li, Zhaolei Qiu, Min Zhu, Hongchang Zhao, Hongchang Zhao, Zhenjie Wang, Zhenjie Wang

“…Mendelian randomization (MR), RT-qPCR, and functional assays were conducted for validation.ResultsBLOC1S1, NDUFA1, and SFT2D1 were identified as key biomarkers. A predictive nomogram demonstrated strong diagnostic potential. …”
Get full text

Detection of Adulteration of Panax Notoginseng Powder by Terahertz Technology by Bin Li, Hai Yin, A-kun Yang, Ai-guo Ouyang

“…The model’s results show that the UVE-BPNN model is better; the classification accuracy of the prediction set of UVE-BPNN is 95%. Then, the least square support vector machine (LS-SVM) algorithm and partial least square (PLS) algorithm are used to establish the quantitative analysis model. …”
Get full text

An approach to forecasting damage due to unfavorable circumstances associated with indistinguishability of source data by V. F. Zolotukhin, A. V. Matershev, L. A. Podkolzina

“…The efficiency of predicting damage to complex systems depends directly on the quality of processing methods, systematization, and the amount of input data. …”
Get full text

Dynamic Heart Rate Variability Vector and Premature Ventricular Contractions Patterns in Adult Hemodialysis Patients: A 48 h Risk Exploration by Gabriel Vega-Martínez, Francisco José Ramos-Becerril, Josefina Gutiérrez-Martínez, Arturo Vera-Hernández, Carlos Alvarado-Serrano, Lorenzo Leija-Salas

“…R-wave and PVC identification resulted in 97.53% and 85.83% positive predictive values, respectively. PVCs’ prevalence and HRV changes’ relationship in 48 h records could relate to cardiovascular risk. …”
Get full text

Parameter Optimization Method for Predictor–Corrector Guidance With Impact Angle Constraint by Xinwan Kong, Cheng Zhang

“…Additionally, an uncertainty factor is proposed to describe the model uncertainty in the predictor–corrector guidance algorithm. Based on the uncertainty factor, the impact of uncertainty and external disturbances on prediction accuracy is derived, and the propagation of prediction error to the miss distance is analyzed using the adjoint method. …”
Get full text

Deep Learning-Guided Simulated Annealing for Designing Vocational High Educational System by Yuan Jie

“…In order to improve the simulated annealing prediction of full-dimensional data, a modified brain emotion based on simulated annealing algorithm is proposed. …”
Get full text

Counterfactual choice and learning in a neural network centered on human lateral frontopolar cortex. by Erie D Boorman, Timothy E Behrens, Matthew F Rushworth

“…Using a three-alternative decision-making task, a Bayesian reinforcement-learning algorithm, and fMRI, we investigated the coding of counterfactual choices and prediction errors in the human brain. …”
Get full text

The impact of artificial intelligence on medical diagnostics: A letter to the editor by Sahar Imtiaz, Sheikh Abdul Qadir Jillani

“…AI-powered diagnostics can assist healthcare professionals in detecting diseases, predicting patient outcomes, and designing personalized treatment plans. (3) Furthermore, AI can contribute to the early detection of diseases, thereby enabling timely interventions and improving patient survival rates. …”
Get full text

A Deep Learning Model for ERP Enterprise Financial Management System by Hui Zhang

“…Then, a financial risk prediction model based on a deep learning model is designed. …”
Get full text

Transforming nano grids to smart grid 3.0: AI, digital twins, blockchain, and the metaverse revolutionizing the energy ecosystem by Herman Zahid, Adil Zulfiqar, Muhammad Adnan, Muhammad Sajid Iqbal, Anwar Shah, Usman Abbasi, Salah Eldeen Gasim Mohamed

“…The digital twins can perform real-time monitoring, simulation, and predictive analysis; blockchain ensures secure, decentralized energy transactions; and the metaverse creates immersive, interactive environments for system management. …”
Get full text

Transforming heart transplantation care with multi-omics insights by Zhengbang Zou, Jianing Han, Zhiyuan Zhu, Shanshan Zheng, Xinhe Xu, Sheng Liu

“…Single–cell omics technologies and machine learning algorithms further resolve cellular heterogeneity and improve predictive modeling, thereby enhancing the clinical translatability of multi-omics data. …”
Get full text

