AIMC Topic: Aged

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B lymphocyte subset-based stratification in primary Sjögren's syndrome: implications for lymphoma risk and personalized treatment.

Clinical rheumatology
OBJECTIVE: This study aimed to perform a detailed stratification analysis of B lymphocyte subsets in patients with primary Sjögren's syndrome (pSS) and to investigate their associations with lymphoma risk, clinical phenotypes, and disease activity.

Microbiome and fragmentation pattern of blood cell-free DNA and fecal metagenome enhance colorectal cancer micro-dysbiosis and diagnosis analysis: a proof-of-concept study.

mSystems
Colorectal cancer (CRC) is the third most common cancer, and it can be prevented by performing early screening. As a hallmark of cancer, the human microbiome plays important roles in the occurrence and development of CRC. Recently, the blood microbio...

Development and validation of a novel chronic pancreatitis pathological grade based on artificial intelligence.

Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
BACKGROUND: Effective chronic pancreatitis (CP) treatment requires accurate severity evaluation, but no histopathology grading system exists. This study aimed to develop and validate a novel CP pathological grade (Histopathology-derived CPpG) using q...

Intelligent predictive risk assessment and management of sarcopenia in chronic disease patients using machine learning and a web-based tool.

European journal of medical research
BACKGROUND: Individuals with chronic diseases are at higher risk of sarcopenia, and precise prediction is essential for its prevention. This study aims to develop a risk scoring model using longitudinal data to predict the probability of sarcopenia i...

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

Journal of translational medicine
BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patients with epidermal growth factor receptor (EGFR)-mutant lung adenocarcinoma. However, not all patients with EGFR mutations respond to TKIs. This study...

Development and validation of machine learning models for predicting no. 253 lymph node metastasis in left-sided colorectal cancer using clinical and CT-based radiomic features.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: The appropriate ligation level of the inferior mesenteric artery (IMA) in left-sided colorectal cancer (CRC) surgery is debated, with metastasis in No. 253 lymph node (No. 253 LN) being a key determining factor. This study aimed to develo...

Development and validation of machine learning models for predicting low muscle mass in patients with obesity and diabetes.

Lipids in health and disease
BACKGROUND AND AIMS: Low muscle mass (LMM) is a critical complication in patients with obesity and diabetes, exacerbating metabolic and cardiovascular risks. Novel obesity indices, such as the body roundness index (BRI), conicity index, and relative ...

Development and validation a radiomics combined clinical model predicts treatment response for esophageal squamous cell carcinoma patients.

BMC gastroenterology
PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiomics and clinical characteristics to predicting the definitive chemoradiotherapy (dCRT) treatment response in esophageal squamous cell carcinoma (ESCC)...

Application of deep learning reconstruction combined with time-resolved post-processing method to improve image quality in CTA derived from low-dose cerebral CT perfusion data.

BMC medical imaging
BACKGROUND: To assess the effect of the combination of deep learning reconstruction (DLR) and time-resolved maximum intensity projection (tMIP) or time-resolved average (tAve) post-processing method on image quality of CTA derived from low-dose cereb...