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Background: Manual extraction of real-world clinical data for research can be time-consuming and prone to error. We assessed the feasibility of using natural language processing (NLP), an AI technique, to automate data extraction for patients with advanced lung cancer (aLC). We assessed the external validity of our NLP-extracted data by comparing our findings to those reported in the literature.

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Objectives: The lack of definitive biomarkers presents a significant challenge for chemo-immunotherapy in extensive-stage small-cell lung cancer (ES-SCLC). We aimed to identify key genes associated with chemo-immunotherapy efficacy in ES-SCLC through comprehensive gene expression analysis using machine learning (ML).

Methods: A prospective multicenter cohort of patients with ES-SCLC who received first-line chemo-immunotherapy was analyzed.

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Zeolites are a large family of minerals and the most studied is the naturally occurring clinoptilolite. They possess anti-inflammatory, antioxidant, and detoxifying properties which makes them valuable for medicinal use. Element analysis of zeolite's composition is necessary for its precise chemical characterization, and within this work development of a suspension method for the determination of manga nese, iron, and zinc by total reflection X-ray fluorescence spec-trometry (TXRF) was presented.

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Evaluation of dose calculation method with a combination of Monte Carlo method and removal-diffusion equation in heterogeneous geometry for boron neutron capture therapy.

Biomed Phys Eng Express

January 2025

Institute for Integrated Radiation and Nuclear Science, Kyoto University, 2-1010 Asashiro-nishi, Kumatori-cho, Sennan-gun, Osaka, 590-0494, JAPAN.

Clinical research in boron neutron capture therapy (BNCT) has been conducted worldwide. Currently, the Monte Carlo (MC) method is the only dose calculation algorithm implemented in the treatment planning system for the clinical treatment of BNCT. We previously developed the MC-RD calculation method, which combines the MC method and the removal-diffusion (RD) equation, for fast dose calculation in BNCT.

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Objective: We aimed to elucidate the histopathological pre-diagnosis of cranial gliomas with magnetic resonance imaging (MRI) techniques in gliomas.

Method: A total of 82 glioma patients were enrolled to our study. Pre-operative conventional MRI images (non-contrast T1/T2/flair/contrast-enhanced T1) and advanced MRI images (DAG and ADC mapping, MRI spectroscopy and perfusion MRI [PMRI]) were analyzed.

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