The multiple uses of artificial intelligence in exercise programs: a narrative review by Alberto Canzone, Alberto Canzone, Giacomo Belmonte, Antonino Patti, Domenico Savio Salvatore Vicari, Domenico Savio Salvatore Vicari, Fabio Rapisarda, Valerio Giustino, Patrik Drid, Antonino Bianco

“…BackgroundArtificial intelligence is based on algorithms that enable machines to perform tasks and activities that generally require human intelligence, and its use offers innovative solutions in various fields. …”
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Expert Consensus on the Management of Acute Otitis Media in India: A Delphi Study by Tanu Singhal, Shyam Kukreja, Jaydeep Choudhury, Vijay Yewale, Balasubramanian Sundaram, Jagdish Chinnappa, Suhas Prabhu, Balaji Veeraraghavan, Camilla Rodrigues, Vidya Krishna, Winsley Rose, Samir Bhargava

“…Finally, experts agreed to include 67 statements pertaining to risk factors, resistant strains, conservative and symptomatic management, and antibiotic treatment algorithms for AOM and OME. Conclusion: The consensus recommendations provide systematic guidance to clinicians on the appropriate management of AOM and OME. …”
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UNet-Att: a self-supervised denoising and recovery model for two-photon microscopic image by Yuer Lu, Yongfa Ying, Chen Lin, Yan Wang, Jun Jin, Xiaoming Jiang, Jianwei Shuai, Xiang Li, Jinjin Zhong

“…The UNet-Att model proves to surpass mainstream algorithms in the dual objectives of denoising and preserving the textural intricacies of original images, which is evidenced by an increase of 9.42 dB in the high Peak Signal-to-Noise Ratio (PSNR) coupled with an improvement of 0.1131 in the Structural Similarity Index Measurement (SSIM). …”
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Towards PErsonalised PRognosis for children with traumatic brain injury: the PEPR study protocol by Jaap Oosterlaan, Marsh Königs, Job B M van Woensel, Marc Engelen, Marjan E Steenweg, Petra J W Pouwels, Cece C Kooper, Hilgo Bruining, Arne Popma, Dennis R Buis, Maayke Hunfeld

“…In addition, the potential added value of advanced neuroimaging data and the use of machine learning algorithms in the development of prognostic models will be assessed.Methods and analysis 210 children aged 4–18 years diagnosed with mild-to-severe TBI will be prospectively recruited from a research network of Dutch hospitals. …”
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Adverse events in the nervous system associated with blinatumomab: a real-world study by Wen Gao, Jingwei Yu, Yifei Sun, Zheng Song, Xia Liu, Xue Han, Lanfan Li, Lihua Qiu, Shiyong Zhou, Zhengzi Qian, Xianhuo Wang, Huilai Zhang

“…The reporting odds ratio (ROR), proportional reporting ratio (PRR), Bayesian confidence interval progressive neural network (BCPNN), and multi-item gamma Poisson shrinker (MGPS) algorithms were utilized for data mining. Results A total of 5,962 blinatumomab-related cases were analyzed. …”
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Development of robust machine learning models for predicting flexural strengths of fiber-reinforced polymeric composites by Abdulhammed K. Hamzat, Umar T. Salman, Md Shafinur Murad, Ozkan Altay, Ersin Bahceci, Eylem Asmatulu, Mete Bakir, Ramazan Asmatulu

“…This study investigates the potential of machine learning (ML) techniques to predict the flexural properties of fiber-reinforced composites accurately and efficiently. Five ML algorithms—Light gradient boosting regressor (LGBR), Extra tree regressor (ETR), Decision tree regressor (DTR), Histogram-based gradient boosting regressor (HGBR), and Adaptive boosting regressor (ABR)—were employed to predict the flexural strengths using both experimental data generated in-house and data collected from open literature. …”
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Research on Traffic Accident Severity Level Prediction Model Based on Improved Machine Learning by Jiming Tang, Yao Huang, Dingli Liu, Liuyuan Xiong, Rongwei Bu

“…Decision tree, XGBoost, and random forest algorithms, respectively, were applied for the secondary prediction. …”
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Attention-enhanced optimized deep ensemble network for effective facial emotion recognition by Taimoor Khan, Muhammad Yasir, Chang Choi

“…In recent studies, various algorithms have encountered several challenges such as data scarcity, low-resolution images, and suboptimal performance, particularly in real-time applications. …”
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Exploring the risk factors of blood transfusion in patients with isolated traumatic brain injury based on machine learning prediction models by LIU Wei, XIONG Ziqing, WU Chenggao, LE Aiping

“…Six machine learning algorithms were used for model construction, and the validation results on the test set showed that the CatBoost model performed the best with an AUC of 0.911. …”
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Novel genes involved in vascular dysfunction of the middle temporal gyrus in Alzheimer’s disease: transcriptomics combined with machine learning analysis by Meiling Wang, Aojie He, Yubing Kang, Zhaojun Wang, Yahui He, Kahleong Lim, Chengwu Zhang, Li Lu