Integrated Additive Manufacturing Trajectory Control and Repair Management for Spiral Bevel Gear Using Fractional-Order PID and Adaptive Fuzzy Neural Inference System by Hiyam Adil Habeeb, Abdul Hadi Azman, Mohd Rizal Alkahari, Dzuraidah Abd Wahab, Nurhasyimah Abd Aziz

“…The framework established for gear repair offers a blueprint for future advancements in predictive maintenance and automated repair systems. …”
Get full text

AI for rapid identification of major butyrate-producing bacteria in rhesus macaques (Macaca mulatta) by Annemiek Maaskant, Donghyeok Lee, Huy Ngo, Roy C. Montijn, Jaco Bakker, Jan A. M. Langermans, Evgeni Levin

“…In addition, to improve transparency, we employed explainability analysis to uncover the image features influencing the model’s predictions. Results By integrating fecal image data with corresponding metagenomic sequencing information, the deep learning (DL) and machine learning (ML) algorithms successfully predicted 16 individual bacterial genera (area under the curve (AUC) > 0.7) among the 50 most abundant genera in rhesus macaques (Macaca mulatta). …”
Get full text

Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census by Yilin Li, Cen Chen, Xiaoyu Ji, Ningxiao Jiang, Fei Wang, Xiangqian Gao, Weiwei Chen, Qiang Tang, Yan Li, Shinan Zhang, Gaofeng Qin, Yingjiang Xu, Yanlin Wang, Lingwen Kong, Lei Han, Jie Mei

“…We then developed the CSCI to predict the prognosis and response to immunotherapy in ovarian cancer patients using advanced machine learning algorithms. …”
Get full text

Development of a machine learning-derived dendritic cell signature for prognostic stratification in lung adenocarcinoma by Fang Zhou, Fang Zhou, Meng Wang, Meng Wang, Zheng Wang, Zheng Wang, Wei Li, Wei Li, Xike Lu, Xike Lu

“…A dendritic cell-related signature (DCRS) was constructed using multiple machine learning algorithms (Lasso-Cox, RSF, CoxBoost, Stepwise-Cox), and its prognostic performance was validated in seven external cohorts. …”
Get full text

Machine Learning in Maritime Safety for Autonomous Shipping: A Bibliometric Review and Future Trends by Jie Xue, Peijie Yang, Qianbing Li, Yuanming Song, P. H. A. J. M. van Gelder, Eleonora Papadimitriou, Hao Hu

“…Machine learning plays a crucial role in enhancing maritime safety by leveraging its data analysis and predictive capabilities. However, there has been no review grounded in bibliometric analysis in this field. …”
Get full text

Dynamic Dwell Time Adjustment in Wire Arc-Directed Energy Deposition: A Thermal Feedback Control Approach by Md Munim Rayhan, Abderrachid Hamrani, Fuad Hasan, Tyler Dolmetsch, Arvind Agarwal, Dwayne McDaniel

“…Future work should focus on integrating multi-axis thermal sensors, extending the framework to multi-material deposition scenarios and implementing machine learning algorithms for predictive thermal modeling.…”
Get full text

The role of LAMA5 in breast cancer progression and its potential in immunotherapy by Xiaoli Zhang, Hongfang Yan, Lihan Bie, Zheng Xu, Xiaoyang Yao, Zhilan Li, Chengshan He, Zhouhong Xiang, Xiudi Jiang

“…ROC analysis indicated moderate predictive value for immunotherapy response (AUC = 0.704), and LAMA5 expression was positively associated with sensitivity to chemotherapeutic agents including cisplatin and docetaxel. …”
Get full text

Dental bur detection system based on asymmetric double convolution and adaptive feature fusion by HongLing Hou, Ao Yang, Xiangyao Li, Kangkai Zhu, Yandi Zhao, Zhiqiang Wu

“…The model also achieved a 14.4% reduction in parameter volume and a 17.9% decrease in computational expenditure, while achieving a flawless counting accuracy of 100%. …”
Get full text

Acute severe ulcerative colitis: using JAK-STAT inhibitors for improved clinical outcomes by Shruthi Karthikeyan, Chetan Ambastha, Kian Keyashian

“…Failure to treat ASUC may lead to toxic dilation of the colon, hemorrhage, or sepsis. Current algorithms suggest the use of intravenous (IV) corticosteroids upon diagnosis, with transition to oral corticosteroids, calcineurin inhibitors or tumor necrosis factor (TNF) inhibitors upon reduction of severe symptoms for candidates deemed to be amenable to medical management. …”
Get full text