AIMC Topic: Retrospective Studies

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Deep learning-based post hoc denoising for 3D volume-rendered cardiac CT in mitral valve prolapse.

The international journal of cardiovascular imaging
We hypothesized that deep learning-based post hoc denoising could improve the quality of cardiac CT for the 3D volume-rendered (VR) imaging of mitral valve (MV) prolapse. We aimed to evaluate the quality of denoised 3D VR images for visualizing MV pr...

Using deep learning generated CBCT contours for online dose assessment of prostate SABR treatments.

Journal of applied clinical medical physics
Prostate Stereotactic Ablative Body Radiotherapy (SABR) is an ultra-hypofractionated treatment where small setup errors can lead to higher doses to organs at risk (OARs). Although bowel and bladder preparation protocols reduce inter-fraction variabil...

Elucidating predictors of preoperative acute heart failure in older people with hip fractures through machine learning and SHAP analysis: a retrospective cohort study.

BMC geriatrics
BACKGROUND: Acute heart failure (AHF) has become a significant challenge in older people with hip fractures. Timely identification and assessment of preoperative AHF have become key factors in reducing surgical risks and improving outcomes.

Association of acute kidney injury with 1-year mortality in granulomatosis with polyangiitis patients: a cohort study using mediation analyses and machine learning.

Rheumatology international
To investigate the correlation between acute kidney injury (AKI) and 1-year mortality in patients with granulomatosis with polyangiitis (GPA). Clinical data for GPA patients were extracted from the MIMIC-IV (version 3.0) database. Logistic and Cox re...

Machine learning technique-based four-autoantibody test for early detection of esophageal squamous cell carcinoma: a multicenter, retrospective study with a nested case-control study.

BMC medicine
BACKGROUND: Autoantibodies represent promising diagnostic blood-based biomarkers that may be generated prior to the first clinically detectable signs of cancers. In present study, we aimed to identify a novel optimized autoantibody panel with high di...

Constructing a neural network model based on tumor-infiltrating lymphocytes (TILs) to predict the survival of hepatocellular carcinoma patients.

PeerJ
BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide, and early pathological diagnosis is crucial for formulating treatment plans. Despite the widespread attention to pathology in the treatment of HCC patients,...

Prostate Cancer Risk Stratification and Scan Tailoring Using Deep Learning on Abbreviated Prostate MRI.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: MRI plays a critical role in prostate cancer (PCa) detection and management. Bi-parametric MRI (bpMRI) offers a faster, contrast-free alternative to multi-parametric MRI (mpMRI). Routine use of mpMRI for all patients may not be necessary,...

Radiomics-based analysis of choroid plexus abnormalities in neuromyelitis optica spectrum disorders and multiple sclerosis and their clinical implications.

Multiple sclerosis and related disorders
BACKGROUND: The choroid plexus (CP) is closely linked to inflammation in multiple sclerosis (MS). While the CP volume is enlarged in MS compared with healthy controls (HC), no such changes are observed in neuromyelitis optica spectrum disorder (NMOSD...

Improved radiological diagnosis of osteoporotic vertebral fragility fractures following UK-wide interventions and re-audit-can this be maintained and translated into clinical practice?

Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA
UNLABELLED: To determine the potential economic, morbidity and mortality impact of improvements in reporting of vertebral fragility fractures (VFFs) following a complete audit cycle. Six percent interval increase in reporting of moderate/severe VFFs ...