“…Finally, combining bulk RNA sequencing data and two machine learning algorithms (least absolute shrinkage and selection operator and random forest), four characteristic Alzheimer’s disease feature genes were identified: somatostatin (SST), protein tyrosine phosphatase non-receptor type 3 (PTPN3), glutinase (GL3), and tropomyosin 3 (PTM3). …”
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A Comparative Study of Machine Learning Techniques for Predicting Mechanical Properties of Fused Deposition Modelling (FDM)-Based 3D-Printed Wood/PLA Biocomposite by Prashant Anerao, Atul Kulkarni, Yashwant Munde, Namrate Kharate

“…Four distinct machine learning algorithms have been selected for predictive modeling: Linear Regression, Support Vector Machine (SVM), eXtreme Gradient Boosting (XGBoost), and Adaptive Boosting (AdaBoost). …”
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An Integrated Stacking Ensemble Model for Natural Gas Purchase Prediction Incorporating Multiple Features by Junjie Wang, Lei Jiang, Le Zhang, Yaqi Liu, Qihong Yu, Yuheng Bu

“…This model integrates diverse algorithms and incorporates weather factors, while regionalizing characteristics of natural gas usage, thereby achieving accurate forecasts of natural gas purchase volumes. …”
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Machine Learning and Intelligent Diagnostics in Dental and Orofacial Pain Management: A Systematic Review by Taseef Hasan Farook, Nafij Bin Jamayet, Johari Yap Abdullah, Mohammad Khursheed Alam

“…The current review did not internally analyze the machine learning models and their respective algorithms, nor consider the confounding variables and factors responsible for shaping the orofacial disorders responsible for eliciting pain.…”
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Leveraging machine learning for enhanced reservoir permeability estimation in geothermal hotspots: a case study of the Williston Basin by Abdul-Muaizz Koray, Emmanuel Gyimah, Mohamed Metwally, Hamid Rahnema, Olusegun Tomomewo

“…To enhance accuracy, we initially applied various clustering algorithms, including the density-based spatial clustering of applications with noise (DBSCAN), K-means, K-median, and hierarchical clustering methods, to delineate hydraulic flow units (HFU) within the reservoir using porosity, permeability and water saturation core data. …”
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可穿戴设备在卒中风险预测及卒中后管理中的应用进展 Research Progress on the Application of Wearable Devices in Stroke Risk Prediction and Post-Stroke Management... by 吴雅婷1，魏宸铭1，桑振华1，陈乐1，梁怡凡1，武剑1，2，3 (WU Yating1, WEI Chenming1, SANG Zhenhua1, CHEN Le1, LIANG Yifan1, WU Jian1,2,3)

“…By integrating with health management platforms and artificial intelligence algorithms, wearable devices can significantly enhance the accuracy of risk assessment, optimize rehabilitation treatment plans, and thus improve the patients’ outcomes. …”
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Revolutionizing ESCC prognosis: the efficiency of tumor-infiltrating immune cells (TIIC) signature score by Haixia Wang, Shaowei Ma, Zixin Yang, Ren Niu, Haiyong Zhu, Shujun Li, Shaolin Gao, Zhirong Li, Yanhua Tian

“…Twenty machine learning algorithms were further applied to evaluate the prognostic efficacy of TIIC signature score. …”
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A novel perspective on survival prediction for AML patients: Integration of machine learning in SEER database applications by Zheng-yi Jia, Maierbiya Abulimiti, Yun Wu, Li-na Ma, Xiao-yu Li, Jie Wang

“…Finally, we used 11 machine learning algorithms to predict the survival rate of AML patients at 1, 2, and 3 years, respectively. …”
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The role of sodium-nickel chloride (Na-NiCl2) batteries in managing uncertainty and renewable sources for empowering hybrid energy systems using bi-level CONOPT-based optimization by Abdallah Aldosary

“…The methodology leverages the CONOPT approach within the GAMS platform, which integrates sequential linear and quadratic programming algorithms with reduced gradients to address complex nonlinear optimization issues characterized by sparse and nonlinear constraints. …”
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High Seroprevalence of Autoantibodies Typical of Autoimmune Liver Disease in Eastern Ethiopia: Is Chewing of Khat (Catha edulis) a Triggering Factor? by Stian Magnus Staurung Orlien, Tekabe Abdosh Ahmed, Nejib Yusuf Ismael, Nega Berhe, Trine Lauritzen, Svein Gunnar Gundersen, Asgeir Johannessen

“…However, the seroprevalences of AMA and SMA were strikingly high in this Ethiopian population compared to global estimates, suggesting that diagnostic algorithms for autoimmune liver diseases developed in Europe and North America might lead to misdiagnosis of patients on the African continent.…”
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Auditory attention decoding based on neural-network for binaural beamforming applications by Roy Gueta, Elana Zion-Golumbic, Jacob Goldberger, Sharon Gannot

“…This led to the development of several algorithms addressing the auditory attention decoder (AAD) task. …”
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