Multiparameter body composition analysis on chest CT predicts clinical outcomes in resectable non-small cell lung cancer by Yilong Huang, Hanxue Cun, Zhanglin Mou, Zhonghang Yu, Chunmei Du, Lan Luo, Yuanming Jiang, Yancui Zhu, Zhenguang Zhang, Xin Chen, Bo He, Zaiyi Liu

“…Assessing muscle mass, quality, and adipose tissue helps predict overall survival in NSCLC. The quantity and distribution of body composition can contribute to unraveling the adiposity paradox. …”
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Predictive value of enhanced CT and pathological indicators in lymph node metastasis in patients with gastric cancer based on GEE model by Ling Yang, Yingying Ding, Dafu Zhang, Guangjun Yang, Xingxiang Dong, Zhiping Zhang, Caixia Zhang, Wenjie Zhang, Youguo Dai, Zhenhui Li

“…Abstract Objectives A predictive model was developed based on enhanced computed tomography (CT), laboratory test results, and pathological indicators to achieve the convenient and effective prediction of single lymph node metastasis (LNM) in gastric cancer. …”
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Development and validation of a novel bleeding risk prediction tool for aspirin users with a low body mass index by Lu Yifang, Lei Wanlin, Wang Maofeng

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Evolving prognostic paradigms in lung adenocarcinoma with brain metastases: a web-based predictive model enhanced by machine learning by Min Liang, Zhiwen Zhang, Langming Wu, Mafeng Chen, Shifan Tan, Jian Huang

“…We pinpointed independent prognostic features for overall survival (OS) using Lasso regression analyses. Predictive models were built using Random Forest, XGBoost, Decision Trees, and Artificial Neural Networks, with their performance evaluated via metrics including the area under the receiver operating characteristic curve (AUC), calibration plots, brier score, and decision curve analysis (DCA). …”
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Effect of Sterilization Methods on the Storage Quality of Soybean Protein-based Small Crisp Meat and Its Shelf Life Prediction by Ying SUN, Bin ZHOU, Long WANG, Shen LIU, Binglin LU, Lianzhou JIANG, Juyang ZHAO, Xiuqing ZHU

“…The Q10 model was utilized to obtain the shelf life model of plant-based small crispy meat precooked dish based on the TVB-N value, and predicted its shelf life at 4 ℃ storage temperature. …”
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Water quality prediction and carbon reduction mechanisms in wastewater treatment in Northwest cities using Random Forest Regression model by Jingjing Sun, Xin Guan, Xiaojun Sun, Xiaojing Cao, Yepei Tan, Jiarong Liao

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T-cell receptor beta variable gene polymorphism predicts immune-related adverse events during checkpoint blockade immunotherapy by Linghua Wang, Siqing Fu, Aung Naing, Funda Meric-Bernstam, Carl Morrison, Joud Hajjar, Mingxuan Xu, Anas Alshawa, Bettzy Stephen, Ying Yuan, Jordi Rodon Ahnert, Abdulrazzak Zarifa, Shrutii Sarda, Timothy Looney, Sapna P Patel, Geoffrey M Lowman, Dzifa Yawa Duose, Jeffrey M Conroy, Evan Kwiatkowski

“…Germline-encoded TRBV polymorphisms may serve as a predictive biomarker of severe irAEs.…”
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Challenges in Predicting the Filtration Performance of a Novel Sewn Mask: Scale-up from Filter Holder to Mannequin Measurements by Audrey J. Dang, Benjamin M. Kumfer, J. Tyler Bertroche, Jane Olson Glidden, Christopher R. Oxford, Udayabhanu Jammalamadaka, Mary Ruppert-Stroescu, Alexander R. Scott, Jason A. Morris, Connie Gan, Jesse Hu, Bradley King, David I. A. Dhanraj, Shruti Choudhary, Pratim Biswas, Richard L. Axelbaum, Kathleen W. Meacham, Brent J. Williams

“…We investigate whether characterizing a material in a filter holder at a range of face velocities enabled precise prediction of the filtration performance of a novel sewn mask design. …”
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Enhanced Adaptive Neural-Fuzzy Inference System for Dynamic Time Series Prediction Using Self-Feedback and Hybrid Training by Andrew Topper, Honglei Yao

“…Predicting time series, especially those originating from chaotic and nonlinear dynamic systems, is a critical research area with broad applications across various fields. …”
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Endothelial Activation and Stress Index (EASIX) to predict mortality after allogeneic stem cell transplantation: a prospective study by Axel Benner, Peter Dreger, Grzegorz W Basak, Christian Koenecke, Olaf Penack, Christophe Peczynski, Lucia López Corral, Ivan Moiseev, Hélène Schoemans, Zinaida Peric, Thomas Luft, Simona Sica, Mutlu Arat, Maija Itäla-Remes, Nicolaas P M Schaap, Michal Karas, Ludek Raida, Thomas Schroeder, Elisabetta Metafuni, Tulay Ozcelik, Brenda M Sandmaier, Lambros Kordelas

