AIMC Topic: Prognosis

Clear Filters Showing 1501 to 1510 of 3837 articles

An artificial intelligence-generated model predicts 90-day survival in alcohol-associated hepatitis: A global cohort study.

Hepatology (Baltimore, Md.)
BACKGROUND AND AIMS: Alcohol-associated hepatitis (AH) poses significant short-term mortality. Existing prognostic models lack precision for 90-day mortality. Utilizing artificial intelligence in a global cohort, we sought to derive and validate an e...

Machine Learning-Based Prediction of Pathological Responses and Prognosis After Neoadjuvant Chemotherapy for Non-Small-Cell Lung Cancer: A Retrospective Study.

Clinical lung cancer
BACKGROUND: Neoadjuvant chemotherapy has variable efficacy in patients with non-small-cell lung cancer (NSCLC), yet reliable noninvasive predictive markers are lacking. This study aimed to develop a radiomics model predicting pathological complete re...

Machine learning for enhanced prognostication: predicting 30-day outcomes following posterior fossa decompression surgery for Chiari malformation type I in a pediatric cohort.

Journal of neurosurgery. Pediatrics
OBJECTIVE: Chiari malformation type I (CM-I) is a congenital disorder occurring in 0.1% of the population. In symptomatic cases, surgery with posterior fossa decompression (PFD) is the treatment of choice. Surgery is, however, associated with peri- a...

Machine learning for identifying tumor stemness genes and developing prognostic model in gastric cancer.

Aging
Gastric cancer presents a formidable challenge, marked by its debilitating nature and often dire prognosis. Emerging evidence underscores the pivotal role of tumor stem cells in exacerbating treatment resistance and fueling disease recurrence in gast...

Machine Learning as a Diagnostic and Prognostic Tool for Predicting Thrombosis in Cancer Patients: A Systematic Review.

Seminars in thrombosis and hemostasis
Khorana score (KS) is an established risk assessment model for predicting cancer-associated thrombosis. However, it ignores several risk factors and has poor predictability in some cancer types. Machine learning (ML) is a novel technique used for the...

Explainable and visualizable machine learning models to predict biochemical recurrence of prostate cancer.

Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
PURPOSE: Machine learning (ML) models presented an excellent performance in the prognosis prediction. However, the black box characteristic of ML models limited the clinical applications. Here, we aimed to establish explainable and visualizable ML mo...

Conventional and machine learning-based risk scores for patients with early-stage hepatocellular carcinoma.

Clinical and molecular hepatology
BACKGROUND/AIMS: The performance of machine learning (ML) in predicting the outcomes of patients with hepatocellular carcinoma (HCC) remains uncertain. We aimed to develop risk scores using conventional methods and ML to categorize early-stage HCC pa...

Exploring tumor heterogeneity in colorectal liver metastases by imaging: Unsupervised machine learning of preoperative CT radiomics features for prognostic stratification.

European journal of radiology
OBJECTIVES: This study aimed to investigate tumor heterogeneity of colorectal liver metastases (CRLM) and stratify the patients into different risk groups of prognoses following liver resection by applying an unsupervised radiomics machine-learning a...

Advancing predictive markers in lung adenocarcinoma: A machine learning-based immunotherapy prognostic prediction signature.

Environmental toxicology
The prognosis of lung adenocarcinoma (LUAD) is generally poor. Immunotherapy has emerged as a promising therapeutic modality, demonstrating remarkable potential for substantially prolonging the overall survival of individuals afflicted with LUAD. How...

Clinical evaluation of deep learning-based risk profiling in breast cancer histopathology and comparison to an established multigene assay.

Breast cancer research and treatment
PURPOSE: To evaluate the Stratipath Breast tool for image-based risk profiling and compare it with an established prognostic multigene assay for risk profiling in a real-world case series of estrogen receptor (ER)-positive and human epidermal growth ...