AIMC Topic: Neoplasm Metastasis
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Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides.
Nature communications
Jul 1, 2025
Accurate risk stratification is critical for guiding treatment decisions in early breast cancer. We present an artificial intelligence (AI)-based tool that analyzes digitized tumor slides to predict 5-year metastasis-free survival (MFS) in patients w...
Development and validation of a machine learning-based risk model for metastatic disease in nmCRPC patients: a tumor marker prognostic study.
International journal of surgery (London, England)
May 1, 2025
BACKGROUND: Nonmetastatic castration-resistant prostate cancer (nmCRPC) is a clinical challenge due to the high progression rate to metastasis and mortality. To date, no prognostic model has been developed to predict the metastatic probability for nm...
In-silico investigation integrated with machine learning to identify potential inhibitors targeting AKT2: Key driver of cancer cell progression and metastasis.
Computer methods and programs in biomedicine
Apr 18, 2025
BACKGROUND AND OBJECTIVE: In search of a key driver for the invasive growth of cancer metastasis, AKT2 is found to be exceptionally expressed in colorectal cancer and its metastasis. Again, exceeding genomic arrangements of AKT2 can be held responsib...
Optimizing prediction of metastasis among colorectal cancer patients using machine learning technology.
BMC gastroenterology
Apr 18, 2025
BACKGROUND AND AIM: Colorectal cancer is among the most prevalent and deadliest cancers. Early prediction of metastasis in patients with colorectal cancer is crucial in preventing it from the advanced stages and enhancing the prognosis among these pa...
Machine Learning Models of Early Longitudinal Toxicity Trajectories Predict Cetuximab Concentration and Metastatic Colorectal Cancer Survival in the Canadian Cancer Trials Group/AGITG CO.17/20 Trials.
JCO clinical cancer informatics
Apr 11, 2025
PURPOSE: Cetuximab (CET), targeting the epidermal growth factor receptor, is a systemic treatment option for patients with colorectal cancer. One known predictive factor for CET efficacy is the presence of CET-related rash; other putative toxicity fa...
MISTIC: a novel approach for metastasis classification in Italian electronic health records using transformers.
BMC medical informatics and decision making
Apr 10, 2025
BACKGROUND: Analysis of Electronic Health Records (EHRs) is crucial in real-world evidence (RWE), especially in oncology, as it provides valuable insights into the complex nature of the disease. The implementation of advanced techniques for automated...
Development and validation of interpretable machine learning models to predict distant metastasis and prognosis of muscle-invasive bladder cancer patients.
Scientific reports
Apr 6, 2025
Muscle-Invasive Bladder Cancer (MIBC) is a more aggressive disease than non-muscle-invasive bladder cancer (NMIBC), with greater chances of metastasis. We sought to develop machine learning (ML) models to predict metastasis and prognosis in MIBC pati...
The Extent to Which Artificial Intelligence Can Help Fulfill Metastatic Breast Cancer Patient Healthcare Needs: A Mixed-Methods Study.
Current oncology (Toronto, Ont.)
Mar 2, 2025
The Artificial Intelligence Patient Librarian (AIPL) was designed to meet the psychosocial and supportive care needs of Metastatic Breast Cancer (MBC) patients with HR+/HER2- subtypes. AIPL provides conversational patient education, answers user ques...
Using prognostic signatures and machine learning to identify core features associated with response to CDK4/6 inhibitor-based therapy in metastatic breast cancer.
Oncogene
Feb 26, 2025
CDK4/6 inhibitors in combination with endocrine therapy are widely used to treat HR+/HER2- metastatic breast cancer leading to improved progression-free survival (PFS) compared to single agent endocrine therapy. Over 300 patients receiving standard-o...
Machine learning-based prediction of distant metastasis risk in invasive ductal carcinoma of the breast.
PloS one
Feb 26, 2025
More than 90% of deaths due to breast cancer (BC) are due to metastasis-related complications, with invasive ductal carcinoma (IDC) of the breast being the most common pathologic type of breast cancer and highly susceptible to metastasis to distant o...
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