AIMC Topic: Prognosis

Clear Filters Showing 71 to 80 of 3837 articles

An assisted diagnostic and prognostic model for endometrial cancer using 36 serological markers and clinical variables from 562 patients.

Scientific reports
Endometrial carcinoma (EC) has demonstrated a concerning epidemiological trajectory. Current evaluation systems for EC are limited to postoperative analysis, necessitating the development of a preoperative risk stratification model. Researchers aimed...

Multimodal AI and tumour microenvironment integration predicts metastasis in cutaneous melanoma.

Nature communications
Accurate prognostication is essential to guide clinical management in localised cutaneous melanoma (CM), the form of skin cancer with the highest mortality. While the tumour microenvironment (TME) plays a key role in disease progression, current stag...

Automatically quantifying spatial heterogeneity of immune and tumor hypoxia environment and predicting disease-free survival for patients with rectal cancer.

Cancer immunology, immunotherapy : CII
Immunohistochemistry (IHC) remains the gold standard for evaluating protein expression in tumor microenvironment analysis. This approach hinders robust correlation analyses between spatial heterogeneity in the tumor microenvironment and clinical outc...

Integrated machine learning and single-cell analysis identify chromatin-remodeling gene signature for diagnosis and prognosis in nasopharyngeal carcinoma.

Clinical and experimental medicine
This study examines the function of chromatin-remodeling genes (CRGs) in nasopharyngeal carcinoma (NPC), with an emphasis on their potential as prognostic and diagnostic biomarkers. We examined gene expression information collected from multiple data...

Multi-omics unravel heterogeneity of glucose metabolism reprogramming in gastric cancer.

Clinical and experimental medicine
Gastric cancer (GC) presents striking survival disparities: 85-100% for early-stage versus only 5-20% for advanced disease. Glucose metabolic reprogramming (GMS)-a cancer hallmark linked to the Warburg effect-fuels tumor progression and immune evasio...

Predicting distant metastasis in early-onset kidney cancer using machine learning: a SEER database study with external validation.

Clinical and experimental medicine
Patients with early-onset kidney cancer (EOKC) face a marked decline in prognosis after distant metastasis, yet the accuracy of current predictive methods remains limited. This study aims to develop a predictive model using multiple machine learning ...

A novel deep learning system for STEMI prognostic prediction from multi-sequence cardiac magnetic resonance.

Science bulletin
ST-elevation myocardial infarction (STEMI) remains a leading cause of cardiovascular morbidity and mortality worldwide, and accurate early risk stratification is critical for implementing precision therapies in clinical practice. However, existing cl...

Automated quantification of Ki-67 expression in breast cancer from H&E-stained slides using a transformer-based regression model.

Breast cancer research : BCR
BACKGROUND: Accurate quantification of the Ki-67 proliferation index is essential for breast cancer prognosis and treatment planning. Current automated methods, including classical and deep learning approaches based on cell detection or segmentation,...

CT-based radiomics and deep learning models for predicting thyroid cartilage invasion and patient prognosis in laryngeal carcinoma.

Scientific reports
Accurate assessment of thyroid cartilage invasion is crucial for treatment decision-making and prognosis evaluation in laryngeal squamous cell carcinoma (LSCC). This study aimed to compare the performance of the radiomics and deep learning (DL) model...

Performance of the pediatric index of mortality (PIM-3) in a Moroccan PICU: challenges in resource-limited settings.

European journal of pediatrics
UNLABELLED: Prognostic scores such as the Pediatric Index of Mortality (PIM-3) are widely used to estimate mortality risk in PICUs, yet their performance in low- and middle-income countries (LMICs) remains uncertain. We aimed to evaluate the predicti...