We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
ARAB HEALTH - INFORMA

Download Mobile App




AI Algorithm Detects Early-Stage Metabolic-Associated Steatotic Liver Disease Using EHRs

By HospiMedica International staff writers
Posted on 25 Nov 2024
Print article
Image: AI can find undiagnosed liver disease in early stages (Photo courtesy of 123RF)
Image: AI can find undiagnosed liver disease in early stages (Photo courtesy of 123RF)

Liver disease, which is treatable when detected early, often goes unnoticed until it reaches advanced stages. Metabolic-associated steatotic liver disease (MASLD), the most prevalent form of liver disease, occurs when the liver is unable to properly manage fat, and it is commonly linked to conditions like obesity, Type-2 diabetes, and high cholesterol. Early detection of MASLD is crucial because it can rapidly progress to more severe liver conditions, but many individuals in the early stages show no symptoms, making diagnosis difficult. Now, a new study has demonstrated that an artificial intelligence (AI)-powered algorithm can accurately identify early-stage MASLD by analyzing electronic health records (EHRs).

Researchers at the University of Washington (Seattle, WA, USA) employed an AI algorithm to examine imaging data within EHRs from three sites in the University of Washington Medical System to identify patients who met the criteria for MASLD. Of the 834 patients identified, only 137 had a formal MASLD diagnosis recorded. This means that 83% of patients who met the criteria for MASLD were undiagnosed, despite the data in their EHRs indicating they were at risk.

“A significant proportion of patients who meet criteria for MASLD go undiagnosed. This is concerning because delays in early diagnosis increase the likelihood of progression to advanced liver disease,” said Ariana Stuart MD, a resident at University of Washington Internal Medicine Residency Program and lead author of the study. “People should not interpret our findings as a lack of primary care training or management. Instead, our study shows how AI can complement physician workflow to address the limitations of traditional clinical practice.”

New
Gold Member
X-Ray QA Meter
T3 AD Pro
Gold Member
12-Channel ECG
CM1200B
New
Blanket Warming Cabinet
EC250
New
Transducer Covers
Surgi Intraoperative Covers

Print article

Channels

Critical Care

view channel
Image: Changes in immune cells can predict patient recovery following out-of-hospital cardiac arrest (Photo courtesy of Adobe Stock)

Activating T Cells Could Improve Neurological Outcomes After Cardiac Arrest

Despite advancements in cardiopulmonary resuscitation (CPR) and improved hospital access, survival rates after out-of-hospital cardiac arrest (OHCA) remain low, with only about 10% of patients surviving.... Read more

Surgical Techniques

view channel
Image: (Left) An image of a 3D-printed material implanted in vivo for 4 weeks. (Right) A photo of coral (Photo courtesy of Dr Zhidao Xia and Jesus Cobaleda)

Revolutionary Coral-Inspired Material for Bone Repair Promotes Faster Healing

Bone defects caused by fractures, tumors, and non-healing injuries are major contributors to disability worldwide. Traditionally, doctors have used either a patient’s own bone (autograft) or donor bone... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more

Health IT

view channel
Image: First ever institution-specific model provides significant performance advantage over current population-derived models (Photo courtesy of Mount Sinai)

Machine Learning Model Improves Mortality Risk Prediction for Cardiac Surgery Patients

Machine learning algorithms have been deployed to create predictive models in various medical fields, with some demonstrating improved outcomes compared to their standard-of-care counterparts.... Read more

Point of Care

view channel
Image: The acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.