Machine Learning Tool Predicts Forms of Esophageal and Stomach … – Inside Precision Medicine
A new artificial intelligence tool predicts esophageal adenocarcinoma (EAC) and gastric cardia adenocarcinoma (GCA), a form of stomach cancer, at least three years prior to a diagnosis. Both cancers are highly fatal, and rates have risen sharply over the past five decades.
Researchers from the Lieutenant Colonel Charles S. Kettles Veterans Affairs Center for Clinical Management Research developed the machine learning model from the electronic medical records of 10 million US veterans. VA records are unique in that they are automatically linked to cancer registry outcomes allowing the researchers to look backwards in veterans health records for information that could be used to predict cancer. Their analysis included previous diagnoses, laboratory value results, weight, prescription history, and more.
We were able to identify individuals who developed adenocarcinoma of the esophagus or esophageal junction and used a form of machine learning to learn more about them, explains Joel Rubenstein, MD, a research scientist at theKettles VA Center and professor of internal medicine at Michigan Medicine, who named the model the Kettles Esophageal and Cardia Adenocarcinoma predictioN tool, or K-ECAN.
The team accessed the Veterans Health Administration (VHA) Corporate Data Warehouse to identify veterans diagnosed with EAC (8,430) or GCA (2,965) over a 13-year period and compared them to 10,256,887 controls. The cancer cohort was split in half. One half was used to develop the K-ECAN model for predicting cancer, another quarter was used to tune the model, with the final quarter validating the results. We found that the model predicts which individuals would develop these cancers at least three years before they did, Rubenstein says. The model was more accurate than published guidelines in predicting cancer and more accurate than other tools that are already available that have been previously validated. Their findings werepublished in Gastroenterology.
The greatest identified risk factor was age, but others were found to be associated with increased cancer risk including Barretts esophagus, a precancerous condition, and gastroesophageal reflux disease (GERD). However, the model revealed other somewhat unexpected factors including slightly elevated hematocrit, low HDL/elevated LDL, lower blood serum bicarbonate levels, and greater white blood cell counts.
All of the screening guidelines for esophageal cancer now rely on GERD symptomsheartburn and refluxto identify people who should get screening, says Rubenstein. And while GERD is associated with the cancer, it wasnt particularly important in terms of the amount of information provided to the model. 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, adds Rubenstein.
While current guidelines already consider screening in high-risk patients, Rubenstein notes that many providers are still unfamiliar with this recommendation and that fewer than 20% of people who have developed the cancer have had prior screening.
We envision this tool being integrated seamlessly in the electronic health record to notify providers of their patients elevated risk, Rubenstein explains. Providers would receive automated notification alerts regarding which patients are at an increased risk of developing ECA and GCA. They could then consider screening when an individual is due for a colonoscopy or when refilling acid-reducing medication as colonoscopy and upper endoscopy can be performed at the same time.
Currently, Rubensteins team is piloting the tool at the Kettles VA facility.
