Outcomes and predictive factors after second stereotactic radiosurgery for refractory trigeminal neuralgia by Bailey A. Loving, Jacob F. Oyeniyi, Siddharth Ramanathan, Joseph S. Lee, Hong Ye, Yastira Ramdas, Inga S. Grills, James F. Fontanesi, Prakash Chinnaiyan, Daniel K. Fahim, Daniel B. Michael, Peter Y. Chen

“…Methods: We analyzed 53 patients who underwent T2 between 2012 and 2018 using a prospectively maintained single institution database. …”
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Predictive Factors and Nomogram for Spontaneous Bacterial Peritonitis in Decompensated Cirrhosis Among the Elderly by Yan F, Peng X, Yang X, Yuan L, Zheng X, Yang Y

“…A multivariate logistic regression analysis was performed to identify significant predictors and to develop a nomogram for predicting the occurrence of SBP. To evaluate the model’s discrimination and calibration, a bootstrap method with 1000 resamples was utilized.Results: Findings from the multivariate logistic regression analysis indicated that constipation (odds ratio [OR] 2.09, 95% confidence interval [CI] 1.25− 3.49, P=0.005), ascites (OR 2.84, 95% CI 1.64− 4.92, P< 0.001), Child-Pugh-Turcotte (CPT) score (OR 4.80, 95% CI 1.69− 13.60, P=0.003), and high sensitivity C-reactive protein (hs-CRP) (OR 2.96, 95% CI 1.54− 5.45, P=0.001) were significant independent predictors for the occurrence of SBP in elderly individuals with DC. …”
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Investigation of predictive factors for fatty liver in children and adolescents using artificial intelligence by Aliakbar Sayyari, Amin Magsudy, Yasamin Moeinipour, Amirhossein Hosseini, Hamidreza Amiri, Mohammadreza Arzaghi, Fereshteh Sohrabivafa, Seyedeh Fatemeh Hamzavi, Ashkan Azizi, Tahereh Hatamii, AmirAli Okhovat, Naghi Dara, Negar Imanzadeh, Farid Imanzadeh, Mahmoud Hajipour

“…Machine learning algorithms could assist in an early diagnostic approach and leading to a favorable prognosis.ObjectiveThis study aimed to identify predictive factors for NAFLD in children and adolescents using machine learning models, focusing on liver biopsy outcomes such as fibrosis, infiltration, ballooning, and steatosis.MethodsData from 659 children suspected of NAFLD, who underwent liver biopsy at Mofid Children's Hospital between 2011 and 2023, were analyzed. …”
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Predictive value of inflammatory indexes in in-hospital mortality for patients with acute aortic dissection by Yijing Xin, Siqi Lyu, Jingyang Wang, Yimeng Wang, Yuyuan Shu, Hanyang Liang, Yanmin Yang

“…The association between admission inflammatory indexes and outcomes was evaluated using the Cox regression model and restricted cubic splines (RCS). …”
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The predictive value of endocan as a novel biomarker: an umbrella study on meta-analyses by Sandeep Samethadka Nayak, Daniyal Ameen, Sara Nobakht, Ranjan Nayak, Shrinidhi Vilas Prabhu, Mohammad-Hossein Keivanlou, Soheil Hassanipour, Ehsan Amini-Salehi, Nisarg Thakker

“…This umbrella review aimed to systematically synthesize and evaluate the evidence from multiple meta-analyses, offering a view of endocan’s effectiveness as a predictive biomarker in medical diseases. …”
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Inflammation‐Derived and Clinical Indicator‐Based Predictive Model for Ischemic Stroke Recovery by Jiao Luo, You Cai, Peng Xiao, Changchun Cao, Meiling Huang, Xiaohua Zhang, Jie Guo, Yongyang Huo, Qiaoyan Tang, Liuyang Zhao, Jiabang Liu, Yaqi Ma, Anqun Yang, Mingchao Zhou, Yulong Wang

“…Conclusions The combined model is a valuable tool for evaluating prognostic outcomes, and the predictive factors can facilitate development of better treatment strategies.…”
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Clinical characteristics, prognosis, and predictive modeling in class IV ± V lupus nephritis by Anjing Wang, Anjing Wang, Yunlong Qin, Yunlong Qin, Yan Xing, Zixian Yu, Liuyifei Huang, Jinguo Yuan, Yueqing Hui, Mei Han, Guoshuang Xu, Jin Zhao, Shiren Sun

“…The RSF model we established for class IV ± V LN patients, incorporating seven risk factors, exhibits superior survival prediction and provides more precise prognostic stratification.…”
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Pro‐adrenomedullin as an independent predictive biomarker for heart failure in atrial fibrillation and flutter by Gaifeng Hu, Xiaodong Peng, Liu He, Yiwei Lai, Nian Liu, Xin Li, Caihua Sang, Jianzeng Dong, Changsheng Ma

“…Kaplan–Meier survival analysis and area under the receiver operating characteristic (ROC) curve assessments were conducted to evaluate predictive performance. Results Over a follow‐up of 14.2 years, 222 cases (21.1%) of HF were documented in the discovery cohort, while 117 cases (38.4%) occurred over 13.8 years in the replication cohort. …”
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Identifying G-Protein Coupled Receptors Using Mixed-Feature Extraction Methods and Machine Learning Methods by Chunyan Ao, Lin Gao, Liang Yu

