Predictive and prognostic significance of loss of heterozygosity in ABC transporter genes in breast cancer by M. M. Tsyganov, M. K. Ibragimova, E. Yu. Garbukov, O. D. Bragina, E. A. Zdereva, E. A. Usynin, N. V. Litviakov

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Quantifying Suicide Risk in Prostate Cancer: A SEER-Based Predictive Model by Jiaxing Du, Fen Zhang, Weinan Zheng, Xue Lu, Huiyi Yu, Jian Zeng, Sujun Chen

“…Time-dependent ROC analysis indicated strong accuracy in predicting suicide risk. Calibration plots displayed high concordance between predicted probabilities and actual outcomes, Kaplan-Meier analysis confirmed the model’s significant discriminative ability among risk groups. …”
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Predictive modeling of air quality in the Tehran megacity via deep learning techniques by Abdullah Kaviani Rad, Mohammad Javad Nematollahi, Abbas Pak, Mohammadreza Mahmoudi

“…The present study aims to forecast the concentrations of various air pollutants, including CO, O3, NO2, SO2, PM10, and PM2.5, from 2013 to 2023 in the Tehran megacity, Iran, via deep learning (DL) models and evaluate their effectiveness over conventional machine learning (ML) methods. …”
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Construction and validation of a predictive model for malignant tumors in patients with membranous nephropathy by Yaling Zhai, Shuaigang Sun, Wenhui Zhang, Huijuan Tian, Zhanzheng Zhao

“…All patients were randomly allocated into a training cohort (n = 584) and a validation cohort (n = 194) in a 3:1 ratio. A predictive model was developed using regression analysis, and its performance was evaluated in terms of discrimination, calibration, and clinical utility through the area under the ROC curve (AUC), calibration curve, and decision curve analysis (DCA). …”
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The predictive value of suPAR for glomerular segmental sclerosis lesions in renal pathology by Zurong Zhang, Chongbin Liu, Yachun Han, Daming Li, Yao Huang, Kewen Shi, Shiyu Xia, Jinying Wei, Hong Liu, Lin Sun, Xuejing Zhu, Shuguang Yuan

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Smart Farming: Enhancing Urban Agriculture Through Predictive Analytics and Resource Optimization by Eman Ali Aldhahri, Abdulwahab Ali Almazroi, Monagi Hassan Alkinani, Nasir Ayub, Elham Abdullah Alghamdi, Nourah Fahad Janbi

“…Optimal agricultural methods need precise crop health and ecological strain monitoring. …”
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The prognostic predictive value of indirect bilirubin-inflammation score in patients with nasopharyngeal carcinoma by JI Huojin, LI Jun, LUO Yonglin, QIN Weiling, YE Yinxin, CAI Yonglin

“…The nomogram, which integrated age, sex, clinical stage, and IBI score, demonstrated good clinical utility and predictive ability, as evaluated by the DCA. Significant interaction was found between IBIL and PLR, and inflammatory markers did not exhibit any medicating effects on the influence of IBIL on NPC survival. …”
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Development and validation of a predictive model for suicidal thoughts and behaviors among freshmen by Yan Qin, Sifang Niu, Xingmeng Niu, Yangziye Guo, Yu Sun, Shuzhang Hu, Fuqin Mu, Ying Zhang, Min Liu, Jianli Wang, Yan Liu

“…This study assessed the impact of prospective baseline variables on the risk of new STB onset among first-year university students over two years and developed a multivariate risk prediction model. Methods 4,560 first-year university students (38.4% males, mean age:18.34) from China participated and completed this prospective cohort study over a three-year period from 2018 to 2020. …”
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Advanced predictive machine and deep learning models for round-ended CFST column by Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy

“…A user-friendly, Python-based interface was also developed, enabling real-time predictions for practical engineering applications. …”
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Acoustic signatures of bulbar ALS: Predictive modeling with sustained vowels and LightGBM by Zahra Farrokhi, Seyed Amirali Zakavi, Arian Sarafraz, Maryam Valifard, Salar Yousefzadeh, Zahra Mashhadi Tafreshi, Omid Anbiyaee, Navid Rostami, Mahsa Asadi Anar, Niloofar Deravi

“…Model performance and feature importance were evaluated. Results: The model performed well with high predictability, yielding an RMSLE of 0.162 and most predictions closely correlating with actual diagnoses. …”
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Predictive biomarkers for cardiometabolic risk in postmenopausal women: insights into visfatin, adropin, and adiponectin by Anna Maria Cybulska, Daria Schneider-Matyka, Ireneusz Walaszek, Mariusz Panczyk, Dorota Ćwiek, Anna Lubkowska, Elżbieta Grochans, Kamila Rachubińska, Katarzyna Malewicz, Mariusz Chabowski, Mariusz Chabowski

“…Furthermore, circulating adiponectin positively correlated with HDL, and negatively with HOMA-IR.ConclusionsAdiponectin is a promising biomarker for predicting cardiometabolic risk in postmenopausal women.…”
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Validation of a predictive model for platelet transfusion refractoriness in patients with hematological diseases by HUANG Xiulan, YUE Shuhan, CAI Qun, LU Liqi, HE Mengzhen, LEI Qiao, LIU Caoyi, ZHANG Jingwei

“…The resulting PTR prediction model exhibits moderate predictive efficacy and clinical benefit.…”
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Establishment and validation of a predictive model for coronary artery lesions in children with KDSS by Zhihui Zhao, Yue Yuan, Lu Gao, Hongxia Li, Qirui Li, Zhen Zhen, Shunying Zhao, Yanyan Xiao

“…Logistic regression analysis was employed to identify the most predictive variables. Utilizing a training set (n = 72), we constructed a logistic regression model to predict CALs in children with KDSS. …”
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Predictive Value of Blood and Echocardiographic Indicators for Nonvalvular Atrial Fibrillation in Postmenopausal Women by Lei Song, Xiao‐Ping Shen, Jian‐Rong Cai, Hong‐Lei Zhang, Gui‐Ru Li, Jing Shi

“…ABSTRACT Objective To evaluate the association and predictive value of midregional pro‐atrial natriuretic peptide (MR‐proANP), bone morphogenetic protein (BMP‐7), and left atrial diameter (LAD) with nonvalvular atrial fibrillation (NVAF) in postmenopausal women. …”
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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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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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