AIMC Topic: SEER Program
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A Deep Learning Survival Model for Evaluating the Survival Prognosis of Papillary Thyroid Cancer: A Population-Based Cohort Study.
Annals of surgical oncology
Apr 20, 2025
BACKGROUND: Deep learning can assess the individual survival prognosis in sizeable datasets with intricate underlying processes. However, studies exploring the performance of deep learning survival in papillary thyroid cancer (PTC) are lacking. This ...
Explainable machine learning for predicting lung metastasis of colorectal cancer.
Scientific reports
Apr 19, 2025
Patients with lung metastasis of colorectal cancer typically have a poor prognosis. Therefore, establishing an effective screening and diagnosis model is paramount. Our study seeks to construct and verify a predictive model utilizing machine learning...
Updated perspectives on visceral pleural invasion in non-small cell lung cancer: A propensity score-matched analysis of the SEER database.
Current problems in cancer
Apr 18, 2025
BACKGROUND: Visceral pleural invasion (VPI), including PL1 (the tumor invades beyond the elastic layer) and PL2 (the tumor extends to the surface of the visceral pleura), plays a crucial role in staging Non-Small Cell Lung Cancer (NSCLC). However, th...
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...
Machine learning models for prediction of lymph node metastasis in patients with gastric cancer: a Chinese single-centre study with external validation in an Asian American population.
BMJ open
Mar 25, 2025
OBJECTIVE: To develop and validate machine learning (ML)-based models to predict lymph node metastasis (LNM) in patients with gastric cancer (GC).
Using machine learning for predicting cancer-specific mortality in bladder cancer patients undergoing radical cystectomy: a SEER-based study.
BMC cancer
Mar 21, 2025
BACKGROUND: Accurately assessing the prognosis of bladder cancer patients after radical cystectomy has important clinical and research implications. Current models, based on traditional statistical approaches and complex variables, have limited perfo...
Development and evaluation of a multivariable prediction model for overall survival in advanced stage pulmonary carcinoid using machine learning.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Feb 25, 2025
BACKGROUND: Evidence is limited on whether patients with advanced pulmonary carcinoid (APC) benefit from comprehensive pulmonary resection (CPR), chemotherapy, or radiotherapy. Existing prognostic models for APC are limited and do not guide treatment...
Predicting cancer survival at different stages: Insights from fair and explainable machine learning approaches.
International journal of medical informatics
Feb 13, 2025
OBJECTIVES: While prior machine learning (ML) models for cancer survivability prediction often treated all cancer stages uniformly, cancer survivability prediction should involve understanding how different stages impact the outcomes. Additionally, t...
Machine learning identifies the association between second primary malignancies and postoperative radiotherapy in young-onset breast cancer patients.
PloS one
Feb 6, 2025
BACKGROUND: A second primary malignant tumor is one of the most important factors affecting the long-term survival of young women with breast cancer (YWBC). As one of the main treatments for breast cancer YWBC patients, postoperative radiotherapy (PO...
Individual risk and prognostic value prediction by interpretable machine learning for distant metastasis in neuroblastoma: A population-based study and an external validation.
International journal of medical informatics
Jan 29, 2025
PURPOSE: Neuroblastoma (NB) is a childhood malignancy with a poor prognosis and a propensity for distant metastasis (DM). We aimed to establish machine learning (ML) based model to accurately predict risk of DM and prognosis of NB patients with DM.
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