Clinical decision support system and hospital readmission reduction: Evidence from US panel data
Using a large-scale panel of US hospitals across health referral regions (HRRs), we
empirically examine how a hospital's and its neighboring hospitals' adoption of the Clinical …
empirically examine how a hospital's and its neighboring hospitals' adoption of the Clinical …
Early prediction of high-cost inpatients with ischemic heart disease using network analytics and machine learning
P Yang, H Qiu, L Wang, L Zhou - Expert Systems with Applications, 2022 - Elsevier
Although identifying high-cost inpatients with ischemic heart disease (IHD) at the point of
admission is helpful for timely intervention and reducing costs, it is a difficult task due to the …
admission is helpful for timely intervention and reducing costs, it is a difficult task due to the …
A collaborative decision support system for multi-criteria automatic clustering
Automatic clustering is a challenging problem, especially when the decision-maker has little
or no information about the nature of the dataset and the criteria of interest. There is a lack of …
or no information about the nature of the dataset and the criteria of interest. There is a lack of …
Disease Network-Based Approaches to Study Comorbidity in Heart Failure: Current State and Future Perspectives
SA Gomez-Ochoa, JD Lanzer, RT Levinson - Current Heart Failure …, 2025 - Springer
Network approaches hold promise for unraveling the impact of comorbidities in the complex
presentation and genetics of HF. Methods that consider comorbidity presence and timing …
presentation and genetics of HF. Methods that consider comorbidity presence and timing …
Multimorbidity prediction using link prediction
Multimorbidity, frequently associated with aging, can be operationally defined as the
presence of two or more chronic conditions. Predicting the likelihood of a patient with …
presence of two or more chronic conditions. Predicting the likelihood of a patient with …
On atomic cliques in temporal graphs
Atomic cliques were introduced recently to analyze disease progression in temporal
comorbidity graphs. Informally, an atomic clique is a clique that is unsplittable over time—the …
comorbidity graphs. Informally, an atomic clique is a clique that is unsplittable over time—the …
Designing conversational dashboards for effective use in crisis response
Governments and health organizations are increasingly using dashboards to provide real-
time information during natural disasters and pandemics. Although these dashboards aim to …
time information during natural disasters and pandemics. Although these dashboards aim to …
What can we learn from multimorbidity? A deep dive from its risk patterns to the corresponding patient profiles
Multimorbidity, the presence of two or more chronic conditions within an individual,
represents one of the most intricate challenges for global health systems. Traditional single …
represents one of the most intricate challenges for global health systems. Traditional single …
A prediction method of diabetes comorbidity based on non-negative latent features
L Zhou, K Liu, Y Wang, H Qin, T He - Neurocomputing, 2024 - Elsevier
In this paper, we present a novel network-based approach, namely Inherently Non-negative
Latent Feature Analysis for Diabetes Mellitus Comorbidity Detection (INDM), to enhance the …
Latent Feature Analysis for Diabetes Mellitus Comorbidity Detection (INDM), to enhance the …
Estimating pandemic effects in urban mass transportation systems: An approach based on visibility graphs and network similarity
Y Perez, FH Pereira - Physica A: Statistical Mechanics and its Applications, 2023 - Elsevier
The COVID-19 pandemic has caused unprecedented disruptions to urban systems
worldwide, but the extent and nature of these disruptions are not yet fully understood when it …
worldwide, but the extent and nature of these disruptions are not yet fully understood when it …