The role of artificial intelligence in hypertensive disorders of pregnancy: towards personalized healthcare
Introduction Guidelines advise ongoing follow-up of patients after hypertensive disorders of
pregnancy (HDP) to assess cardiovascular risk and manage future patient-specific …
pregnancy (HDP) to assess cardiovascular risk and manage future patient-specific …
Mortality prediction with adaptive feature importance recalibration for peritoneal dialysis patients
The study aims to develop AICare, an interpretable mortality prediction model, using
electronic medical records (EMR) from follow-up visits for end-stage renal disease (ESRD) …
electronic medical records (EMR) from follow-up visits for end-stage renal disease (ESRD) …
Comparison of machine learning models including preoperative, intraoperative, and postoperative data and mortality after cardiac surgery
JC Forte, G Yeshmagambetova… - JAMA Network …, 2022 - jamanetwork.com
Importance A variety of perioperative risk factors are associated with postoperative mortality
risk. However, the relative contribution of routinely collected intraoperative clinical …
risk. However, the relative contribution of routinely collected intraoperative clinical …
Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach
Mortality risk prediction can greatly improve the utilization of resources in intensive care
units (ICUs). Existing schemes in ICUs today require laborious manual input of many …
units (ICUs). Existing schemes in ICUs today require laborious manual input of many …
Position paper on the reporting of norepinephrine formulations in critical care from the Society of Critical Care Medicine and European Society of Intensive Care …
PM Wieruszewski, M Leone… - Critical Care …, 2024 - journals.lww.com
OBJECTIVES: To provide guidance on the reporting of norepinephrine formulation labeling,
reporting in publications, and use in clinical practice. DESIGN: Review and task force …
reporting in publications, and use in clinical practice. DESIGN: Review and task force …
Bottom-up and top-down paradigms of artificial intelligence research approaches to healthcare data science using growing real-world big data
Objectives As the real-world electronic health record (EHR) data continue to grow
exponentially, novel methodologies involving artificial intelligence (AI) are becoming …
exponentially, novel methodologies involving artificial intelligence (AI) are becoming …
Discrete-time survival analysis in the critically ill: a deep learning approach using heterogeneous data
Prediction of survival for patients in intensive care units (ICUs) has been subject to intense
research. However, no models exist that embrace the multiverse of data in ICUs. It is an …
research. However, no models exist that embrace the multiverse of data in ICUs. It is an …
[HTML][HTML] Clinical applications of artificial intelligence and machine learning in the modern cardiac intensive care unit
JC Jentzer, AH Kashou, DH Murphree - Intelligence-Based Medicine, 2023 - Elsevier
The depth and breadth of data produced in the modern cardiac intensive care unit (CICU)
poses challenges to clinicians and researchers. Artificial intelligence (AI) and machine …
poses challenges to clinicians and researchers. Artificial intelligence (AI) and machine …
Interpretable machine learning models for predicting venous thromboembolism in the intensive care unit: an analysis based on data from 207 centers
C Guan, F Ma, S Chang, J Zhang - Critical Care, 2023 - Springer
Background Venous thromboembolism (VTE) is a severe complication in critically ill
patients, often resulting in death and long-term disability and is one of the major contributors …
patients, often resulting in death and long-term disability and is one of the major contributors …
Explainable machine-learning algorithms to differentiate bipolar disorder from major depressive disorder using self-reported symptoms, vital signs, and blood-based …
T Zhu, X Liu, J Wang, R Kou, Y Hu, M Yuan… - Computer Methods and …, 2023 - Elsevier
Background and objective Caused by shared genetic risk factors and similar
neuropsychological symptoms, bipolar disorder (BD) and major depressive disorder (MDD) …
neuropsychological symptoms, bipolar disorder (BD) and major depressive disorder (MDD) …