AIMC Topic: Retrospective Studies

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Prognostic role of computed tomography analysis using deep learning algorithm in patients with chronic hepatitis B viral infection.

Clinical and molecular hepatology
BACKGROUND/AIMS: The prediction of clinical outcomes in patients with chronic hepatitis B (CHB) is paramount for effective management. This study aimed to evaluate the prognostic value of computed tomography (CT) analysis using deep learning algorith...

An Artificial Intelligence Model for Predicting Trauma Mortality Among Emergency Department Patients in South Korea: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Within the trauma system, the emergency department (ED) is the hospital's first contact and is vital for allocating medical resources. However, there is generally limited information about patients that die in the ED.

Geometric evaluations of CT and MRI based deep learning segmentation for brain OARs in radiotherapy.

Physics in medicine and biology
Deep-learning auto-contouring (DL-AC) promises standardisation of organ-at-risk (OAR) contouring, enhancing quality and improving efficiency in radiotherapy. No commercial models exist for OAR contouring based on brain magnetic resonance imaging (MRI...

Criticality and clinical department prediction of ED patients using machine learning based on heterogeneous medical data.

Computers in biology and medicine
PROBLEM: Emergency triage faces multiple challenges, including limited medical resources and inadequate manual triage nurses, which cause incorrect triage, overcrowding in the emergency department (ED), and long patient waiting time.

Deep Learning Radiomics Nomogram Based on Magnetic Resonance Imaging for Differentiating Type I/II Epithelial Ovarian Cancer.

Academic radiology
RATIONALE AND OBJECTIVES: To develop and validate a T2-weighted magnetic resonance imaging (MRI)-based deep learning radiomics nomogram (DLRN) to differentiate between type I and type II epithelial ovarian cancer (EOC).

Predicting Lymph Node Metastasis From Primary Cervical Squamous Cell Carcinoma Based on Deep Learning in Histopathologic Images.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
We developed a deep learning framework to accurately predict the lymph node status of patients with cervical cancer based on hematoxylin and eosin-stained pathological sections of the primary tumor. In total, 1524 hematoxylin and eosin-stained whole ...

Efficacy and safety of robot-assisted versus fluoroscopy-assisted PKP or PVP for osteoporotic vertebral compression fractures: a systematic review and meta-analysis.

Journal of robotic surgery
Percutaneous vertebral augmentation (PVA), which includes percutaneous kyphoplasty (PKP) and percutaneous vertebroplasty (PVP). Robot-assisted (RA) and fluoroscopy-assisted (FA) are important methods for treating osteoporotic vertebral compression fr...

Application of machine learning (individual vs stacking) models on MERRA-2 data to predict surface PM concentrations over India.

Chemosphere
The spatial coverage of PM monitoring is non-uniform across India due to the limited number of ground monitoring stations. Alternatively, Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA-2), is an atmospheric reanalys...