AI-Driven Tools for Coronavirus Outbreak: Need of Active Learning and Cross-Population Train/Test Models on Multitudinal/Multimodal Data
Open accessAbstract
The novel coronavirus (COVID-19) outbreak, which was identified in late 2019, requires special attention because of its future epidemics and possible global threats. Beside clinical procedures and treatments, since Artificial Intelligence (AI) promises a new paradigm for healthcare, several different AI tools that are built upon Machine Learning (ML) algorithms are employed for analyzing data and decision-making processes. This means that AI-driven tools help identify COVID-19 outbreaks as well as forecast their nature of spread across the globe. However, unlike other healthcare issues, for COVID-19, to detect COVID-19, AI-driven tools are expected to have active learning-based cross-population train/test models that employs multitudinal and multimodal data, which is the primary purpose of the paper.
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The combination of multimodal data can predict and screen for COVID-19 more accurately.
“The latest literature indicates that the combination of multimodal data can predict and screen for this virus more accurately [106, 145].”
From A survey on deep multimodal learning for computer vision: advances, trends, applications, and datasets (2022) · cites this paper as [106]
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- Authors
- Santosh, K. C.
- Affiliations
- University of South Dakota (US)
- Corresponding author
- Santosh, K. C.
- ORCID
- Santosh, K. C.
- Venue
- Journal of Medical Systems
- Published
- 2020-03-18
- Volume
- 44
- Issue
- 5
- Pages
- 93-93
- ISSN
- 0148-5598 (ISSN-L)
- 1573-689X
- PMC
- PMC7087612
- OpenAlex
- W3011716991
- Cited by
- 341
- References
- 21
- Citations by year
- 2026: 8 · 2025: 12 · 2024: 17 · 2023: 51 · 2022: 51 · 2021: 104 · 2020: 98
- FWCI
- 36.82
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Journal of Medical Systems (publishedVersion)
- Europe PMC (PubMed Central) (publishedVersion)
- PubMed Central (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › COVID-19 diagnosis using AI
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Health Sciences › Medicine › Infectious Diseases › SARS-CoV-2 detection and testing
- Keywords
- COVID-19 pandemic, outbreak detection, epidemic forecasting, active learning (machine learning), multimodal data
- MeSH terms
- Machine Learning, COVID-19, Algorithms, Artificial Intelligence, Decision Making, Delivery of Health Care, Disease Outbreaks, Forecasting, Humans, Pneumonia, Viral, Coronavirus Infections
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