“…Background We previously reported that the “Endothelial Activation and Stress Index” (EASIX; ((creatinine×lactate dehydrogenase)÷thrombocytes)) measured before start of conditioning predicts mortality after allogeneic hematopoietic stem cell transplantation (alloSCT) when used as continuous score. …”
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Prevalence, influencing factors, and prediction model construction of anemia in ankylosing spondylitis based on real-world data: An exploratory study. by Yifan Gong, Kun Yang, Zhaoyang Geng, Hongxiao Liu

“…The logistic model constructed based on these indicators for predicting the risk of anemia in AS demonstrated good efficacy.…”
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In-silico tool based on Boolean networks and meshless simulations for prediction of reaction and transport mechanisms in the systemic administration of chemotherapeutic drugs. by Fabián Mauricio Vélez Salazar, Iván David Patiño

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Predictive factors of thrombosis during autologous stem cell transplantation in multiple myeloma: Experience from EHU Oran (Algeria) by Mohammed Amine BEKADJA, Brahim BENZINEB, Mansour BELKACEM, Hafida OUDJERIOUAT, Badra ENTASOLTAN, Soufi OSMANI, Kamila AMANI, Samira BOUCHAMA, Leila CHAREF, Mohamed BRAHIMI, Abdessamad ARABI, Rachir Amar BOUHASS, Nabil YAFOUR

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Impact of hepatic steatosis on the efficacy of antiviral treatment for chronic hepatitis B and the establishment of predictive model: a cohort study by Guanghui Ren, Kaining Jia, Shi Yin, Yunpeng Guan, Qingwei Cong, Ying Zhu

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Developing clinical prognostic models to predict graft survival after renal transplantation: comparison of statistical and machine learning models by Getahun Mulugeta, Temesgen Zewotir, Awoke Seyoum Tegegne, Mahteme Bekele Muleta, Leja Hamza Juhar

“…This study aimed to develop prognostic models for predicting renal graft survival and compare the performance of statistical and machine learning models. …”
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Coupling ICESat-2 and Sentinel-2 data for inversion of mangrove tidal flat to predict future distribution pattern of mangroves by Xiaoyong Ming, Yichao Tian, Qiang Zhang, Yali Zhang, Jin Tao, Junliang Lin

“…A detailed topography survey of tidal flat is essential for exploring how tidal flat ecosystems respond to environmental changes and for predicting morphological shifts, thereby impacting the protection and restoration of mangrove ecosystems. …”
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AI-driven prediction of drug activity against Toxoplasma gondii: Data augmentation and deep neural networks for limited datasets by Natalia V. Karimova, Ravithree D. Senanayake

“…By leveraging AI and data augmentation approach, this study provides a powerful tool for pIC50 predictions of TgDHFR inhibitors, which can be adapted to other systems.…”
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Men’s internet sex addiction predicts sexual objectification of women even after taking pornography consumption frequency into account by Pavla Novakova, Edita Chvojka, Anna Ševčíková, Lukas Blinka, Paul Wright, Steven Kane

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Inflamed immune phenotype predicts favorable clinical outcomes of immune checkpoint inhibitor therapy across multiple cancer types by Jeanne Shen, Sergio Pereira, Chan-Young Ock, Yung-Jue Bang, Seulki Kim, Sehhoon Park, Se-Hoon Lee, George A Fisher, Young Kwang Chae, Yoon-La Choi, Jin-Haeng Chung, Tony S K Mok, Leeseul Kim, Jun-Eul Hwang, Gahee Park, Sanghoon Song, Seunghwan Shin, Yoojoo Lim, Wonkyung Jung, Heon Song, Hyojin Kim, Taebum Lee, Sukjun Kim, Chang Ho Ahn, Seokhwi Kim, Ben W Dulken, Stephanie Bogdan, Maggie Huang, Chiyoon Oum, Siraj M. Ali

“…Here, we investigate artificial intelligence (AI)-based immune phenotypes capable of predicting ICI clinical outcomes in multiple solid tumor types.Methods Lunit SCOPE IO is a deep learning model which determines the immune phenotype of the tumor microenvironment based on TIL analysis. …”
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Prediction of Hourly PM2.5 and PM10 Concentrations in Chongqing City in China Based on Artificial Neural Network by Qingchun Guo, Zhenfang He, Zhaosheng Wang

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