AIMC Topic: Aged

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Automated Esophageal Cancer Staging From Free-Text Radiology Reports: Large Language Model Evaluation Study.

JMIR medical informatics
BACKGROUND: Accurate staging of esophageal cancer is crucial for determining prognosis and guiding treatment strategies, but manual interpretation of radiology reports by clinicians is prone to variability and limited accuracy, resulting in reduced s...

Clinically interpretable electrovectorcardiographic machine learning criteria for the detection of echocardiographic left ventricular hypertrophy.

PloS one
Echocardiographic left ventricular hypertrophy (Echo-LVH) is frequently underdetected by traditional electrocardiogram (ECG) criteria due to limited sensitivity. We investigated whether integrating ECG with vectorcardiography (VCG) using a clinically...

AI-driven 3D CT imaging prediction model for improving preoperative detection of visceral pleural invasion in early-stage lung cancer.

PloS one
Visceral pleural invasion (VPI) is a critical prognostic factor in early-stage non-small-cell lung cancer (NSCLC), significantly affecting patient outcomes. Conventional computed tomography (CT) often fails to diagnose VPI accurately. This retrospect...

Association between atherogenic index of plasma and sepsis in critically ill patients with ischemic stroke: a retrospective cohort study using propensity score and machine learning approaches.

Lipids in health and disease
BACKGROUND: Sepsis is a severe and frequent complication among ischemic stroke patients during hospitalization. The atherogenic index of plasma (AIP), as metabolism-related markers, are closely linked to inflammation. However, their relationship with...

Multi-channel deep learning radiomics model based on contrast-enhanced CT for predicting postoperative prognosis in laryngeal carcinoma.

BMC cancer
BACKGROUND: Accurate prediction of prognosis and risk stratification in patients with laryngeal cancer can inform appropriate treatment decision-making. This study aims to develop a multi-channel deep learning radiomics model based on contrast-enhanc...

Using magnetic resonance imaging-based subregional texture analysis models to classify knee osteoarthritis severity by compartment.

Scientific reports
We evaluated the effectiveness of magnetic resonance imaging (MRI)-based subregional texture analysis (TA) models for classifying knee osteoarthritis (OA) severity grades by compartment. We identified 122 MR images of 121 patients with knee OA (mild-...

Modelling of immune infiltration in prostate cancer treated with HDR-brachytherapy using Raman spectroscopy and machine learning.

Scientific reports
Prostate cancer is characterized by an immunosuppressive tumour environment. This work combines Raman spectroscopy with group-and-bases-restricted non-negative matrix factorization (GBR-NMF) and machine learning to assemble models of immune cell dens...

Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China.

Scientific reports
This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 patients with T2DM w...

A Machine Learning-Based Scoring System to Identify High Immunoactivity Microsatellite Stability Tumors by Quantifying Similarity to Microsatellite Instability-High Tumors in Colorectal Cancers: Development and Quantitative Study.

JMIR formative research
BACKGROUND: Microsatellite stability (MSS) colorectal cancers (CRCs) have a limited response to immune checkpoint inhibitors (ICIs) compared to microsatellite instability-high (MSI-H) CRCs. Nevertheless, previous studies have shown that some MSS CRCs...

Automated detection of large vessel occlusion using deep learning: a pivotal multicenter study and reader performance study.

Journal of neurointerventional surgery
BACKGROUND: To evaluate the stand-alone efficacy and improvements in diagnostic accuracy of early-career physicians of the artificial intelligence (AI) software to detect large vessel occlusion (LVO) in CT angiography (CTA).