Read this article:
Machine Learning Tool Predicts Forms of Esophageal and Stomach ... - Inside Precision Medicine
- Wearable sensors and machine learning give leg up on better running data - Medical Xpress - October 23rd, 2025 [October 23rd, 2025]
- Geophysical-machine learning tool developed for continuous subsurface geomaterials characterization - Phys.org - October 23rd, 2025 [October 23rd, 2025]
- Ohio wins national cybersecurity award for fraud solutions using machine learning - Spectrum News 1 - October 23rd, 2025 [October 23rd, 2025]
- Machine learning predictions of climate change effects on nearly threatened bird species ( Crithagra xantholaema) habitat in Ethiopia for conservation... - October 23rd, 2025 [October 23rd, 2025]
- A machine learning tool for predicting newly diagnosed osteoporosis in primary healthcare in the Stockholm Region - Nature - October 23rd, 2025 [October 23rd, 2025]
- ECBs New Perspective on Machine Learning in Banking - KPMG - October 23rd, 2025 [October 23rd, 2025]
- Ensemble Machine Learning for Digital Mapping of Soil pH and Electrical Conductivity in the Andean Agroecosystem of Peru - Frontiers - October 21st, 2025 [October 21st, 2025]
- New UA research develops machine learning to address needs of children with autism - AZPM News - October 21st, 2025 [October 21st, 2025]
- NMDSI Speaker Series on Weather Forecasting: What Machine Learning Can and Can't Do, Oct. 23 - Marquette Today - October 21st, 2025 [October 21st, 2025]
- Polyskill Achieves 1.7x Improved Skill Reuse and 9.4% Higher Success Rates through Polymorphic Abstraction in Machine Learning - Quantum Zeitgeist - October 21st, 2025 [October 21st, 2025]
- University of Strathclyde opens admission for MSc in Machine & Deep Learning for Jan 2026 intake - The Indian Express - October 21st, 2025 [October 21st, 2025]
- Reducing Model Biases with Machine Learning Corrections Derived from Ocean Data Assimilation Increments - ESS Open Archive - October 19th, 2025 [October 19th, 2025]
- Unlocking Obesity: Multi-Omics and Machine Learning Insights - Bioengineer.org - October 19th, 2025 [October 19th, 2025]
- Lockheed Martin advances PAC-3 MSE interceptor using artificial intelligence and machine learning - Defence Industry Europe - October 19th, 2025 [October 19th, 2025]
- Semi-automated surveillance of surgical site infections using machine learning and rule-based classification models - Nature - October 19th, 2025 [October 19th, 2025]
- AI and Machine Learning - City of San Jos to release RFP for generative AI platform - Smart Cities World - October 19th, 2025 [October 19th, 2025]
- Machine learning helps identify 'thermal switch' for next-generation nanomaterials - Phys.org - October 17th, 2025 [October 17th, 2025]
- Machine Learning Makes Wildlife Data Analysis Less of a Trek - Maryland.gov - October 17th, 2025 [October 17th, 2025]
- An interpretable multimodal machine learning model for predicting malignancy of thyroid nodules in low-resource scenarios - BMC Endocrine Disorders - October 17th, 2025 [October 17th, 2025]
- In First-Episode Psychosis Patients, Machine Learning Predicted Illness Trajectories to Potentially Improve Outcomes - Brain and Behavior Research - October 17th, 2025 [October 17th, 2025]
- Novel Machine Learning Model Improves MASLD Detection in Type 2 Diabetes - The American Journal of Managed Care (AJMC) - October 17th, 2025 [October 17th, 2025]
- Hybrid machine learning models for predicting the tensile strength of reinforced concrete incorporating nano-engineered and sustainable supplementary... - October 17th, 2025 [October 17th, 2025]
- Modelling of immune infiltration in prostate cancer treated with HDR-brachytherapy using Raman spectroscopy and machine learning - Nature - October 17th, 2025 [October 17th, 2025]
- Association between atherogenic index of plasma and sepsis in critically ill patients with ischemic stroke: a retrospective cohort study using... - October 17th, 2025 [October 17th, 2025]
- AI enters the nuclear age: Pentagon modernizes warheads with machine learning - Washington Times - October 17th, 2025 [October 17th, 2025]
- AI and Machine Learning - Bentley Systems shares its vision for trustworthy AI - Smart Cities World - October 17th, 2025 [October 17th, 2025]
