Feature selection: Multi-source and multi-view data limitations, capabilities and potentials

M Cherrington, J Lu, D Airehrour… - 2019 29th …, 2019 - ieeexplore.ieee.org
Feature Selection (FS) is a crucial step in high-dimensional and big data analytics. It
mitigates thecurse of dimensionality'by removing redundant and irrelevant features. Most FS …

[HTML][HTML] The extent and coverage of current knowledge of connected health: Systematic mapping study

M Karampela, M Isomursu, T Porat, C Maramis… - Journal of medical …, 2019 - jmir.org
Background This study examines the development of the connected health (CH) research
landscape with a view to providing an overview of the existing CH research. The research …

Integrating co-clustering and interpretable machine learning for the prediction of intravenous immunoglobulin resistance in kawasaki disease

H Wang, Z Huang, D Zhang, J Arief, T Lyu, J Tian - Ieee Access, 2020 - ieeexplore.ieee.org
Identifying intravenous immunoglobulin-resistant patients is essential for the prompt and
optimal treatment of Kawasaki disease, suggesting the need for effective risk assessment …

Challenges associated with missing data in electronic health records: a case study of a risk prediction model for diabetes using data from Slovenian primary care

G Stiglic, P Kocbek, N Fijacko… - Health informatics …, 2019 - journals.sagepub.com
The increasing availability of data stored in electronic health records brings substantial
opportunities for advancing patient care and population health. This is, however …

An overview of Business Intelligence research in healthcare organizations using a topic modeling approach

M Mehraeen, L Mahmoudi… - 2023 13th International …, 2023 - ieeexplore.ieee.org
The intersection of Business intelligence (BI) and data analytics with healthcare has
witnessed remarkable growth in recent decades. With the aim of identifying the most …

A Reduced Modeling Approach for Making Predictions with Incomplete Data Having Blockwise Missing Patterns

K Srinivasan, F Currim, S Ram - INFORMS Journal on Data …, 2024 - pubsonline.informs.org
Incomplete data with blockwise missing patterns are commonly encountered in analytics,
and solutions typically entail listwise deletion or imputation. However, as the proportion of …

A Hybrid Approach of Feature Selection and K-Nearest Neighbor for Handling Healthcare Prospective Missing Data

R Alkhawaldeh - 2023 - search.proquest.com
The electronic health record system generates an enormous amount of data that can be
utilized in healthcare predictive analytics. Although there has been a steady increase in the …

A regularization approach for identifying cumulative lagged effects in smart health applications

K Srinivasan, F Currim, S Ram, MR Mehl… - Proceedings of the …, 2017 - dl.acm.org
Recent development of wearable sensor technologies have made it possible to capture
concurrent data streams for ambient environment and instantaneous physiological stress …

Indoor environmental effects on individual wellbeing

K Srinivasan, S Ram - Proceedings of the 6th International Conference …, 2016 - dl.acm.org
A growing literature demonstrates the impact of the built environment on human health and
wellbeing. A wide range of factors such as daylight exposure, ambient noise and air quality …

Feature and case importance and confidence for imputation in computer-based reasoning systems

CJ Hazard, M Resnick - US Patent 10,845,769, 2020 - Google Patents
Techniques are provided for imputation in computer-based reasoning systems. The
techniques include performing the following until there are no more cases in a computer …