AIMC Topic: Prognosis

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Machine learning reveals limited predictive value of clinical factors for asthma exacerbations.

Scientific reports
While predictors of asthma exacerbation risk are generally well established, predictors of exacerbation severity remain largely undefined. Identifying robust clinical predictors of exacerbation severity is essential to support tailored management str...

A robust artificial intelligence system for predicting EBV status in gastric cancer biopsy and resection specimens.

Scientific reports
Epstein-Barr virus (EBV) associated gastric cancer, accounting for ~ 9% of all gastric cancers, has unique pathologic, genomic, and clinical features and is linked to a better prognosis. Therefore, we aim to develop and validate a robust deep learnin...

Artificial intelligence for the prediction of posthepatectomy recurrence in hepatocellular carcinoma: a systematic review and meta-analysis.

Annals of medicine
OBJECTIVE: Posthepatectomy recurrence of hepatocellular carcinoma (HCC) is a major cause of poor prognosis. Accurate prediction is essential for reducing the burden of advanced disease and improving outcomes.

AI-driven prognostics in pediatric bone marrow transplantation: a CAD approach with Bayesian and PSO optimization.

BMC medical informatics and decision making
Bone marrow transplantation (BMT) is a critical treatment for various hematological diseases in children, offering a potential cure and significantly improving patient outcomes. However, the complexity of matching donors and recipients and predicting...

Development and validation of diagnostic and prognostic prediction tools for dental caries in young children through prospective and cross-sectional observational studies: a protocol.

BMJ open
INTRODUCTION: Dental caries is the most common oral disease worldwide, affecting up to 90% of children globally. It can lead to pain, infection and impaired quality of life. Early prevention is a key strategy for reducing the prevalence of dental car...

Artificial neural networks as a prognostic tool using hyperspectral imaging on pretherapeutic histopathological specimens of esophageal adenocarcinoma.

Journal of cancer research and clinical oncology
PURPOSE: The integration of artificial intelligence (AI) with hyperspectral imaging (HSI) offers a promising avenue for improving pre-therapeutic prognosis, a key factor in optimizing cancer treatment strategies. This study explores the potential of ...

Predicting six-month mortality in adult hemophagocytic lymphohistiocytosis with machine learning: a prognostic approach utilizing laboratory data.

Annals of medicine
BACKGROUND: Hemophagocytic lymphohistiocytosis (HLH) is associated with high mortality rates. This study was conducted to develop and validate a predictive model for adult HLH patients at high risk of six months mortality using machine learning (ML) ...

Identification of methylation-related genes and the potential regulatory mechanism of SLAMF6 in CMS4 colorectal cancer.

Clinical epigenetics
BACKGROUNDS: Consensus molecular subtype 4 (CMS4) of colorectal cancer (CRC) is characterized by TGF-β activation, and generally accompanied with metastasis and recurrence. Nevertheless, molecular biomarkers and regulatory mechanisms underlying CMS4 ...

Survival risk stratification of 2021 WHO glioblastoma by MRI radiomics and biological exploration.

BMC cancer
BACKGROUND: There is variability in overall survival among 2021 World Health Organization isocitrate dehydrogenase wild type glioblastoma (IDH-wt GBM) patients. The aim of the study was to develop a combined model for stratifying survival risk in IDH...