- Looking back to move forward: can historical clinical trial data and machine learning drive change in participant recruitment in anticipation of... - October 15th, 2025 [October 15th, 2025]
- Physics-Based Machine Learning Paves the Way for Advanced 3D-Printed Materials - Bioengineer.org - October 15th, 2025 [October 15th, 2025]
- Predicting one-year overall survival in patients with AITL using machine learning algorithms: a multicenter study - Nature - October 15th, 2025 [October 15th, 2025]
- Explainable machine learning models for predicting of protein-energy wasting in patients on maintenance haemodialysis - BMC Nephrology - October 15th, 2025 [October 15th, 2025]
- Feasibility of machine learning analysis for the identification of patients with possible primary ciliary dyskinesia - Orphanet Journal of Rare... - October 15th, 2025 [October 15th, 2025]
- Machine learning-based prediction of preeclampsia using first-trimester inflammatory markers and red blood cell indices - BMC Pregnancy and Childbirth - October 15th, 2025 [October 15th, 2025]
- Utilizing AI and machine learning to improve railroad safety: Detecting trespasser hotspots - masstransitmag.com - October 15th, 2025 [October 15th, 2025]
- Precision medicine meets machine learning: AI and oncology biomarkers - pharmaphorum - October 15th, 2025 [October 15th, 2025]
- Aether Pro Exchange Transforms Execution Dynamics with Machine-Learning Optimization - GlobeNewswire - October 15th, 2025 [October 15th, 2025]
- Prevalence, associated factors, and machine learning-based prediction of depression, anxiety, and stress among university students: a cross-sectional... - October 15th, 2025 [October 15th, 2025]
- Artificial Intelligence vs. Machine Learning: Which skills will open better career options in the global - Times of India - October 15th, 2025 [October 15th, 2025]
- Study Reveals Impact of Negative Class Definitions on Machine Learning Accuracy in Immunotherapy - geneonline.com - October 15th, 2025 [October 15th, 2025]
- Muna Al-Khaifi: Detection of Breast Cancer Using Machine Learning and Explainable AI - Oncodaily - October 13th, 2025 [October 13th, 2025]
- Expedia Group Unveils Innovative AI and Machine Learning Solutions to Transform Partner Travel Experiences - Travel And Tour World - October 13th, 2025 [October 13th, 2025]
- Machine Learning-Guided Prediction of Formulation Performance in Inhalable CiprofloxacinBile Acid Dispersions with Antimicrobial and Toxicity... - October 13th, 2025 [October 13th, 2025]
- Machine Learning and BIG DATA workshop planned Oct. 14-15 - West Virginia University - October 11th, 2025 [October 11th, 2025]
- How Google enables third-party circularity by increasing recycling rates with Machine Learning - The World Business Council for Sustainable... - October 11th, 2025 [October 11th, 2025]
- Integrating Artificial Intelligence and Machine Learning in Hydroclimatic Research - A Promising Step Forward - University of Northern British... - October 11th, 2025 [October 11th, 2025]
- Semi-automatic detection of anteriorly displaced temporomandibular joint discs in magnetic resonance images using machine learning - BMC Oral Health - October 11th, 2025 [October 11th, 2025]
- AI and Machine Learning - Partnership to bring infrastructure intelligence to US public sector - Smart Cities World - October 11th, 2025 [October 11th, 2025]
- Between rain and snow, machine learning finds nine precipitation types - Phys.org - October 9th, 2025 [October 9th, 2025]
- Between rain and snow, machine learning finds 9 precipitation types - Michigan Engineering News - October 9th, 2025 [October 9th, 2025]
- Machine learning optimizes nanoparticle design for drug delivery to the brain - Physics World - October 9th, 2025 [October 9th, 2025]
- Development and validation of a machine learning-based prediction model for prolonged length of stay after laparoscopic gastrointestinal surgery: a... - October 9th, 2025 [October 9th, 2025]
- G Sachs: Stock Mkt Not in Bubble Yet; Machine Learning/ AI Expected to Spawn New Wave of Superstars - AASTOCKS.com - October 9th, 2025 [October 9th, 2025]
- AI and Machine Learning - See.Sense works with City of Sydney to develop AI dashboard - Smart Cities World - October 9th, 2025 [October 9th, 2025]
- Machine Learning Used to Predict Live Birth Outcomes in Fresh Embryo Transfers - geneonline.com - October 9th, 2025 [October 9th, 2025]
