Associations between age, red cell distribution width and 180-day and 1-year mortality in giant cell arteritis patients: mediation analyses and machine learning in a cohort study by Si Chen, Rui Nie, Xiaoran Shen, Yan Wang, Haixia Luan, Xiaoli Zeng, Yanhua Chen, Hui Yuan

“…Methods Clinical data from GCA patients were extracted from the MIMIC-IV (3.0) database. …”
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Biological subphenotypes in patients hospitalized with suspected infection in Thailand: a secondary analysis of a prospective observational studyResearch in context by Prapassorn Poolchanuan, Taylor D. Coston, Viriya Hantrakun, Parinya Chamnan, Gumphol Wongsuvan, Pavan K. Bhatraju, Narisara Chantratita, Direk Limmathurotsakul, T. Eoin West, Shelton W. Wright

“…Patient characteristics were compared after subphenotype assignment, and a parsimonious model was developed to identify patient subphenotypes. …”
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Bayesian reinforcement learning models reveal how great-tailed grackles improve their behavioral flexibility in serial reversal learning experiments by Lukas, Dieter, McCune, Kelsey, Blaisdell, Aaron, Johnson-Ulrich, Zoe, MacPherson, Maggie, Seitz, Benjamin, Sevchik, August, Logan, Corina

“…Cues are reliably associated with a reward, but the association between the reward and the cue frequently changes. Here, we apply and expand newly developed Bayesian reinforcement learning models to gain additional insights into how individuals might dynamically modulate their behavioral flexibility if they experience serial reversals. …”
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Defining Nocturnal Polyuria in Adolescents by Tasmia Promi, Anthony Brooks, Gulzhan Tologonova, Marie-Claire Roberts, Sarita Dhuper, Meseret Tena, Oluwatoyin Bamgbola, Monique Hanono, Jeffrey P. Weiss, Karel Everaert, Tine DeBacker, Thomas F. Monaghan, Louis Salciccioli, Stephen Wadowski, Elka Jacobson-Dickman, Jason M. Lazar

“…Receiver operating characteristic (ROC) curves were used to test the performance of different NUP values in predicting nocturia. …”
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Leveraging Comprehensive Echo Data to Power Artificial Intelligence Models for Handheld Cardiac Ultrasound by D.M. Anisuzzaman, PhD, Jeffrey G. Malins, PhD, John I. Jackson, PhD, Eunjung Lee, PhD, Jwan A. Naser, MBBS, Behrouz Rostami, PhD, Grace Greason, BA, Jared G. Bird, MD, Paul A. Friedman, MD, Jae K. Oh, MD, Patricia A. Pellikka, MD, Jeremy J. Thaden, MD, Francisco Lopez-Jimenez, MD, MSc, MBA, Zachi I. Attia, PhD, Sorin V. Pislaru, MD, PhD, Garvan C. Kane, MD, PhD

“…Study data were collected between January 1, 2018 and February 29, 2024. …”
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Exploring and detecting predictors associated with survival and mortality of cervical cancer patients: a 10-year retrospective study by Shaba Muneeha, Raushan Kumar Chaudhary, Vijith Vittal Shetty, Soumya Patil, Uday Venkat Mateti

“…Conclusion We conclude that the 5- and 10-year survival rates for cervical cancer patients were found to be 51.2% and 42.9%, respectively. Advanced age, underweight, postmenopausal status, advanced cancer stage, poor cancer cell differentiation and chemotherapy-based treatment were significant predictor of mortality and vice-versa for survival which might guide clinicians and policymakers in making informed clinical decisions to combat cervical cancer.…”
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Machine learning for predicting severe dengue in Puerto Rico by Zachary J. Madewell, Dania M. Rodriguez, Maile B. Thayer, Vanessa Rivera-Amill, Gabriela Paz-Bailey, Laura E. Adams, Joshua M. Wong

“…Results Among the 1708 laboratory-confirmed dengue cases, 24.3% were classified as severe. Gradient boosting algorithms achieved the highest predictive performance, with an AUC-ROC of 97.1% (95% CI: 96.0–98.3%) for CatBoost using the full 40-variable feature set. …”
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Electrocardiography-based artificial intelligence predicts the upcoming future of heart failure with mildly reduced ejection fraction by Dae-Young Kim, Sang-Won Lee, Dong-Ho Lee, Sang-Chul Lee, Sang-Chul Lee, Ji-Hun Jang, Sung-Hee Shin, Dae-Hyeok Kim, Dae-Hyeok Kim, Wonik Choi, Wonik Choi, Yong-Soo Baek, Yong-Soo Baek, Yong-Soo Baek

“…Following the predictability analysis with another group of 953 patients for improvements of follow-up EF in HFmrEF, the patients were grouped into three clusters based on the AI-Euclidean distance; Cluster 1 had the most severe cases and poorer outcomes than Clusters 2 (p < 0.001) and 3 (p < 0.001).ConclusionsAI-ECG presents an innovative approach for the prognostic stratification of cardiac contractility in patients with HFmrEF. …”
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Enhanced characterization of non-metallic inclusions in ultra-high-strength steels using advanced synchrotron-based X-ray absorption spectroscopy and chemometric analysis by Mourad Kharbach, Mohammed Alaoui Mansouri, Ekta Rani, Harishchandra Singh, Tuomas Alatarvas, Brice Sarpi, Lin Zhu, Yuran Niu, Alexei Zakharov, Ilkka Launonen, Marko Huttula, Mikko J. Sillanpaa, Samuli Urpelainen

