Diagnostic models for sepsis-associated encephalopathy: a comprehensive systematic review and meta-analysis by Tengfei Zhou, Tengfei Zhou, Xinming Tian, Wei Wang, Zhe Chu

“…A total of 29 predictive models were developed, comprising 10 optimal models, primarily utilizing logistic regression or machine learning algorithms. The combined AUC of the five logistic regression models was 0.85 (95% CI 0.77–0.93), exhibiting substantial heterogeneity (I2 = 91.8%). …”
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Application of Motor Imagery Brain-Computer Interface in Rehabilitation of Neurological Diseases by YANG Banghua

“…Specifically, the overview of BCI technology mainly introduces BCI technology, MI-BCI technology and AR-MI-BCI rehabilitation training system (the process and overall structure of the AR-MI-BCI rehabilitation training system). …”
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Optimizing skin cancer screening with convolutional neural networks in smart healthcare systems. by Ali Raza, Akhtar Ali, Sami Ullah, Yasir Nadeem Anjum, Basit Rehman

“…Clinical examination of skin lesions is a key aspect that is important in the assessment of skin disease but comes with some drawbacks mainly with interpretational aspects, time-consuming and healthare expenditure. …”
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An Updated Systematic Review on Asthma Exacerbation Risk Prediction Models Between 2017 and 2023: Risk of Bias and Applicability by Liu A, Zhang Y, Yadav CP, Chen W

“…PROBAST indicated a generally high risk of bias (80%) in these models, which mainly originated from the sample selection (“Participant” domain, 6 studies) and statistical analysis (“Analysis” domain, 7 studies). …”
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The diagnostic value investigation of programmed cell death genes in heart failure by Qiuyue Chen, Su Tu

“…These genes, such as Serpin Family E Member 1 (SERPINE1), are mainly enriched in pathways such as the regulation of the inflammatory response. …”
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Design of an Efficient Distracted Driver Detection System: Deep Learning Approaches by Naveen Kumar Vaegae, Kranthi Kumar Pulluri, Kalapraveen Bagadi, Olutayo O Oyerinde

“…In this paper, an efficient distracted driver detection scheme (DDDS) has been proposed using two robust deep learning architectures, mainly visual geometric groups (VGG-16) and residual networks (ResNet-50). …”
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Integrating bioinformatics and machine learning to investigate the mechanisms by which three major respiratory infectious diseases exacerbate heart failure by Yiding Yu, Quancheng Han, Juan Zhang, Jingle Shi, Huajing Yuan, Yitao Xue, Yan Li

“…GO and KEGG enrichment analysis showed that these genes were mainly involved in innate immune response, inflammation and coagulation pathways. …”
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The Specific Features of the Pathogenesis and Correction of Critical Conditions in Obstetric Care by Yu. S. Podolsky

“…Dyshidrosis appears as an increased extracellular sector mainly due to interstitial hyperhydration. The low values of arterial blood oxygen, its delivery and uptake, oxygen extract coefficient and the high value of oxygen debt (OD) confirmed blood shunting or circulatory centralization, which was indicative of visceral hypoxia. …”
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Movement Disorders and Smart Wrist Devices: A Comprehensive Study by Andrea Caroppo, Andrea Manni, Gabriele Rescio, Anna Maria Carluccio, Pietro Aleardo Siciliano, Alessandro Leone

“…The selected articles mainly investigate the relationship between smart wrist devices and Parkinson’s disease. …”
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Spatial-temporal data analysis of digital twin [version 1; peer review: 1 approved, 2 approved with reservations] by Qian Ai, Lei Tang, Xing He, Bo Pan, Robert Qiu

“…Methods: Our work, which is mainly concerned with heterogeneous spatial-temporal data, focuses on exploring data utilization methodology in DT. …”
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Cloud-edge collaborative data anomaly detection in industrial sensor networks. by Tao Yang, Xuefeng Jiang, Wei Li, Peiyu Liu, Jinming Wang, Weijie Hao, Qiang Yang

“…The former is implemented using Gaussian and Bayesian algorithms, which effectively filter the substantial volume of sensor data generated during the normal operation of the industrial sensor network, thereby reducing traffic load. …”
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Advancing the accuracy of tyrosinase inhibitory peptides prediction via a multiview feature fusion strategy by Watshara Shoombuatong, Nalini Schaduangrat, Nutta Homdee, Saeed Ahmed, Pramote Chumnanpuen

“…Tyrosinase inhibitory peptides (TIPs), mainly designed to regulate the activity of the enzyme tyrosinase, are of interest in various domains, including cosmetics, dermatology, and pharmaceuticals, due to their potential applications in controlling skin pigmentation. …”
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Identification of markers correlating with mitochondrial function in myocardial infarction by bioinformatics. by Wenlong Kuang, Jianwu Huang, Yulu Yang, Yuhua Liao, Zihua Zhou, Qian Liu, Hailang Wu

“…<h4>Results</h4>MitoDEGs in MI were mainly involved in mitochondrial function and adenosine triphosphate (ATP) synthesis pathways. …”
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Short-Term Prediction of Origin–Destination Passenger Flow in Urban Rail Transit Systems with Multi-Source Data: A Deep Learning Method Fusing High-Dimensional Features by Huanyin Su, Shanglin Mo, Huizi Dai, Jincong Shen

“…Additionally, the distribution characteristics are also complex. Previous studies mainly focus on passenger flow prediction at metro stations, while few methods solve the OD passenger flow prediction problems of an urban rail transit system. …”
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Index or illusion: The case of frailty indices in the Health and Retirement Study. by Yi-Sheng Chao, Hsing-Chien Wu, Chao-Jung Wu, Wei-Chih Chen

“…We are developing new algorithms to develop and validate innovative indices.…”
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Neighborhood Information Aggregation and Multi-View Feature Extraction-Based Contrastive Graph Clustering by Liulong Yao, Jinrong Cui, Yazi Xie, Chengli Sun

“…Extensive experiments on five benchmark datasets show that our proposed method outperforms most other clustering algorithms.…”
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scAMZI: attention-based deep autoencoder with zero-inflated layer for clustering scRNA-seq data by Lin Yuan, Zhijie Xu, Boyuan Meng, Lan Ye

“…We compare the performance of scAMZI with nine methods (three shallow learning algorithms and six state-of-the-art DL-based methods) on fourteen benchmark scRNA-seq datasets of various sizes (from hundreds to tens of thousands of cells) with known cell types. …”
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A review of interactions between irrigation and evapotranspiration by Ziyuan Gong, Fei Gao, Xinyu Chang, Tianqi Hu, Yaping Li

“…The study found that the hot spots mainly concentrated on ET, irrigation, remote sensing (RS) technology, crop yield, and water utilization rate. …”
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State of Charge Estimation for Li-Ion Batteries: An Edge-Based Data-Driven Approach by Sesidhar Dvsr, Chandrashekhar Badachi, Chandrashekar Nagawaram, Panduranga Chary Kondoju, C. Dhanamjayulu, Innocent Kamwa

“…Recently, the confluence of Edge computing with IoT has enabled resource constrained embedded devices to implement machine learning algorithms. TinyML, with its emphasis on integrating machine learning into embedded systems, seeks to move the end users away from high-performance machines, towards devices with limited resources and power. …”
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Analysis of shared pathogenic mechanisms and drug targets in myocardial infarction and gastric cancer based on transcriptomics and machine learning by Junyang Ma, Junyang Ma, Shufu Hou, Xinxin Gu, Peng Guo, Jiankang Zhu

“…The random forest and Lasso algorithms were used to identify genes with diagnostic value, leading to nomogram construction. …”
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