Machine Learning Tools for COVID-19 Patient Screening Discussed at AACC 2021
|
By HospiMedica International staff writers Posted on 29 Sep 2021 |
|
A team of researchers at the National Institute of Blood Disease (Karachi, Pakistan) have created a new machine learning tool that could help healthcare workers to quickly screen and direct the flow of COVID-19 patients arriving at hospitals. The results from an evaluation of this algorithm were presented at the 2021 AACC Annual Scientific Meeting & Clinical Lab Expo.
It is important for clinicians to quickly diagnose COVID-19 patients when they arrive at hospitals, both to triage them and to separate them from other vulnerable patients who may be immunocompromised or have pre-existing medical conditions. This can be difficult, however, because COVID-19 shares many symptoms with other viral infections, and the most accurate PCR-based tests for COVID-19 can take several days to yield results.
This led the researchers to create a machine learning algorithm to help healthcare workers efficiently screen incoming COVID-19 patients. The scientists extracted routine diagnostic and demographic data from the records of 21,672 patients presenting at hospitals and applied several statistical techniques to develop this algorithm, which is a predictive model that differentiates between COVID-19 and non-COVID-19 patients. During validation experiments, the model performed with an accuracy of up to 92.5% when tested with an independent dataset and showed a negative predictive value of up to 96.9%. The latter means that the model is particularly reliable when identifying patients who don’t have COVID-19.
“The true negative labeling efficiency of our research advocates its utility as a screening test for rapid expulsion of SARS-CoV-2 from emergency departments, aiding prompt care decisions, directing patient-case flow, and fulfilling the role of a ‘pre-test’ concerning orderly RT-PCR testing where it is not handy,” said Dr. Rana Zeeshan Haider, PhD who led the study. “We propose this test to accept the challenge of critical diagnostic needs in resource constrained settings where molecular testing is not under the flag of routine testing panels.”
Related Links:
National Institute of Blood Disease
Latest COVID-19 News
- Low-Cost System Detects SARS-CoV-2 Virus in Hospital Air Using High-Tech Bubbles
- World's First Inhalable COVID-19 Vaccine Approved in China
- COVID-19 Vaccine Patch Fights SARS-CoV-2 Variants Better than Needles
- Blood Viscosity Testing Can Predict Risk of Death in Hospitalized COVID-19 Patients
- ‘Covid Computer’ Uses AI to Detect COVID-19 from Chest CT Scans
- MRI Lung-Imaging Technique Shows Cause of Long-COVID Symptoms
- Chest CT Scans of COVID-19 Patients Could Help Distinguish Between SARS-CoV-2 Variants
- Specialized MRI Detects Lung Abnormalities in Non-Hospitalized Long COVID Patients
- AI Algorithm Identifies Hospitalized Patients at Highest Risk of Dying From COVID-19
- Sweat Sensor Detects Key Biomarkers That Provide Early Warning of COVID-19 and Flu
- Study Assesses Impact of COVID-19 on Ventilation/Perfusion Scintigraphy
- CT Imaging Study Finds Vaccination Reduces Risk of COVID-19 Associated Pulmonary Embolism
- Third Day in Hospital a ‘Tipping Point’ in Severity of COVID-19 Pneumonia
- Longer Interval Between COVID-19 Vaccines Generates Up to Nine Times as Many Antibodies
- AI Model for Monitoring COVID-19 Predicts Mortality Within First 30 Days of Admission
- AI Predicts COVID Prognosis at Near-Expert Level Based Off CT Scans
Channels
Artificial Intelligence
view channel
AI Tool Predicts Chronic Kidney Disease Risk in Diabetes
Chronic kidney disease is a common and serious complication of type 2 diabetes and often progresses without obvious early symptoms, increasing morbidity and straining health systems. Many risk models were... Read more
AI Trends Report Guides Responsible, Effective Healthcare Deployment
Hospitals are under growing pressure to adopt artificial intelligence tools that improve safety, efficiency, and continuity of care without compromising quality. At the same time, clinicians need clearer... Read more
Critical Care
view channel
AI-Guided Outreach System Improves Colorectal Cancer Screening
Colorectal cancer is the second-leading cause of cancer deaths in the United States. Early detection improves survival, yet many eligible adults remain overdue for recommended screening.... Read more
Multi-Night Home Monitoring Reduces Sleep Apnea Misdiagnosis
Obstructive sleep apnea is a common disorder in which breathing repeatedly stops and starts during sleep. Diagnosis often relies on a single-night polysomnography study, yet patients’ sleep can vary widely... Read more
FDA Breakthrough Device Targets Brain Hemorrhage Complications
Subarachnoid hemorrhage, bleeding into the space around the brain most often caused by a ruptured aneurysm, frequently leads to cerebral vasospasm during intensive care. This secondary narrowing of blood... Read more
ECG-Based Screening Framework Aims to Standardize Cardiac Evaluation in Military Personnel
Sudden cardiac death, the unexpected loss of heart function, can occur during intense exertion and remains a concern in physically demanding occupations. Military personnel face additional environmental... Read moreSurgical Techniques
view channel
Nerve Block Technique Reduces Opioid Use After Cardiac Surgery
Opioid exposure after open-heart surgery is associated with delirium, nausea, and other complications, and may contribute to longer-term dependence. Because cardiac procedures often still require high... Read more
New Bone Graft Material Targets Residual Cancer and Resists Infection
Primary bone tumors, including osteosarcoma, are aggressive malignancies that commonly affect children and young adults. Despite multimodal therapy, survival has stagnated for four decades.... Read more
Patient Care
view channel
AI Avatar Doctor Improves Patient Understanding Before Radiotherapy
Radiation oncology consultations require patients to grasp complex concepts quickly, yet anxiety and information overload often undermine understanding and informed consent. Poor comprehension can also... Read more
Wearable Sleep Data Predict Adherence to Pulmonary Rehabilitation
Chronic obstructive pulmonary disease (COPD) is a long-term lung disorder that makes breathing difficult and often disturbs sleep, reducing energy for daily activities. Limited engagement in pulmonary... Read more
Health IT
view channel
Digital Heart Model Supports Targeted Ablation in Atrial Fibrillation
Atrial fibrillation is an erratic, quivering heartbeat and a leading cause of stroke. Catheter ablation is widely used to interrupt arrhythmogenic tissue, yet many patients—especially with persistent ... Read more
AI Framework Helps Clinicians Create Trustworthy Risk Prediction Tools
Artificial intelligence (AI) is increasingly used to estimate risks for conditions such as sepsis, heart disease, and cancer, yet many models remain difficult for clinicians to interpret or trust.... Read more
Point of Care
view channel
New Brain Ultrasound Platform Enables Bedside Postoperative Imaging
Transporting postoperative patients for CT or MRI can create operational burdens, delays, and disruptions in care. Bedside visualization may help reduce transport demands, lower radiation exposure, and... Read more
Handheld Ultrasound Expands Point-of-Care Imaging Access in Brazil
Rapid access to diagnostic imaging is essential across hospitals, emergency departments, clinics, and municipal health systems, but large markets still face uneven availability, particularly in rural regions.... Read more
Business
view channel
Danaher Completes Acquisition of Masimo to Expand Patient Monitoring Capabilities
Danaher Corporation (Washington, DC, USA) has completed its acquisition of Masimo Corporation (Irvine, CA, USA), a specialty diagnostics provider known for pulse oximetry and advanced patient monitoring... Read more
