AI Tool Accurately Predicts Cancer Three Years Prior to Diagnosis
|
By HospiMedica International staff writers Posted on 24 Aug 2023 |

Over the past five decades, there has been a surge in cases of a specific type of esophageal and stomach cancer - esophageal adenocarcinoma (EAC) and gastric cardia adenocarcinoma (GCA). Both cancers have high fatality rates, although preventive measures can make a difference. Screenings can detect pre-cancerous changes, such as Barrett’s esophagus, often identified in individuals with long-standing gastroesophageal reflux disease (GERD). Although guidelines suggest screening for high-risk patients, many healthcare providers remain unfamiliar with this recommendation. Now, a new artificial intelligence (AI) tool offers accurate predictions for these forms of esophageal and stomach cancer at least three years in advance of a diagnosis.
Researchers at Michigan Medicine (Ann Arbor, MI, USA) have developed an automated tool integrated into the electronic health record (EHR). This tool has the potential to bridge the awareness gap between healthcare providers and patients with an elevated risk of developing EAC and GCA. The researchers employed a specific type of AI for analyzing data related to EAC and GCA rates across more than 10 million U.S. veterans in order to develop and validate the Kettles Esophageal and Cardia Adenocarcinoma prediction tool, or K-ECAN for short.
K-ECAN leverages readily accessible data from the EHR, including patient demographics, weight, prior diagnoses, and routine lab results, to gauge an individual's risk of developing EAC and GCA. Outperforming published guidelines and previously validated prediction tools, K-ECAN accurately predicts cancer at least three years ahead of a diagnosis. Integrating this AI tool into the EHR could automatically notify healthcare providers about patients at a higher risk of developing EAC and GCA.
“Symptoms of GERD, like heartburn, are an important risk factor for esophageal adenocarcinoma,” said Joel Rubenstein, M.D., M.S., professor of internal medicine at Michigan Medicine. “But most people with GERD symptoms will never develop esophageal adenocarcinoma and gastric cardia adenocarcinoma. In addition, roughly half of the patients with this form of cancer never experienced prior GERD symptoms at all. This makes K-ECAN particularly useful because it can identify people who are at elevated risk, regardless of whether they have GERD symptoms or not.”
Related Links:
Michigan Medicine
Latest AI News
- AI Platform Interprets Real-Time Wearable Data for Parkinson’s Management
- Algorithm Identifies Cardiac Arrest Hotspots to Guide AED Placement
- AI Analysis of Pericardial Fat Refines Long-Term Heart Disease Risk
- Machine Learning Approach Enhances Liver Cancer Risk Stratification
- New AI Approach Monitors Brain Health Using Passive Wearable Data
- AI Tool Maps Early Risk Patterns in Bloodstream Infections
- AI Model Identifies Rare Endocrine Disorder from Hand Images
- AI Tool Promises to Reduce Length of Hospital Stays and Free Up Beds
Channels
Critical Care
view channel
Synthetic Biology Approach Enables On-Demand Liver Tissue Growth
End-stage liver disease occurs when hepatic injury exceeds the organ’s normal regenerative capacity, leaving transplantation as the only option. Access to donor livers remains limited, with thousands on... Read more
Bioinspired Imaging System Identifies Cancerous Lymph Nodes Intraoperatively
Accurate identification of cancer-involved lymph nodes during surgery remains difficult, forcing trade-offs between complete tumor clearance and the risk of complications such as lymphedema.... Read moreSurgical Techniques
view channel
Fish-Skin Graft Shortens Hospital Stay in Severe Burns
Severely burned patients who require skin grafting face intensive inpatient management, where length of stay and complications such as sepsis, graft loss, venous thromboembolism, and hospital-acquired... Read more
Transcatheter Valve Replacement Demonstrates High Success in Real-World Study
Severe tricuspid regurgitation occurs when the tricuspid valve fails to close, causing backward blood flow that drives right‑sided heart failure symptoms and repeat hospitalizations in older adults.... Read morePatient Care
view channel
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
Revolutionary Automatic IV-Line Flushing Device to Enhance Infusion Care
More than 80% of in-hospital patients receive intravenous (IV) therapy. Every dose of IV medicine delivered in a small volume (<250 mL) infusion bag should be followed by subsequent flushing to ensure... Read moreHealth IT
view channel
Automated System Classifies and Tracks Cardiogenic Shock Across Hospital Settings
Cardiogenic shock remains a difficult, time-sensitive emergency, with delayed identification driving poor outcomes and persistently high mortality. Many cases go undocumented even at advanced stages, hindering... Read more
Voice-Driven AI System Enables Structured GI Procedure Documentation
Documentation during gastrointestinal (GI) procedures often competes with real-time clinical decision-making and imposes a significant cognitive burden on physicians. Manual data entry and post-procedure... Read more
EMR-Based Tool Predicts Graft Failure After Kidney Transplant
Kidney transplantation offers patients with end-stage kidney disease longer survival and better quality of life than dialysis, yet graft failure remains a major challenge. Although a successful transplant... Read more
Printable Molecule-Selective Nanoparticles Enable Mass Production of Wearable Biosensors
The future of medicine is likely to focus on the personalization of healthcare—understanding exactly what an individual requires and delivering the appropriate combination of nutrients, metabolites, and... Read morePoint of Care
view channelBusiness
view channel
Sinocare Presents AI-Driven Integrated Digital Health Solutions at CMEF
At the 93rd China International Medical Equipment Fair (CMEF), Sinocare presented a comprehensive portfolio of digital health technologies designed to support integrated chronic disease management across... Read more







