AIMC Topic: Nomograms

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Predicting clinical prognosis in gastric cancer using deep learning-based analysis of tissue pathomics images.

Computer methods and programs in biomedicine
OBJECTIVE: Evaluate the utility of a machine learning-based pathomics model in predicting overall survival (OS) post-surgery for gastric cancer patients.

Machine learning-based histopathological features of histological slides and clinical characteristics as a novel prognostic indicator in diffuse large B-cell lymphoma.

Pathology, research and practice
OBJECTIVE: This study developed and validated a deep learning model based on clinical and histopathological features for predicting the outcomes of diffuse large B-cell lymphoma (DLBCL).

Construction and validation of a prognostic nomogram model integrating machine learning-pathomics and clinical features in IDH-wildtype glioblastoma.

Journal of translational medicine
BACKGROUND: Novel diagnostic criteria for glioblastoma (GBM) in the 2021 WHO classification emphasize the importance of integrating pathological and molecular features. Pathomics, which involves the extraction of digital pathology data, is gaining si...

Multi-Organ metabolic profiling with [F]F-FDG PET/CT predicts pathological response to neoadjuvant immunochemotherapy in resectable NSCLC.

European journal of nuclear medicine and molecular imaging
PURPOSE: To develop and validate a novel nomogram combining multi-organ PET metabolic metrics for major pathological response (MPR) prediction in resectable non-small cell lung cancer (rNSCLC) patients receiving neoadjuvant immunochemotherapy.

Development of a machine learning-based predictive nomogram for screening children with juvenile idiopathic arthritis: a pseudo-longitudinal study of 223,195 children in the United States.

Frontiers in public health
BACKGROUND: Juvenile idiopathic arthritis (JIA) is a prevalent chronic rheumatological condition in children, with reported prevalence ranging from 12. 8 to 45 per 100,000 and incidence rates from 7.8 to 8.3 per 100,000 person-years. The diagnosis of...

Immunological biomarkers and gene signatures predictive of radiotherapy resistance in non-small cell lung cancer.

Frontiers in immunology
INTRODUCTION: A significant challenge in treating non-small cell lung cancer (NSCLC) is its inherent resistance to radiation therapy, leading to poor patient prognosis. This study aimed to identify key genes influencing radiotherapy resistance in NSC...

The Role of PANoptosis-Related Genes in Predicting Breast Cancer Survival and Immune Prospect.

BioMed research international
The function of PANoptosis in breast cancer (BC) remains indistinct. We constructed a nomogram model to predict the prognosis of BC to identify high-risk patients and help them receive more accurate treatment. We used Cox regression and least absol...

Development and validation of a LASSO logistic regression based nomogram for predicting live births in women with polycystic ovary syndrome: a retrospective cohort study.

Frontiers in endocrinology
OBJECTIVE: There is limited study on predictive models for live births in patients with polycystic ovarian syndrome (PCOS). The study aimed to develop and validate a nomogram for predicting live births in Chinese women with PCOS, as well as to identi...

Development and validation of a predictive model for refracture risk in elderly individuals with osteoporotic vertebral compression fracture: a retrospective study in China.

Aging clinical and experimental research
BACKGROUND: The rising incidence of refractures and associated adverse outcomes among individuals with osteoporotic vertebral compression fractures has gained significant attention. Identifying refracture risk is crucial for implementing effective pr...