Publications citing HiRID, a high time-resolution ICU dataset v1.1.1

Exploring Risk Factors and Prediction Models for Sudden Cardiac Death with Machine Learning
Younès Youssfi. 2023. Cites: paper

Künstliche Intelligenz in der Neurologie
Katharina Ernst, Jan Rémi. Nervenheilkunde, 2023. Cites: paper

Machine learning applications and challenges in graft-versus-host disease: a scoping review
Ali Hassan Mushtaq, Areez Shafqat, Haneen Thabit Salah et al. Current Opinion in Oncology, 2023. Cites: paper

Heralding a new era of oxytocinergic research: New tools, new problems?
Ferdinand Althammer. Journal of Neuroendocrinology, 2023. Cites: paper

Predicting 7-day unplanned readmission in elderly patients with coronary heart disease using machine learning
Xuewu Song, Yitong Tong, Yi Luo et al. Frontiers in Cardiovascular Medicine, 2023. Cites: paper

Predicting sepsis using deep learning across international sites: a retrospective development and validation study
Michael Moor, Nicolas Bennett, Drago Plečko et al. EClinicalMedicine, 2023. Cites: paper

Machine learning algorithms for predicting outcomes of traumatic brain injury: A systematic review and meta-analysis
Evan Courville, Syed Faraz Kazim, John Vellek et al. Surgical Neurology International, 2023. Cites: paper

Open datasets in perioperative medicine: a narrative review
Leerang Lim, Hyung‐Chul Lee. Anesthesia and Pain Medicine, 2023. Cites: paper

Continuous and early prediction of future moderate and severe Acute Kidney Injury in critically ill patients: Development and multi-centric, multi-national external validation of a machine-learning model
Francesca Alfieri, Andrea Ancona, Giovanni Luigi Tripepi et al. PLoS ONE, 2023. Cites: paper

Machine learning-based prediction of in-ICU mortality in pneumonia patients
Eun‐Tae Jeon, Hyo Jin Lee, Tae Yun Park et al. Scientific Reports, 2023. Cites: paper

Smart Prediction of Circulatory Failure: Machine Learning for Early Detection of Patient Deterioration
Shrouk Hesham Mahmoud, Sahar Selim Soussa, Aya Mohamed Hassan et al. Intelligent Methods, Systems, and Applications (IMSA), 2023. Cites: paper

Smart Police: A Hybrid Deep Learning Model for Crime Proactivity Assessment
M. Vijayalakshmi, Rigzen Norbu. International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2023. Cites: paper

A guide to sharing open healthcare data under the General Data Protection Regulation
Jip W T M de Kok, Miguel Ángel Armengol de la Hoz, Ymke de Jong et al. Scientific Data, 2023. Cites: dataset

Continuous monitoring of patients in and after the acute admission ward to improve clinical pathways: study protocol for a randomized controlled trial (Optimal-AAW)
Sjoerd H. Garssen, Niels Kant, Carlijn A. Vernooij et al. Trials, 2023. Cites: paper

Early warning signals for critical transitions in complex systems
Sandip V. George, Sneha Kachhara, G. Ambika. Physica Scripta, 2023. Cites: paper

Development of Machine Learning Models for Predicting Osteoporosis in Patients with Type 2 Diabetes Mellitus—A Preliminary Study
Xuelun Wu, Furui Zhai, Ailing Chang et al. Diabetes Metabolic Syndrome and Obesity, 2023. Cites: paper

A CT-based radiomics nomogram for distinguishing between malignant and benign Bosniak IIF masses: a two-centre study
Ting Wang, Hsuan‐Chia Yang, Dapeng Hao et al. Clinical Radiology, 2023. Cites: paper

A deep learning algorithm to predict risk of pancreatic cancer from disease trajectories
Davide Placido, Bo Yuan, Jessica Xin Hjaltelin et al. Nature Medicine, 2023. Cites: paper

Uncovering expression signatures of synergistic drug responses via ensembles of explainable machine-learning models
Joseph D. Janizek, Ayse B. Dincer, Safiye Çelik et al. Nature Biomedical Engineering, 2023. Cites: paper

Leveraging physiology and artificial intelligence to deliver advancements in health care
Angela Zhang, Zhenqin Wu, Eric Wu et al. Physiological Reviews, 2023. Cites: paper

Making the Improbable Possible: Generalizing Models Designed for a Syndrome-Based, Heterogeneous Patient Landscape
Joshua Pei Le, Supreeth Prajwal Shashikumar, Atul Malhotra et al. Critical Care Clinics, 2023. Cites: paper

The impact of commercial health datasets on medical research and health-care algorithms
Isabelle Rose I. Alberto, Nicole Rose I. Alberto, Arnab K. Ghosh et al. The Lancet Digital Health, 2023. Cites: paper

Self-Supervised Contrastive Learning for Medical Time Series: A Systematic Review
Ziyu Liu, Azadeh Alavi, Minyi Li et al. Sensors, 2023. Cites: paper

Machine Learning for Predicting Micro- and Macrovascular Complications in Individuals With Prediabetes or Diabetes: Retrospective Cohort Study
Simon Schallmoser, Thomas Züger, Mathias Kraus et al. Journal of Medical Internet Research, 2023. Cites: paper

Machine Learning to Predict Interstage Mortality Following Single Ventricle Palliation: A NPC-QIC Database Analysis
Sudeep D. Sunthankar, Juan Zhao, Wei‐Qi Wei et al. Pediatric Cardiology, 2023. Cites: paper

