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

“…All models showed a high risk of bias according to the PROBAST evaluation, mainly due to the lack of external validation and methodological shortcomings.ConclusionCurrent SAE prediction models demonstrate moderate discriminatory ability, but their methodological quality remains poor, and they are not yet suitable for routine clinical application. …”
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Artificial intelligence-assisted capsule endoscopy for detecting lesions in Crohn’s disease: a systematic review and meta-analysis by Yuling Bin, Rumei Peng, Yaqian Lee, Zhijie Lee, Yang Liu

“…However, given the limitations and heterogeneity of current research, more high-quality, large-sample studies are needed to comprehensively and thoroughly evaluate the practical application value of AI in CD diagnosis, thereby promoting its widespread adoption and optimization in clinical practice.…”
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Machine Learning and Deep Learning for Diagnosis of Lumbar Spinal Stenosis: Systematic Review and Meta-Analysis by Tianyi Wang, Ruiyuan Chen, Ning Fan, Lei Zang, Shuo Yuan, Peng Du, Qichao Wu, Aobo Wang, Jian Li, Xiaochuan Kong, Wenyi Zhu

“…ObjectiveThis systematic review and meta-analysis aimed to pool the results and evaluate the heterogeneity of the current studies in using TML or DL models to diagnose LSS, thereby providing more comprehensive information for further clinical application. …”
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Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…In addition, eight different machine learning algorithms were applied for prediction, and the prediction performances of these algorithms were comprehensively evaluated using the receiver operating characteristic curve, area under the curve (AUC), calibration curve analysis, and decision curve analysis and confusion matrix.ConclusionsUsing LASSO regression analysis, leukocyte, neutrophil, red blood cell, hemoglobin, platelet, and monocyte-to-lymphocyte ratios were identified as risk factors for HF. …”
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The role of artificial intelligence in occupational health in radiation exposure: a scoping review of the literature by Zohreh Fazli, Mehran Sadeghi, Mohebat Vali, Parvin Ahmadinejad

“…The quality of the included studies was evaluated using the MMAT critical appraisal tool. …”
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Optimal policy for composite sensing with crowdsourcing by Bei Zhao, Siwen Zheng, Jianhui Zhang

“…Besides, we provide necessary theoretical analysis, which ensures the optimality of the optimal algorithm. In the end, we conduct some experiments to evaluate the performance of our two policies in terms of the average quality, the sensing ratio, the success report ratio, and the approximate ratio. …”
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A Workflow for Integrated Geological Modeling for Shale Gas Reservoirs: A Case Study of the Fuling Shale Gas Reservoir in the Sichuan Basin, China by Xiaofei Shang, Huawei Zhao, Shengxiang Long, Taizhong Duan

“…Moreover, the workflow involves multiple model integration processes, which is the key to model quality. The selection and optimization of modeling methods, the innovation and development of modeling algorithms, and the evaluation techniques for model uncertainty are areas where breakthroughs may be possible in the geological modeling of shale gas reservoirs. …”
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T_SRNET: A multimodal model based on convolutional neural network for emotional speech enhancement by Shaoqiang Wang, Lei Feng, Li Zhang

“…After ablation and contrast experiments, the accuracy of CREMA-D and IEMOCAP was improved by 2% and 1% respectively. Also it can be evaluated that the proposed model in this study can correlate image data with speech data, improve the quality of speech data tagging and enhance the performance of speech recognition.…”
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Reprogramming Heritage: An Approach for the Automatization in the Adaptative Reuse of Buildings by Marta Domènech-Rodríguez, David López López, Sergi Nadal, Anna Queralt, Còssima Cornadó

“…The proposed methodology for a computational algorithm aims to systematise spatial characteristics, assess programmatic needs, and optimise building usage, while addressing challenges such as data integration and quality assurance. …”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…The algorithms (RF and STR) with the smallest Mean Absolute Error (MAE) and the highest residual error (RMSE) and the highest correlation coefficient (RP2) were selected for further parameter optimization and evaluation. …”
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Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis by Xue Ge, Lan Yao, Yan Liu, Yi Wang, Fang Zhang

