The Newly Developed Ai Can Predict Which Cancer Patients are at Risk for Life-Thread Wasting Syndrome, the New Study Says.
The Syndrome, Called Cachexia, Accounts for About 20% of All Cancer-Related Deaths, Statistics Show.
“Cancer Cachexia is a serous complication affecting many patients with cancer and is characterized by Systemic Infummation, Severe Muscle Wasting, and Profound Weight Loss,” Lead Researcher Saben Ahmed, Graduate Student at the University of South Florida, Said in a News Release.
No One Knows What Causes Cachexia, But Infummation, Increaded Cancer Metabolism, Insulin Resistance and Hormone Changes Are Suscted in the Wasting Syndrome, According to the National Cancer Institute.
CACHEXIA CAN’T BE Reverse by Nutrition Alone, But Must Be Treated with Medicines, The Nci Says. It’s hard to reverse one starts, and is most common in people with advanced cancer.
“Detection of Cancer Cachexia Enables Lifestyle and Pharmacological Interventions That Can Help Slow Muscle Wasting, Improve Metabolic Function, and Enhance the Patient’s Quality of Life,” Ahmed Said.
“UNFORTUNATEKY, Current Methods for Detecting Cancer Cachexia Rely on Clinical Observations, Weight Loss ThresHolds, and Indirect Biomarkers, Which Are Often Inconsistent, Subjective, and Detected Too Late in Disease Progression,” She added.
For the New Study, Researchers Taught an ai Program to Estimate The Risk of Cachexia Based on Imaging Scans and Clinical Data.
The First Examines CT Scans to Assess the Amount of Muscle in A Person’s Body, and then Uses Other Data to Judge A Patient’s Risk of Cachexia, Researchers Said.
The Ai Acuratutely Identified Cachexia in 77% of Cases When Fed Imaging Scans Along with a Patient’s Demographic Info, Weight, Height and Cancer Stage, Research Reported.
Accuracy Increured to 81% with the addition of lab results and 85% when doctors’ clinical notes were included in the mix, results show.
Using this assessment, the ai was able to better predicct survival odds for patients with pancreatic, colon and ovarian cancer, researchers said.
Results Also Showed That the Ai’s Assessment of Muscle Differed by About 2.5% On Averag From Calculations Made by Expert Radiologists.
“The Median Discredency of 2.48% Indicates That, on Averag, the Model’s Measurements of Skeletal Muscle Were Very Close to the Expert Radiologists’ Measurements, Demonstating The High Rally Reliability of Our Ai-Based Approach,” Ahmed Said.
Ahmed giftd these findings at the American Association for Cancer Research’s Annual Meeting In Chicago.
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Citation: AI PREDICTS WASTING SYNDROME IN CANCER PAIENTS (2025, APRIL 28) RETRIEV 28 APRIL 2025 FROM
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