AIMC Topic: Prognosis

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A Multi-Omics-Based Prognostic Model for Elderly Breast Cancer by Machine Learning: Insights From Hypoxia and Immunity of Tumor Microenvironment.

Clinical breast cancer
INTRODUCTION: Older adult breast cancer (OABC) patients (≥ 65 years) frequently experience poorer prognoses compared to younger adults, attributed to complex tumor biology and age-related factors. The present study employs a multiomics approach combi...

Transformer-based skeletal muscle deep-learning model for survival prediction in gastric cancer patients after curative resection.

Gastric cancer : official journal of the International Gastric Cancer Association and the Japanese Gastric Cancer Association
BACKGROUND: We developed and evaluated a skeletal muscle deep-learning (SMDL) model using skeletal muscle computed tomography (CT) imaging to predict the survival of patients with gastric cancer (GC).

Interpretable prognostic modeling for long-term survival of Type A aortic dissection patients using support vector machine algorithm.

European journal of medical research
OBJECTIVES: This study aims to develop a reliable and interpretable predictive model for long-term survival in Type A aortic dissection (TAAD) patients, utilizing machine learning (ML) algorithms.

TET2 gene mutation status associated with poor prognosis of transition zone prostate cancer: a retrospective cohort study based on whole exome sequencing and machine learning models.

Frontiers in endocrinology
BACKGROUND: Prostate cancer (PCa) in the transition zone (TZ) is uncommon and often poses challenges for early diagnosis, but its genomic determinants and therapeutic vulnerabilities remain poorly characterized.

Integrating Machine Learning and Bulk and Single-Cell RNA Sequencing to Decipher Diverse Cell Death Patterns for Predicting the Prognosis of Neoadjuvant Chemotherapy in Breast Cancer.

International journal of molecular sciences
Breast cancer (BRCA) continues to pose a serious risk to women's health worldwide. Neoadjuvant chemotherapy (NAC) is a critical treatment strategy. Nevertheless, the heterogeneity in treatment outcomes necessitates the identification of reliable biom...

Recent Advances in Artificial Intelligence for Precision Diagnosis and Treatment of Bladder Cancer: A Review.

Annals of surgical oncology
BACKGROUND: Bladder cancer is one of the top ten cancers globally, with its incidence steadily rising in China. Early detection and prognosis risk assessment play a crucial role in guiding subsequent treatment decisions for bladder cancer. However, t...

Integrated multi-omics analysis and machine learning refine molecular subtypes and clinical outcome for hepatocellular carcinoma.

Hereditas
The high morbidity and mortality of hepatocellular carcinoma (HCC) impose a substantial economic burden on patients' families and society, and the majority of HCC patients are detected at advanced stages and experience poor therapeutic outcomes, wher...

A strategy for multimodal integration of transcriptomics, proteomics, and radiomics data for the prediction of recurrence in patients with IDH-mutant gliomas.

International journal of cancer
Isocitrate dehydrogenase-mutant gliomas are lethal brain cancers that impair quality of life in young adults. Although less aggressive than glioblastomas, IDH-mutant gliomas invariably progress to incurable disease with unpredictable recurrence. A be...