Development of the Combined Assessment of Risk Encountered in Surgery (CARES) surgical risk calculator for prediction of postsurgical mortality and need for intensive care unit adm... by Yiong Huak Chan, Diana Xin Hui Chan, Hairil Rizal Abdullah, Yilin Eileen Sim, Ruban Poopalalingam

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Diverse regulated cell death patterns and immune traits in kidney allograft with fibrosis: a prediction of renal allograft failure based on machine learning, single-nucleus RNA seq... by Yuqing Li, Jiandong Zhang, Xuemeng Qiu, Yifei Zhang, Jiyue Wu, Qing Bi, Zejia Sun, Wei Wang

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中国青年缺血性卒中的疾病负担变化趋势分析及预测Analysis and Prediction of the Trend in Disease Burden of Ischemic Stroke among Chinese Young Adults by 王小军，杨珂珂，吴健恒，林铎，李晨威，彭慧渊(WANG Xiaojun, YANG Keke, WU Jianheng, LIN Duo, LI Chenwei, PENG Huiyuan)

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Curating a knowledge base for patients with neurosyphilis: a study protocol of a DEep learning Framework for pErsonalized prediction of Adverse prognosTic events in NeuroSyphilis (... by Jun Li, Tian Tian, Huachun Zou, Hanlin Zhang, Jun Zou, Zhen Lu, Junfeng Wang, Liuqing Yang, Bingyi Wang, Leiwen Fu, Siyang Liu, Weibo Wu, Zhipeng Peng

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Assessment of Masonry-Infilled Steel Frames Using Existing Experimental Tests Database in Comparison to Standards by Ciprian Bratu, Dario Šokić, Naida Ademović, Ercan Isik, Borko Bulajić, Dorin Radu, Marijana Hadzima-Nyarko

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Online tools to predict individualised survival for primary oesophageal cancer patients with and without pathological complete response after neoadjuvant therapy followed by oesoph... by Jie Zhang, Xiang Chen, Dong Dong, Lijie Tan, Yajie Zhang, Hecheng Li, Yuqin Cao, Binhao Huang, Han Tang, Tianzheng Shen, Xijia Feng, Jiahao Zhang, Liqiang Shi, Chengqiang Li, Heng Jiao

“…Key predictors included demographic characteristics, pretreatment clinical stage, surgical approach, pathological information and postoperative treatments. The predictive models for pCR and non-pCR patients demonstrated good calibration and clinical utility, with acceptable discrimination that surpassed that of the current tumour, node, metastases staging system.Conclusions The web-based dynamic nomograms for pCR (https://predict-survival.shinyapps.io/pCR-eso/) and non-pCR patients (https://predict-survival.shinyapps.io/non-pCR-eso/) developed in this study can facilitate the calculation of OS probability for individual patients undergoing neoadjuvant therapy and radical oesophagectomy, aiding clinicians and patients in making personalised treatment decisions.…”
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Ensemble Machine Learning Classifiers Combining CT Radiomics and Clinical-Radiological Features for Preoperative Prediction of Pathological Invasiveness in Lung Adenocarcinoma Pres... by Yunhua Li BS, Jianbang Ding MS, Kun Wu MS, Wanyin Qi BS, Shanyue Lin BS, Gangwen Chen BS, Zhichao Zuo PhD

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Efectos de las actividades en la naturaleza en la predicción de la satisfacción de la Educación Física (Effects of outdoor activities in predicting Physical Education satisfaction)... by Antonio Baena-Extremera, Antonio Granero-Gallegos

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Development and validation of a diabetes mellitus and prediabetes risk prediction function for case finding in primary care in Hong Kong: a cross-sectional study and a prospective... by Kathryn Choon Beng Tan, Carlos King Ho Wong, Esther Yee Tak Yu, Cindy Lo Kuen Lam, Emily Tsui Yee Tse, Weng Yee Chin, David Vai Kiong Chao, Eric Ho Man Tang, Weinan Dong, Will Ho Gi Cheng, Yuqi Mi, Laura Elizabeth Bedford, Welchie Wai Kit Ko

