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
GLOBE SCIENTIFIC, LLC

Download Mobile App




AI Method Predicts Overall Survival Rate of Prostate Cancer Patients

By LabMedica International staff writers
Posted on 04 Jun 2025

Prostate adenocarcinoma (PAC) accounts for 99% of prostate cancer diagnoses and is the second most common cancer in men globally after skin cancer. More...

With more than 3.3 million men in the United States diagnosed with prostate cancer and one in 44 dying from the disease, early and accurate survival prediction is vital. However, accurately predicting the overall survival of patients with PAC has long been a clinical challenge due to the disease's complex and varied nature. While early diagnosis improves treatment outcomes, the diverse progression patterns of this cancer make precise prognosis difficult. Now, scientists have developed a machine learning-based method that uses ensemble models to deliver near-perfect survival estimates for patients with PAC.

In a study led by University of Sharjah (Sharjah, UAE) and Near East University (Istanbul, Turkey), the researchers applied and evaluated eight machine learning ensemble methods to predict overall survival outcomes in prostate adenocarcinoma patients, using clinical and genomic data from The Cancer Genome Atlas (TCGA) PanCancer Atlas. The models assessed in the study include Random Forest (RF), AdaBoost, Gradient Boosting (GB), Extreme Gradient Boosting (XGB), LightGBM (LGBM), CatBoost, Hard Voting Classifier (HVC), and Support Vector Classifier (SVC). These ensemble techniques combine the predictive power of multiple algorithms to improve model performance. By using essential performance indicators such as accuracy, precision, recall, F1 score, and ROC AUC score, the researchers determined how well each method predicted patient survival.

The findings, published in the journal Computers in Biology and Medicine, reveal that among the eight models tested, GB emerged as the top performer, achieving a perfect score of 1.0 in accuracy, precision, recall, and F1 score, and 0.99 for ROC AUC. Other high-performing models included RF and AdaBoost, which also demonstrated strong predictive capability and robustness in distinguishing between positive and negative survival outcomes. The ability of these models to accurately identify high-risk and low-risk patients could offer critical support for clinical decision-making and individualized patient care. The use of these AI-driven models could greatly enhance the clinical understanding of PAC and overcome existing barriers by offering tailored prognostic insights, potentially leading to improved outcomes and optimized treatment strategies.

“The outstanding performances of GB are suggestive that it is an ensemble model, highly capable of predicting PAC (Prostate adenocarcinoma), because it identifies all true positive cases, and can minimize the negative cases as well as can be clinically integrated,” the study authors wrote. “RF performances showed its ability to distinguish between positive and negative cases of PAC highlighting its high level of accuracy, especially in predicting the presence of PAC.”


Gold Member
Troponin T QC
Troponin T Quality Control
3-Part Differential Hematology Analyzer
Swelab Alfa Plus Sampler
New
Myocardial Infarction Test
Finecare cTn I/NT-proBNP Rapid Quantitative Test
New
HAV Rapid Test
OnSite HAV IgG/IgM Rapid Test
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Clinical Chemistry

view channel
Image: New automated lab procedures can detect opioids in tiny amounts of blood (Photo courtesy of Tripathi Lab/Brown University)

First-Of-Its-Kind Quantitative Method Assesses Opioid Exposure in Newborns

As the opioid crisis continues to impact communities across the United States, laboratories encounter significant difficulties in accurately detecting opioid substances in individuals with opioid use disorder.... Read more

Hematology

view channel
Image: CitoCBC is the world first cartridge-based CBC to be granted CLIA Waived status by FDA (Photo courtesy of CytoChip)

Disposable Cartridge-Based Test Delivers Rapid and Accurate CBC Results

Complete Blood Count (CBC) is one of the most commonly ordered lab tests, crucial for diagnosing diseases, monitoring therapies, and conducting routine health screenings. However, more than 90% of physician... Read more

Immunology

view channel
Image: T cell immunity could be a marker for early Parkinson’s treatment (Photo courtesy of Shutterstock)

T Cells in Blood Can Detect Parkinson's Years Before Diagnosis

Diagnosing Parkinson’s disease before the appearance of motor symptoms remains one of neurology’s most significant challenges. Patients can go years—even decades—without a diagnosis, as subtle early indicators... Read more

Microbiology

view channel
Image: A prototype of the lateral flow test (Photo courtesy of University of Exeter)

POC Lateral Flow Test Detects Deadly Fungal Infection Faster Than Existing Techniques

Diagnosing mucormycosis—an aggressive and often deadly fungal infection—remains a major challenge due to the disease’s rapid progression and the lack of fast, accurate diagnostic tools. The problem became... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.