Machine Learning Tools for Acute Respiratory Distress Syndrome Detection and Prediction

F Rubulotta, S Bahrami, DC Marshall… - Critical Care …, 2024 - journals.lww.com
Abstract Machine learning (ML) tools for acute respiratory distress syndrome (ARDS)
detection and prediction are increasingly used. Therefore, understanding risks and benefits …

Trash in/trash out? Using routinely collected clinical data for data science in the ICU: Con

B Pörteners, C Jung, G Meyfroidt - Intensive Care Medicine, 2024 - Springer
The availability of large amounts of electronic data in the Intensive Care Unit (ICU) has
enabled the creation of large open or semi-open access data repositories. Using these …

Implicit bias in Critical Care Data: Factors affecting sampling frequencies and missingness patterns of clinical and biological variables in ICU Patients

J Shi, A Hubbard, N Fong, R Pirracchio - medRxiv, 2024 - medrxiv.org
The presence of missing values in Electronic Health Records (EHRs) is a widespread and
inescapable issue. Publicly available data sets mirror the incompleteness found in EHRs …

Public Datasets: A Foundation to Artificial Intelligence in Health Care

S Ferguson, PM Tille - American Society for Clinical Laboratory …, 2024 - clsjournal.ascls.org
The use of artificial intelligence (AI) in health care is predicated on its safety and efficacy. AI
is a technical field of study and is fast evolving. It will affect everyone, so it is important that …

Implicit Bias in ICU Electronic Health Record Data Measurement Frequencies and Missingness Rates of Clinical Variables

JS Shi, AE Hubbard, N Fong, R Pirracchio - 2024 - researchsquare.com
Background: Disparities in data collection within electronic health records (EHRs),
especially in Intensive Care Units (ICUs), can reveal underlying biases that may affect …