Prognostic models in COVID-19 infection that predict severity: a systematic review
Current evidence on COVID-19 prognostic models is inconsistent and clinical applicability
remains controversial. We performed a systematic review to summarize and critically …
remains controversial. We performed a systematic review to summarize and critically …
Transformative potential of AI in Healthcare: definitions, applications, and navigating the ethical Landscape and Public perspectives
Artificial intelligence (AI) has emerged as a crucial tool in healthcare with the primary aim of
improving patient outcomes and optimizing healthcare delivery. By harnessing machine …
improving patient outcomes and optimizing healthcare delivery. By harnessing machine …
A GPT-based EHR modeling system for unsupervised novel disease detection
Abstract Objective To develop an Artificial Intelligence (AI)-based anomaly detection model
as a complement of an “astute physician” in detecting novel disease cases in a hospital and …
as a complement of an “astute physician” in detecting novel disease cases in a hospital and …
Deep learning in public health: Comparative predictive models for COVID-19 case forecasting
The COVID-19 pandemic has had a significant impact on both the United Arab Emirates
(UAE) and Malaysia, emphasizing the importance of develo** accurate and reliable …
(UAE) and Malaysia, emphasizing the importance of develo** accurate and reliable …
Sociodemographic bias in clinical machine learning models: a sco** review of algorithmic bias instances and mechanisms
M Colacci, YQ Huang, G Postill, P Zhelnov… - Journal of Clinical …, 2024 - Elsevier
Background Clinical machine learning (ML) technologies can sometimes be biased and
their use could exacerbate health disparities. The extent to which bias is present, the groups …
their use could exacerbate health disparities. The extent to which bias is present, the groups …
In-hospital real-time prediction of COVID-19 severity regardless of disease phase using electronic health records
H Park, CM Choi, SH Kim, SH Kim, DK Kim, JB Jeong - Plos one, 2024 - journals.plos.org
Coronavirus disease 2019 (COVID-19) has strained healthcare systems worldwide.
Predicting COVID-19 severity could optimize resource allocation, like oxygen devices and …
Predicting COVID-19 severity could optimize resource allocation, like oxygen devices and …
Artificial intelligence in triage of COVID-19 patients
Y Oliveira, I Rios, P Araújo, A Macambira… - Frontiers in Artificial …, 2024 - frontiersin.org
In 2019, COVID-19 began one of the greatest public health challenges in history, reaching
pandemic status the following year. Systems capable of predicting individuals at higher risk …
pandemic status the following year. Systems capable of predicting individuals at higher risk …
Racial Differences in Accuracy of Predictive Models for High-Flow Nasal Cannula Failure in COVID-19
OBJECTIVES: To develop and validate machine learning (ML) models to predict high-flow
nasal cannula (HFNC) failure in COVID-19, compare their performance to the respiratory …
nasal cannula (HFNC) failure in COVID-19, compare their performance to the respiratory …
Social determinants of health and the prediction of missed breast imaging appointments
Background Predictive models utilizing social determinants of health (SDH), demographic
data, and local weather data were trained to predict missed imaging appointments (MIA) …
data, and local weather data were trained to predict missed imaging appointments (MIA) …
ITNR: Inversion Transformer-based Neural Ranking for cancer drug recommendations
Personalized drug response prediction is an approach for tailoring effective therapeutic
strategies for patients based on their tumors' genomic characterization. While machine …
strategies for patients based on their tumors' genomic characterization. While machine …