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Translation and Validation of the Edinburgh Postnatal Depression Scale for Eritrea: A Screening Tool for Postpartum Depression in Primary Health Care Facilities by Gebregziabher NK, Netsereab TB, Alazar FA, Fessaha YG, Sium AH, Ghebrehiwet NK

“…This is crucial as PPD is a severe condition affecting maternal and family well-being, and existing tools were not tailored for the Eritrean cultural context.What did the researchers do and find?…”
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Skaitmeninių metodų taikymas praeities kelionių tyrimuose by Rimvydas Laužikas

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Effect of crystalline lens decentration and tilt on visual performance in eyes implanted with bifocal or extended depth of focus intraocular lenses by Yu Zhang, Jiaqing Zhang, Chen Liang, Yifan Xu, Jiaying Wu, Junming Wu, Yifan Zhang, Aixia Jin, Xuhua Tan, Lixia Luo

“…Patients undergoing phacoemulsification with bifocal (Tecnis ZMB00) or extended depth-of-focus (EDOF) (Tecnis ZXR00) IOL implantation were consecutively enrolled. The decentration and tilt of the crystalline lens and the IOL were quantified through the utilization of swept-source optical coherence tomography (SS-OCT, Casia2). …”
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Profile of non-invasive physical health indicators associated with cognitive performance in Chinese older adults: evidence from the China Health and Retirement Longitudinal Study by Xiyu Wei, Chao Li, Dongyu Liu, Jieyi Chen, Yumeng Ju, Jin Liu, Bangshan Liu, Yan Zhang

“…Methods The present study utilized a three-year longitudinal cohort design, with data from the China Health and Retirement Longitudinal Study (CHARLS). 4,869 participants aged 60–97 years from CHARLS wave 2015 and 2018 who were cognitively and physically healthy were included in analysis. …”
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Contribution of cuproptosis and immune-related genes to idiopathic pulmonary fibrosis disease by Chengji Jin, Jia Li, Qiaoyu Li, Lipeng Zhang, Shaomao Zheng, Qiong Feng, Yongjie Li, Yu Zheng, Qiuli Nie, Jin Liang, Jing Wang, Jing Wang

“…Additionally, multiple bioinformatics analyses were employed to identify immune-related biomarkers associated with the diagnosis of IPF, offering valuable insights for future treatment strategies.MethodsFour microarray datasets were selected from the Gene Expression Omnibus (GEO) collection for screening. …”
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Optimasi Data Tidak Seimbang pada Interaksi Drug Target dengan Sampling dan Ensemble Support Vector Machine by Nabila Sekar Ramadhanti, Wisnu Ananta Kusuma, Annisa Annisa

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An Easy and Quick Risk-Stratified Early Forewarning Model for Septic Shock in the Intensive Care Unit: Development, Validation, and Interpretation Study by Guanghao Liu, Shixiang Zheng, Jun He, Zi-Mei Zhang, Ruoqiong Wu, Yingying Yu, Hao Fu, Li Han, Haibo Zhu, Yichang Xu, Huaguo Shao, Haidan Yan, Ting Chen, Xiaopei Shen

“…MethodsA total of 5125 patients with sepsis from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database were divided into training, validation, and test sets. …”
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Impact of shear wave elastography and attenuation imaging for predicting life-threatening event in patients with metabolic dysfunction-associated steatotic liver disease by Yudai Fujiwara, Hidekatsu Kuroda, Tamami Abe, Tomoaki Nagasawa, Ippeki Nakaya, Asami Ito, Takuya Watanabe, Kenji Yusa, Hiroki Sato, Akiko Suzuki, Kei Endo, Yuichi Yoshida, Takayoshi Oikawa, Keisuke Kakisaka, Kei Sawara, Toshifumi Tada, Akio Miyasaka, Takuma Oguri, Naohisa Kamiyama, Takayuki Matsumoto

“…The LSM and AC cut off values were 8.37 kPa and 0.62 dB/cm/MHz, respectively. The cumulative incidence rate in Groups A, B, C, and D were 11.2%, 12.2%, 29.5%, and 31.0%/5years, respectively (p < 0.05). …”
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Diagnostic Effectiveness of Transforming Growth Factor Beta 1 in Assessing the Risk of Developing Graft Dysfunction in Liver Recipient Children by R. M. Kurabekova, O. M. Tsiroulnikova, I. E. Pashkova, A. G. Olefirenko, O. E. Gichkun, L. V. Makarova, R. A. Monakhov, P. O. Shevchenko

“…Materials and methods. 95 children aged 3 to 73 months with liver cirrhosis of various etiologies were surveyed. All the patients underwent liver transplantation (LT) from a living related donor. …”
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The synergistic effect of the triglyceride-glucose index and a body shape index on cardiovascular mortality: the construction of a novel cardiovascular risk marker by Hao-ming He, Ying-ying Xie, Qiang Chen, Yi-ke Li, Xue-xi Li, Sun-jing Fu, Na Li, Yan-ru Han, Yan-xiang Gao, Jin-gang Zheng

“…The associations of the TyG index and ABSI with cardiovascular mortality were investigated via Cox regression analysis and restricted cubic splines. …”
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Assessment of six insulin resistance surrogate indexes for predicting stroke incidence in Chinese middle-aged and elderly populations with abnormal glucose metabolism: a nationwide... by Luqing Jiang, Tengxiao Zhu, Wenjing Song, Ying Zhai, Yu Tang, Fengxia Ruan, Zichen Xu, Lei Li, Xia Fu, Daoqin Liu, Aidong Chen, Qiwen Wu

“…Methods Data from the China Health and Retirement Longitudinal Study (CHARLS) were analysed in this study. Multivariate logistic regression models were applied to analyse the relationships of IR surrogate indexes with stroke risk. …”
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