AI Medical Compendium Journal:
Discover oncology

Showing 1 to 7 of 7 articles

Machine learning predicts prognosis in patients with gastroenteropancreatic neuroendocrine tumors with liver metastases.

Discover oncology
BACKGROUND: Patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs) and liver metastases typically exhibit poor prognoses. However, accurate survival prediction models remain insufficient. This study aimed to develop machine learning...

Construction of a novel CD8T cell-related index for predicting clinical outcomes and immune landscape in ovarian cancer by combined single-cell and RNA-sequencing analysis.

Discover oncology
BACKGROUND: CD8T cells, also known as cytotoxic T lymphocytes, play a key role in the tumor immune microenvironment (TME) and immune response. The aim of this study was to explore the potential role of CD8T cell-associated biomarkers in predicting pr...

Pan-cancer predictive survival model development and evaluation using electronic health record and genetic data across 10 cancer types.

Discover oncology
The growing burden of cancer and recent surge in healthcare data availability call for new ways of analysing this multifactorial disease and improving patient outcomes. The aim of this study is to develop and evaluate prognostic cancer survival model...

Research on the functions and potential mechanisms of STAT3 in chronic myelogenous leukemia.

Discover oncology
OBJECTIVE: To explore the bioinformatics characteristics and potential mechanisms of signal transducer and activator of transcription (STAT3) in chronic myelogenous leukemia (CML).

Identification of novel potential biomarkers using bulk RNA and single cells to build a neural network model for diagnosis of liver cancer.

Discover oncology
BACKGROUND: As a common cancer, liver cancer imposes an unacceptable burden on patients, but its underlying molecular mechanisms are still not fully understood. Therefore, there is an urgent need to potential biomarkers and diagnostic models for live...

Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm.

Discover oncology
PURPOSE: The aim of this study was to develop and validate a machine learning (ML) based prediction model for sentinel lymph node metastasis in breast cancer to identify patients with a high risk of sentinel lymph node metastasis.

The role of nanomedicine and artificial intelligence in cancer health care: individual applications and emerging integrations-a narrative review.

Discover oncology
Cancer remains one of the deadliest diseases globally, significantly impacting patients' quality of life. Addressing the rising incidence of cancer deaths necessitates innovative approaches such as nanomedicine and artificial intelligence (AI). The c...