Zobrazeno 1 - 10
of 1 107
pro vyhledávání: '"RISK PREDICTION MODELS"'
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-14 (2024)
Abstract The current investigation aimed to develop a novel approach for risk prediction modeling of clinical outcomes in common diseases based on computational and human intelligence techniques with no a priori input on risk factors using real-world
Externí odkaz:
https://doaj.org/article/59050ac1ec924837b777ff49a67d2b41
Autor:
Will HG Cheng, Weinan Dong, Emily TY Tse, Carlos KH Wong, Weng Y Chin, Laura E Bedford, Daniel YT Fong, Welchie WK Ko, David VK Chao, Kathryn CB Tan, Cindy LK Lam
Publikováno v:
Journal of Diabetes Investigation, Vol 15, Iss 9, Pp 1317-1325 (2024)
ABSTRACT Aims/Introduction Two Hong Kong Chinese non‐laboratory‐based prediabetes/diabetes mellitus (pre‐DM/DM) risk models were developed using logistic regression (LR) and machine learning, respectively. We aimed to evaluate the models' valid
Externí odkaz:
https://doaj.org/article/8827314f1b724640b05af19e1d064415
Autor:
Chun Pan
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 17, Iss 1, Pp 1-13 (2024)
Abstract The evaluation of financial sharing centres in enterprises typically relies on outdated financial data, lacks comprehensive assessment, and presents risks such as employee misconduct. To address these challenges, we propose a risk prediction
Externí odkaz:
https://doaj.org/article/1ac2207e516d4e63abfb6eb0ba6a0335
Publikováno v:
Frontiers in Public Health, Vol 12 (2024)
ObjectiveThe purpose of this study was to identify independent risk factors affecting patient survival and explore predictors of severe cases of coronavirus disease 2019 (COVID-19).MethodsWe conducted a retrospective, observational, case–control st
Externí odkaz:
https://doaj.org/article/fc6544b6bb614bdb8598cba6306de7cc
Publikováno v:
Revista de Investigación Clínica, Vol 76, Iss 4 (2024)
Background: Several models have been developed to assess bleeding risk in patients with venous thromboembolism, such as HAS-BLED, but their external validity has not been adequately assessed. Objective: The objective of the study was to evaluate the
Externí odkaz:
https://doaj.org/article/cf412a5d293e4be5be38c8490ecdd698
Autor:
Yue Cai, Yu-Qing Cai, Li-Ying Tang, Yi-Han Wang, Mengchun Gong, Tian-Ci Jing, Hui-Jun Li, Jesse Li-Ling, Wei Hu, Zhihua Yin, Da-Xin Gong, Guang-Wei Zhang
Publikováno v:
BMC Medicine, Vol 22, Iss 1, Pp 1-18 (2024)
Abstract Background A comprehensive overview of artificial intelligence (AI) for cardiovascular disease (CVD) prediction and a screening tool of AI models (AI-Ms) for independent external validation are lacking. This systematic review aims to identif
Externí odkaz:
https://doaj.org/article/3cb1606e112c47adab33f9058c72e113
Autor:
Olav Toai Duc Nguyen, MD, Ioannis Fotopoulos, MS, Maria Markaki, PhD, Ioannis Tsamardinos, PhD, Vincenzo Lagani, PhD, Oluf Dimitri Røe, PhD
Publikováno v:
JTO Clinical and Research Reports, Vol 5, Iss 4, Pp 100660- (2024)
Background: Improving the method for selecting participants for lung cancer (LC) screening is an urgent need. Here, we compared the performance of the Helseundersøkelsen i Nord-Trøndelag (HUNT) Lung Cancer Model (HUNT LCM) versus the Dutch-Belgian
Externí odkaz:
https://doaj.org/article/cbd1147f52fb4484b9fa756a7b4eb45d
Autor:
Petras Navickas, Laura Lukavičiūtė, Sigita Glaveckaitė, Arvydas Baranauskas, Agnė Šatrauskienė, Jolita Badarienė, Aleksandras Laucevičius
Publikováno v:
Medicina, Vol 60, Iss 9, p 1511 (2024)
Background and Objectives: In the context of female cardiovascular risk categorization, we aimed to assess the inter-model agreement between nine risk prediction models (RPM): the novel Predicting Risk of cardiovascular disease EVENTs (PREVENT) equat
Externí odkaz:
https://doaj.org/article/4c04945c4843410b91689596c5501d3c
Publikováno v:
Frontiers in Oncology, Vol 13 (2024)
PurposeSeveral surgical risk models are widely utilized in general surgery to predict postoperative morbidity. However, no studies have been undertaken to examine the predictive efficacy of these models in biliary tract cancer patients, and other per
Externí odkaz:
https://doaj.org/article/cf4cd05cf66f4e8e88c66dedd5552ae3
Autor:
James S. Hampton, Ryan P.W. Kenny, Colin J. Rees, William Hamilton, Claire Eastaugh, Catherine Richmond, Linda Sharp
Publikováno v:
EClinicalMedicine, Vol 64, Iss , Pp 102204- (2023)
Summary: Background: Colorectal cancer (CRC) incidence and mortality are increasing internationally. Endoscopy services are under significant pressure with many overwhelmed. Faecal immunochemical testing (FIT) has been advocated to identify a high-ri
Externí odkaz:
https://doaj.org/article/73fbba1db9c64fe880db6e97f532f8c0