The impact of inconsistent human annotations on AI driven clinical decision making
Aneeta Sylolypavan, Derek H. Sleeman, Honghan Wu et al. npj Digital Medicine, 2023. Cites: dataset

Swiss Sepsis National Action Plan: A coordinated national action plan to stop sepsis-related preventable deaths and to improve the support of people affected by sepsis in Switzerland
Luregn Jan Schlapbach, Elisa Zimmermann, Sylvain Meylan et al. Frontiers in Medicine, 2023. Cites: paper

Real-time prediction of organ failures in patients with acute pancreatitis using longitudinal irregular data
Jiawei Luo, Lan Lan, Shixin Huang et al. Journal of Biomedical Informatics, 2023. Cites: paper

The data driven intensive care unit
Lucas M. Fleuren. 2023. Cites: dataset, paper

MIMIC-IV, a freely accessible electronic health record dataset
Alistair E. W. Johnson, Lucas Bulgarelli, Lu Shen et al. Scientific Data, 2023. Cites: paper

Artificial Intelligence Framework for Real-Time Prioritization of Inpatient Transport Requests Using Patient Acuity, Destination Urgency, Transporter Availability, Elevator Congestion, and Unit-Level Transfer Demand
Sanjay Kulkarni, Meenal Joshi, Rohan Patil et al. Journal of Health Informatics and Digital Systems, 2023. Cites: paper

Clinical applications of artificial intelligence and machine learning in the modern cardiac intensive care unit
Jacob Colin Jentzer, Anthony H. Kashou, Dennis H. Murphree. Intelligence-Based Medicine, 2023. Cites: paper

Early Predicting the Need for Aftercare Based on Patients Events from the First Hours of Stay – A Case Study
Annika L. Dubbeldam, István Ketykó, Renata Medeiros de Carvalho et al. Lecture notes in business information processing, 2023. Cites: paper

Hemodynamic Monitoring: Current Practice and New Perspectives
Christopher Lai, Jean–Louis Teboul. Elsevier eBooks, 2023. Cites: paper

Machine Learning Techniques for Prognosis Estimation and Knowledge Discovery From Lab Test Results With Application to the COVID-19 Emergency
Alfonso Gerevini, Roberto Maroldi, Matteo Olivato et al. IEEE Access, 2023. Cites: paper

Mortality prediction of patients with sepsis in the emergency department using machine learning models: a retrospective cohort study according to the Sepsis-3 definitions
Signa Vitae, 2023. Cites: paper

OCTFormer: An Efficient Hierarchical Transformer Network Specialized for Retinal Optical Coherence Tomography Image Recognition
Haoran Wang, Xinyu Guo, Kaiwen Song et al. IEEE Transactions on Instrumentation and Measurement, 2023. Cites: paper

Predictive Alarm Prevention by Forecasting Threshold Alarms at the Intensive Care Unit
Jonas Chromik, Bjarne Pfitzner, Nina Ihde et al. Communications in computer and information science, 2023. Cites: paper

Rapid Response System Based on Graph Attention Network for Predicting In-Hospital Clinical Deterioration
Thanh-Cong Do, Hyung-Jeong Yang, Guee-Sang Lee et al. IEEE Access, 2023. Cites: paper

Subgroup State Prediction under Different Noise Levels Using MODWT and XGBoost
Xin Zhao, Xiaokai Nie. Journal of Healthcare Engineering, 2023. Cites: paper

ricu: R’s interface to intensive care data
Nicolas Bennett, Drago Plečko, Ida-Fong Ukor et al. GigaScience, 2022. Cites: paper

Entering the new digital era of intensive care medicine: an overview of interdisciplinary approaches to use artificial intelligence for patients’ benefit
Oliver Old, Benjamin Friedrichson, Kai D. Zacharowski et al. European Journal of Anaesthesiology Intensive Care, 2022. Cites: paper

Bibliography
De Gruyter eBooks, 2022. Cites: paper

Development and Validation of a Prediction Model for Need for Massive Transfusion During Surgery Using Intraoperative Hemodynamic Monitoring Data
Seung Mi Lee, Garam Lee, Tae Kyong Kim et al. JAMA Network Open, 2022. Cites: paper

Optimized Arterial Line Artifact Identification Algorithm Cleans High-Frequency Arterial Line Data With High Accuracy in Critically Ill Patients
Jasmine M. Khan, David M. Maslove, John Gordon Boyd. Critical Care Explorations, 2022. Cites: paper

Forecasting medical state transition using machine learning methods
Xiaokai Nie, Xin Zhao. Scientific Reports, 2022. Cites: paper

Multicenter validation of a deep-learning-based pediatric early-warning system for prediction of deterioration events
Yunseob Shin, Kyung-Jae Cho, Yeha Lee et al. Acute and Critical Care, 2022. Cites: paper

Style-transfer counterfactual explanations: An application to mortality prevention of ICU patients
Zhendong Wang, Isak Samsten, Vasiliki Kougia et al. Artificial Intelligence in Medicine, 2022. Cites: paper

Accelerating Time Series Analysis via Processing using Non-Volatile Memories
Ivan Fernandez, Christina Giannoula, Aditya Manglik et al. arXiv (Cornell University), 2022. Cites: paper

Self-explaining Hierarchical Model for Intraoperative Time Series
Dingwen Li, Bing Xue, Christopher King et al. Proceedings, 2022. Cites: paper

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