Evaluating the state of the art in missing data imputation for clinical data

Y Luo - Briefings in Bioinformatics, 2022 - academic.oup.com
Clinical data are increasingly being mined to derive new medical knowledge with a goal of
enabling greater diagnostic precision, better-personalized therapeutic regimens, improved …

Data pre-processing using neural processes for modeling personalized vital-sign time-series data

P Sharma, FE Shamout, V Abrol… - IEEE Journal of …, 2021 - ieeexplore.ieee.org
Clinical time-series data retrieved from electronic medical records are widely used to build
predictive models of adverse events to support resource management. Such data is often …

Mortality prediction using medical time series on TBI patients

J Fonseca, X Liu, HP Oliveira, T Pereira - Computer methods and programs …, 2023 - Elsevier
Abstract Background and objective Traumatic Brain Injury (TBI) is one of the leading causes
of injury-related mortality in the world, with severe cases reaching mortality rates of 30-40 …

An Enhanced Imputation Approach for Spatio-Temporal Clinical Data

Y Yin, CA Chou - 2022 IEEE 18th International Conference on …, 2022 - ieeexplore.ieee.org
Recently, clinical decision making processes largely benefit from electronic health records
(EHR) to improve the diagnosis outcomes and quality of patient care. In particular, patients' …

Data-Driven Modeling and Learning Approach to Solving ICU Risk Prediction and Survival Analysis

Y Yin - 2022 - search.proquest.com
Intensive care unit (ICU) is an expensive and limited resource in hospitals, which majorly
maintains the survival of critical life-threatened patients. Accordingly, the short-term mortality …

[PDF][PDF] DEVELOPMENT OF ARTIFICIAL INTELLIGENCE ALGORITHMS FOR EARLY DIAGNOSIS OF SEPSIS

FDEANT MANOEL - 2021 - run.unl.pt
Sepsis is a prevalent syndrome that manifests itself through an uncontrolled response from
the body to an infection, that may lead to organ dysfunction. Its diagnosis is urgent since …