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Comparative clinical frailty scale and hospital frailty risk score in identifying frailty and predicting mid-term outcomes in older patients with acute coronary syndrome: a multice... by Tan Van Nguyen, Huy Minh Tran, Trinh Kim Thi Ngo

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Viral replication modulated by hallmark conformational ensembles: how AlphaFold-predicted features of RdRp folding dynamics combined with intrinsic disorder-mediated function enabl... by Rachid Tahzima, Rachid Tahzima, Rachid Tahzima, Rachid Tahzima, Justine Charon, Adrian Diaz, Kris De Jonghe, Sebastien Massart, Thierry Michon, Wim Vranken, Wim Vranken, Wim Vranken, Wim Vranken

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Association between estimated glucose disposal rate and prediction of cardiovascular disease risk among individuals with cardiovascular-kidney-metabolic syndrome stage 0–3: a natio... by Jing Tian, Hu Chen, Yan Luo, Zhen Zhang, Shiqiang Xiong, Hanxiong Liu

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Hybrid intelligence systems for reliable automation: advancing knowledge work and autonomous operations with scalable AI architectures by Allan Grosvenor, Anton Zemlyansky, Abdul Wahab, Kyrylo Bohachov, Aras Dogan, Dwyer Deighan

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大脑中动脉闭塞性急性缺血性卒中血管内治疗后不良预后的危险因素分析及预测模型开发 Risk Factors Analysis and Prediction Model Development for Poor Prognosis after Endovascular Treatment of Middle Cerebral Artery Occlusive... by 蒋兰1，傅新民1，2，3，孙梦飞2，李怡萍1 (JIANG Lan1, FU Xinmin1,2,3, SUN Mengfei2, LI Yiping1 )

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Improved Discrete-Time Active Disturbance Rejection Control for Enhancing Dynamics of Current Loop in LC-Filtered SPMSM Drive System by Zibo Li, Haitao Yang, Jin Wang, Yali Wang, Libing Zhou

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Growth Rate Determination of <i>Listeria monocytogenes</i> in Ready-To-Eat Fish Products Under Different Storage Conditions for Possible Shelf-Life Extension by Paolo Cipriani, Elena Dalzini, Elena Cosciani-Cunico, Muhammad-Ehtesham Abdul, Paola Monastero, Daniela Merigo, Stefania Ducoli, Alessandro Norton, Marina-Nadia Losio, Enrico Pavoni

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急性卒中院前诊断识别研究进展(Research Progress in Prehospital Diagnosis and Identification of Acute Stroke) by 王荣，何松，岗瑞娟，王琪，唐宇杰，刘飞凤，杨杰，李刚，林亚鹏(WANG Rong, HE Song, GANG Ruijuan, WANG Qi, TANG Yujie, LIU Feifeng, YANG Jie, LI Gang, LIN Yapeng)

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Prediction of the 70-gene signature (MammaPrint) high versus low risk by nomograms among axillary lymph node positive (LN+) and negative (LN-) Chinese breast cancer patients, a ret... by Jie Lian, Ru Yao, Ying Xu, Linjuan Tan, Fangyuan Chen, Jiahui Zhang, Yang Qu, Lu Gao, Yanna Zhang, Songjie Shen, Qingli Zhu, Xinyu Ren, Lingyan Kong, Bo Pan, Qiang Sun, Yidong Zhou

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How Cybersecurity Leadership Became the New Critical Managerial Competency in Healthcare Administration by Ebone McCoy

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AI in Context: Harnessing Domain Knowledge for Smarter Machine Learning by Tymoteusz Miller, Irmina Durlik, Adrianna Łobodzińska, Lech Dorobczyński, Robert Jasionowski

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