[HTML][HTML] Predicting patient deterioration: a review of tools in the digital hospital setting

KD Mann, NM Good, F Fatehi, S Khanna… - Journal of medical …, 2021 - jmir.org
Background Early warning tools identify patients at risk of deterioration in hospitals.
Electronic medical records in hospitals offer real-time data and the opportunity to automate …

[HTML][HTML] Prediction of respiratory decompensation in Covid-19 patients using machine learning: The READY trial

H Burdick, C Lam, S Mataraso, A Siefkas… - Computers in biology …, 2020 - Elsevier
Background Currently, physicians are limited in their ability to provide an accurate prognosis
for COVID-19 positive patients. Existing scoring systems have been ineffective for identifying …

[HTML][HTML] Evaluation of machine learning-based models for prediction of clinical deterioration: A systematic literature review

S Jahandideh, G Ozavci, BW Sahle, AZ Kouzani… - International Journal of …, 2023 - Elsevier
Background and objective Early identification of patients at risk of deterioration can prevent
life-threatening adverse events and shorten length of stay. Although there are numerous …

[HTML][HTML] Mortality prediction model for the triage of COVID-19, pneumonia, and mechanically ventilated ICU patients: A retrospective study

L Ryan, C Lam, S Mataraso, A Allen… - Annals of Medicine and …, 2020 - Elsevier
Rationale Prediction of patients at risk for mortality can help triage patients and assist in
resource allocation. Objectives Develop and evaluate a machine learning-based algorithm …

[HTML][HTML] A racially unbiased, machine learning approach to prediction of mortality: algorithm development study

A Allen, S Mataraso, A Siefkas… - JMIR public health …, 2020 - publichealth.jmir.org
Background: Racial disparities in health care are well documented in the United States. As
machine learning methods become more common in health care settings, it is important to …

Machine Learning Approach for Improved Longitudinal Prediction of Progression from Mild Cognitive Impairment to Alzheimer's Disease

RP Adelson, A Garikipati, J Maharjan, M Ciobanu… - Diagnostics, 2023 - mdpi.com
Mild cognitive impairment (MCI) is cognitive decline that can indicate future risk of
Alzheimer's disease (AD). We developed and validated a machine learning algorithm (MLA) …

Combining machine learning and conventional statistical approaches for risk factor discovery in a large cohort study

I Madakkatel, A Zhou, MD McDonnell, E Hyppönen - Scientific reports, 2021 - nature.com
We present a simple and efficient hypothesis-free machine learning pipeline for risk factor
discovery that accounts for non-linearity and interaction in large biomedical databases with …

[HTML][HTML] Electronic cigarette–related contents on Instagram: observational study and exploratory analysis

Y Gao, Z Xie, L Sun, C Xu, D Li - JMIR Public Health and …, 2020 - publichealth.jmir.org
Background: Instagram is a popular social networking platform for users to upload pictures
sharing their experiences. Instagram has been widely used by vaping companies and stores …

Development and structure of an accurate machine learning algorithm to predict inpatient mortality and hospice outcomes in the coronavirus disease 2019 era

S Chi, A Guo, K Heard, S Kim, R Foraker, P White… - Medical care, 2022 - journals.lww.com
Background: The coronavirus disease 2019 (COVID-19) pandemic has challenged the
accuracy and racial biases present in traditional mortality scores. An accurate prognostic …

Dynamic mortality risk predictions for children in ICUs: development and validation of machine learning models

EAT Rivera, JM Chamberlain, AK Patel… - Pediatric Critical Care …, 2022 - journals.lww.com
OBJECTIVES: Assess a machine learning method of serially updated mortality risk. DESIGN:
Retrospective analysis of a national database (Health Facts; Cerner Corporation, Kansas …