AIMC Topic: Middle Aged

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Histological proven AI performance in the UKLS CT lung cancer screening study: Potential for workload reduction.

European journal of cancer (Oxford, England : 1990)
PURPOSE: Artificial intelligence (AI) could reduce lung cancer screening computer tomography (CT)-reading workload if used as a first-reader, ruling-out negative CT-scans at baseline. Evidence is lacking to support AI performance when compared to gol...

Artificial Intelligence Based Augmented Reality Navigation in Minimally Invasive Partial Nephrectomy.

Urology
OBJECTIVE: To explore the role of artificial intelligence based augmented reality intraoperative real-time navigation in minimally invasive partial nephrectomy to standardize renal hilum dissection procedures and improve operative efficiency.

Predicting social anxiety disorder based on communication logs and social network data from a massively multiplayer online game: Using a graph neural network.

Psychiatry and clinical neurosciences
AIM: Social anxiety disorder (SAD) is a mental disorder that requires early detection and treatment. However, some individuals with SAD avoid face-to-face evaluations, which leads to delayed detection. We aim to predict individuals with SAD based on ...

The feasibility and cost-effectiveness of implementing mobile low-dose computed tomography with an AI-based diagnostic system in underserved populations.

BMC cancer
BACKGROUND: Low-dose computed tomography (LDCT) significantly increases early detection rates of lung cancer and reduces lung cancer-related mortality by 20%. However, many significant screening barriers remain. This study conduct an initial feasibil...

Preoperative clinical radiomics model based on deep learning in prognostic assessment of patients with gallbladder carcinoma.

BMC cancer
OBJECTIVE: We aimed to develop a preoperative clinical radiomics survival prediction model based on the radiomics features via deep learning to provide a reference basis for preoperative assessment and treatment decisions for patients with gallbladde...

Machine learning for temporary stoma after intestinal resection in surgical decision-making of Crohn's disease.

BMC gastroenterology
BACKGROUND: Crohn's disease (CD) often necessitates surgical intervention, with temporary stoma creation after intestinal resection (IR) being a crucial decision. This study aimed to construct novel models based on machine learning (ML) to predict te...

Detecting severe coronary artery stenosis in T2DM patients with NAFLD using cardiac fat radiomics-based machine learning.

Scientific reports
To analyze radiomics features of cardiac adipose tissue in individuals with type 2 diabetes (T2DM) and non-alcoholic fatty liver disease (NAFLD), integrating relevant clinical indicators, and employing machine learning techniques to construct a preci...