- RIT researchers use machine learning to better understand the pathways of disease - Rochester Institute of Technology - October 7th, 2025 [October 7th, 2025]
- Leveraging machine learning to predict mosquito bed net utilization among women of reproductive age in sub-Saharan Africa - Malaria Journal - October 7th, 2025 [October 7th, 2025]
- Machine learning-based radiomics using magnetic resonance images for prediction of clinical complete response to neoadjuvant chemotherapy in patients... - October 7th, 2025 [October 7th, 2025]
- Machine Learning Self Driving Cars: The Technology Driving the Future of Mobility - SpeedwayMedia.com - October 7th, 2025 [October 7th, 2025]
- Investigating the relationship between blood factors and HDL-C levels in the bloodstream using machine learning methods - Journal of Health,... - October 7th, 2025 [October 7th, 2025]
- AI in the fast lane: F1 teams Alpine, Audi use machine learning as force multiplier - The Business Times - October 7th, 2025 [October 7th, 2025]
- Future Scope of Machine Learning in Healthcare Market Set to Witness Significant Growth by 2025-2032 - openPR.com - October 7th, 2025 [October 7th, 2025]
- AI and Machine Learning - AI readiness and adoption toolkit launched - Smart Cities World - October 4th, 2025 [October 4th, 2025]
- Machine Learning Model UmamiPredict Developed to Forecast Savory Taste of Molecules and Peptides - geneonline.com - October 4th, 2025 [October 4th, 2025]
- Machine Learning Boosts Crop Yield Predictions in Senegal - Bioengineer.org - October 4th, 2025 [October 4th, 2025]
- Machine learning-driven stability analysis of eco-friendly superhydrophobic graphene-based coatings on copper substrate - Nature - October 4th, 2025 [October 4th, 2025]
- Integrated machine learning analysis of proteomic and transcriptomic data identifies healing associated targets in diabetic wound repair - Nature - October 4th, 2025 [October 4th, 2025]
- Development and evaluation of a machine learning prediction model for short-term mortality in patients with diabetes or hyperglycemia at emergency... - October 4th, 2025 [October 4th, 2025]
- Fast and robust mixed gas identification and recognition using tree-based machine learning and sensor array response - Nature - October 4th, 2025 [October 4th, 2025]
- Estimation of sexual dimorphism of adult human mandibles of South Indian origin using non-metric parameters and machine learning classification... - October 4th, 2025 [October 4th, 2025]
- Cloud-Based Machine Learning Platforms Technologies Market Growth and Future Prospects - Precedence Research - October 4th, 2025 [October 4th, 2025]
- Machine Learning Framework Developed to Optimize Phosphorus Recovery in Hydrothermal Treatment of Livestock Manure - geneonline.com - October 4th, 2025 [October 4th, 2025]
- Unifying machine learning and interpolation theory via interpolating neural networks - Nature - October 2nd, 2025 [October 2nd, 2025]
- Anna: an open-source platform for real-time integration of machine learning classifiers with veterinary electronic health records - BMC Veterinary... - October 2nd, 2025 [October 2nd, 2025]
- The Future of Liver Health: Can Human Models and Machine Learning Reduce Disease Rates? - Technology Networks - October 2nd, 2025 [October 2nd, 2025]
- Machine Learning Radiomics Predicts Pancreatic Cancer Invasion - Bioengineer.org - October 2nd, 2025 [October 2nd, 2025]
- Next-generation COVID-19 detection using a metasurface biosensor with machine learning-enhanced refractive index sensing - Nature - October 2nd, 2025 [October 2nd, 2025]
- Machine learning-based models for screening of anemia and leukemia using features of complete blood count reports - Nature - October 2nd, 2025 [October 2nd, 2025]
- Estimating the peak age of chess players through statistical and machine learning techniques - Nature - October 2nd, 2025 [October 2nd, 2025]
- Optimizing water quality index using machine learning: a six-year comparative study in riverine and reservoir systems - Nature - October 2nd, 2025 [October 2nd, 2025]
- Physics-informed machine learning-based real-time long-horizon temperature fields prediction in metallic additive manufacturing - Nature - October 2nd, 2025 [October 2nd, 2025]
- The Silicon Revolution: How AI and Machine Learning Are Forging the Future of Semiconductor Manufacturing - FinancialContent - October 2nd, 2025 [October 2nd, 2025]