“…We combine three individual features, such as 400D, N-gram and Parallel correlation pseudo amino acid composition (PC-PseAAC), using mixed-feature representation methods, which are evaluated by Random Forest, Na&#x00EF;ve Bayes, and J48 for classification purposes. …”
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Angiogenesis Dynamics: A Computational Model of Intravascular Flow Within a Structural Adaptive Vascular Network by Sahar Jafari Nivlouei, Ana Guerra, Jorge Belinha, Naside Mangir, Sheila MacNeil, Christiane Salgado, Fernando Jorge Monteiro, Renato Natal Jorge

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A predictive analytics approach with Bayesian-optimized gentle boosting ensemble models for diabetes diagnosis by Behnaz Motamedi, Balázs Villányi

“…Effective disease management necessitates the accurate and timely prediction of lung cancer and diabetes. Machine learning (ML) based models have garnered attention in the realm of predictive healthcare, with ensemble methods, in particular, bolstering algorithms to improve classification performance. …”
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EFFICACY OF EXTRACORPOREAL ELECTROMAGNETIC STIMULATION FOR THE TREATMENT OF URINARY INCONTINENCE AND THE PREDICTIVE FACTORS FOR SATISFACTION by Funda Güngör Uğurlucan, Cenk Yaşa, Nalan Çapan, İnci Sema Taş, Emircan Ertürk, Önay Yalçın

“…We aim to analyze the subjective and objective outcomes of ExMS treatment and evaluate factors that could predict satisfaction. Material and Method: Patients who underwent ExMS treatment for UI were evaluated. …”
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Distributed Model Predictive Cross-Dimensional Formation Control for Heterogeneous Multiagent Systems by Haitao Liu, Zhaoxin Li, Qingqun Mai, Haochun Liu, Xuehong Tian

“…In this paper, a distributed predefined-time model predictive formation control method is proposed for second-order multidimensional cross-dimensional heterogeneous multiagent systems (HMASs) with collision avoidance, switching topology and formation transformation. …”
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Predictive Framework for Sustainable Engineering through Machine Learning and Cross-Sector Collaboration by Choudhary Abhik, Adhikari Upasana, Roy Dipankar, Gupta Subir, Roy Priyanka, Bhaduri Aparna

“…Unlike traditional rule-based and qualitative evaluations, the proposed method measures diverse parameters like funding streams, policy advocacy, and stakeholder participation to construct a comprehensive model of collaboration at cross-sectoral levels. …”
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Predictive Modeling of the Softness of Facial Tissue Products: A Spectral Analysis Approach by Yong Ju Lee, Ji Eun Cha, Geon-Woo Kim, Tai-Ju Lee, Hyoung Jin Kim

“…This work highlights the potential of combining spectral analysis and machine learning for objective softness evaluation.…”
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Predictive Study on the Cutting Energy Efficiency of Dredgers Based on Specific Cutting Energy by Junlang Yuan, Ke Yang, Taiwei Yang, Haoran Xu, Ting Xiong, Shidong Fan

“…Subsequently, five machine learning algorithms, such as RF and XGBoost, are used in combination with a grid search to find the optimal hyperparameters, and Lasso is used as the meta-learner to integrate the prediction results. The experimental results show that the Random Forest and Stacking models have high prediction accuracy for slurry concentration, cutter motor power, and slurry flow rate, verifying the feasibility of this method.…”
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Utilizing machine learning for predictive maintenance of production machinery in small and medium enterprises by Yopa Eka Prawatya, Noveicalistus H Djanggu, Ratih Rahmahwati

“…Machine learning is a pertinent statistical method for predictive maintenance, enabling the early detection of machine failures and the implementation of preventive measures through a model. …”
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Advanced Deep Learning Based Predictive Maintenance of DC Microgrids: Correlative Analysis by M. Y. Arafat, M. J. Hossain, Li Li

“…The achieved decremental MAE scores from 12.102 (advanced RNN) to 10.182 (advanced GRU) to 8.263 (advanced LSTM) and incremental R² scores from 0.941 (advanced RNN) to 0.958 (advanced GRU), and finally to 0.971 (advanced LSTM) demonstrate strong predictive capabilities of all, while the proposed advanced LSTM method outperforming other counterparts. …”
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Evaluating epidemic forecasts in an interval format. by Johannes Bracher, Evan L Ray, Tilmann Gneiting, Nicholas G Reich

“…This article provides an overview of how established methods for the evaluation of quantile and interval forecasts can be applied to epidemic forecasts in this format. …”
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Efficacy and predictive biomarkers of immunotherapy in Epstein-Barr virus-associated gastric cancer by Lin Shen, Xiaochen Zhao, Zhenghang Wang, Yuezong Bai, Feilong Zhao, Zhi Peng, Jinping Cai, Tong Xie, Shuang Tong, Xiaofan Wei

“…The value of EBV infection for predicting ICB efficacy was evaluated among 95 patients with advanced or metastatic GC receiving ICB. …”
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