“…Various machine learning algorithms were also employed to build predictive models. …”
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A Pilot Study on Mixed-Reality Approaches for Detecting Upper-Limb Dysfunction in Multiple Sclerosis: Insights on Cerebellar Tremor by Etty Sabatino, Miriam Moschetta, Andrea Lucaroni, Giacinto Barresi, Carlo Ferraresi, Jessica Podda, Erica Grange, Giampaolo Brichetto, Anna Bucchieri

“…This study explored the feasibility of using Microsoft HoloLens2 for motion capture to assess upper-limb function in PwMS. Using the ROCKapp application, kinematic metrics such as movement quality and oculomotor coordination were recorded during pick-and-place tasks. …”
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Determinants and risk prediction models for frailty among community-living older adults in eastern China by Lin Qi, Lin Qi, Jianyu Liu, Xuhui Song, Xinle Wang, Mengmeng Yang, Xinyi Cao, Yan He

“…Predictive models were constructed using decision trees, random forests, and XGBoost algorithms, implemented in R software (version 4.4.2). …”
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Enhancing student reflections with natural language processing based scaffolding: A quasi-experimental study in a large lecture course by Muhsin Menekse, Alfa Satya Putra, Jiwon Kim, Ahmed Ashraf Butt, Mark A. McDaniel, Ido Davidesco, Michelle Cadieux, Joe Kim, Diane Litman

“…The app uses Natural Language Processing (NLP) algorithms to evaluate students' reflection quality and specificity using a 4-point scale, with 1 indicating shallow reflection and 4 indicating highly relevant or specific reflection. …”
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Quantification of the heterogeneity of prognostic cellular biomarkers in ewing sarcoma using automated image and random survival forest analysis. by Claudia Bühnemann, Simon Li, Haiyue Yu, Harriet Branford White, Karl L Schäfer, Antonio Llombart-Bosch, Isidro Machado, Piero Picci, Pancras C W Hogendoorn, Nicholas A Athanasou, J Alison Noble, A Bassim Hassan

“…Through elimination of bias, the evaluation of high-dimensionality biomarker distribution within cell populations of a tumour using random forest analysis in quality controlled tumour material could be achieved. …”
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Vehicular-Computational Resource Geofencing: Efficient Spatiotemporal Uncertainty Estimation by Ghada Afifi, Bassem Mokhtar

“…However, existing VCC solutions are unable to satisfy the stringent quality of experience (QoE) requirements for running vehicular applications, especially delay- and throughput-sensitive applications, given the high communication delay and latency with the central cloud. …”
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Quantum computing challenges and solutions in software industry—A multivocal literature review by Masaud Salam, Muhammad Ilyas

“…Subsequently, these challenges were examined deeply and determined that five of them are the most critical, these are ‘Lack of quantum specific algorithms, dev and testing methodologies’, ‘Difficult compilation and debugging’, ‘Lack of development tools and technology’, ‘Lack of development guidelines & Quality Assurance Standards’ and ‘Lack of professional expert’, together founding over 30% of occurrences. …”
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Automatic text generation system for endangered languages based on conditional generative adversarial networks by Zhong Luo

“…Future research directions include optimizing CGAN parameters using algorithms like particle swarm optimization, refining discriminator outputs in loss calculations, and incorporating cultural and linguistic features specific to endangered languages to improve the quality of the generated texts.…”
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Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…Traditional Foreign Object Debris (FOD) detection methods face challenges such as difficulties in large-size data acquisition and the ineffective application of detection algorithms with high accuracy. …”
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A Big-Data-Driven Framework for Parking Demand Estimation in Urban Central Districts by Yunlin Guan, Yun Wang, Xuedong Yan, Haonan Guo, Yu Zhou

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