We scan the top radiology sources so you don’t have to.
From AI breakthroughs to imaging trends, we serve up real-time radiology insights.
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Interpretable Machine learning model using Dual-Energy CT for predicting adverse histopathological status in gastric Cancer: A multicenter study
Gastric cancer (GC) ranks as the fifth most prevalent malignant neoplasm globally and is also the fifth leading cause of cancer-related deaths worldwide[1]. Advanced tumor stage (T3/T4), lymph node metastasis (LNM), and lymphovascular or perineural invasion (LVI/PNI) are strongly associated with poor clinical outcomes[2–5]. These prognostic factors reflect advanced-stage disease, in which patients are more likely to benefit from neoadjuvant therapy[6–8]. Recently, some scholars have proposed tha…
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Development of predictive models to identify the intracranial aneurysm responsible for subarachnoid hemorrhage in patients with multiple saccular aneurysms
To develop and test machine learning (ML) models using computed tomography angiography to identify the intracranial aneurysm (IA) responsible for subarachnoid hemorrhage (SAH) accurately in patients with multiple saccular IAs and to determine whether these models outperform traditional predictive markers.
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Use of cardiac CT in the preoperative assessment for non-cardiac surgery – What are the guideline recommendations?
Peri-operative cardiovascular complications remain a leading cause of morbidity and mortality in patients undergoing non-cardiac surgery (NCS). Demographics of patients undergoing surgery show trends towards increasing numbers of elderly patients and increasing numbers of patients with multiple cardiovascular comorbidities.1 Given the rising prevalence of cardiovascular disease (CVD) and the more than 300 million surgical procedures performed worldwide each year, accurate risk stratification is …
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Multimodal deep learning model for predicting microsatellite instability in colorectal cancer by contrast-enhanced computed tomography and histopathology
Colorectal cancer (CRC) ranks as the third most commonly diagnosed malignancy and the second leading cause of cancer-related deaths globally [1]. Despite advancements in surgery and systemic therapies, the intricate molecular heterogeneity of CRC continues to hinder biomarker-guided treatment stratification and precision oncology approaches [2]. Among the established molecular biomarkers in CRC, microsatellite instability (MSI) has emerged as a critical determinant of prognosis and therapeutic r…
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CT-based habitat radiomics for differentiating papillary thyroid carcinoma from nodular goiter: a two-center study
To develop habitat-based radiomics signatures for distinguishing papillary thyroid carcinoma (PTC) from nodular goiter (NG).
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Diagnostic Imaging's Weekly Scan: October 5 — October 11
Catch up on the top radiology content of the past week.