ArticleComputers in biology and medicine2022
Detection of COVID-19 severity using blood gas analysis parameters and Harris hawks optimized extreme learning machine.
Article in Computers in biology and medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 97 citations in OpenAlex.
- Deep Learning-Based Lung Cancer Segmentation and Volumetric Analysis Using CT Imaging: A Comprehensive Survey.Annals of biomedical engineering · 2026Review
- [Research progress in artificial intelligence for the diagnosis and management of diseases in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Review
- A prediction model for microseismic signals based on kernel extreme learning machine optimized by Harris Hawks algorithm.Scientific reports · 2025Article
- An enhancing diagnostic pulmonary diseases diagnostic method for differentiating talaromycosis from tuberculosis.iScience · 2025Article
- An enhanced machine learning-based prognostic prediction model for patients with AECOPD on invasive mechanical ventilation.iScience · 2024Article
- Diagnosis of Lung Cancer Through Exhaled Breath: A Comprehensive Study.Molecular diagnosis & therapy · 2024Article
- Article
- Towards Improved XAI-Based Epidemiological Research into the Next Potential Pandemic.Life (Basel, Switzerland) · 2024Review
- Exploratory analysis of serum Krebs von den Lungen-6, blood gas analysis & Brixia score in determining COVID-19 severity & mortality.The Indian journal of medical research · 2024Article
- An Enhanced RIME Optimizer with Horizontal and Vertical Crossover for Discriminating Microseismic and Blasting Signals in Deep Mines.Sensors (Basel, Switzerland) · 2023Article
- RNAenrich: a web server for non-coding RNA enrichment.Bioinformatics (Oxford, England) · 2023Article
- A Survey of COVID-19 Diagnosis Using Routine Blood Tests with the Aid of Artificial Intelligence Techniques.Diagnostics (Basel, Switzerland) · 2023Review
- Crisscross Harris Hawks Optimizer for Global Tasks and Feature Selection.Journal of bionic engineering · 2023Article
- An enhanced decision-making framework for predicting future trends of sharing economy.PloS one · 2023Article
- Predictive models for COVID-19 detection using routine blood tests and machine learning.Heliyon · 2022Review
- Smart ECG Biosensor Design with an Improved ANN Performance Based on the Taguchi Optimizer.Bioengineering (Basel, Switzerland) · 2022Article
- Multilevel threshold image segmentation for COVID-19 chest radiography: A framework using horizontal and vertical multiverse optimization.Computers in biology and medicine · 2022Article
- An Improved Machine-Learning Approach for COVID-19 Prediction Using Harris Hawks Optimization and Feature Analysis Using SHAP.Diagnostics (Basel, Switzerland) · 2022Article
- An Ensemble Learning Model for COVID-19 Detection from Blood Test Samples.Sensors (Basel, Switzerland) · 2022Article
- Multiclass feature selection with metaheuristic optimization algorithms: a review.Neural computing & applications · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coronavirus disease-2019 (COVID-19) has made the world more cautious about widespread viruses, and a tragic pandemic that was caused by a novel coronavirus has harmed human beings in recent years. The new coronavirus pneumonia outbreak is spreading rapidly worldwide. We collect arterial blood samples from 51 patients with a COVID-19 diagnosis. Blood gas analysis is performed using a Siemens RAPID Point 500 blood gas analyzer. To accurately determine the factors that play a decisive role in the early recognition and discrimination of COVID-19 severity, a prediction framework that is based on an improved binary Harris hawk optimization (HHO) algorithm in combination with a kernel extreme learning machine is proposed in this paper. This method uses specular reflection learning to improve the original HHO algorithm and is referred to as HHOSRL. The experimental results show that the selected indicators, such as age, partial pressure of oxygen, oxygen saturation, sodium ion concentration, and lactic acid, are essential for the early accurate assessment of COVID-19 severity by the proposed feature selection method. The simulation results show that the established methodlogy can achieve promising performance. We believe that our proposed model provides an effective strategy for accurate early assessment of COVID-19 and distinguishing disease severity. The codes of HHO will be updated in https://aliasgharheidari.com/HHO.html.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.