AIMC Topic: Retrospective Studies
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A deep learning-based computed tomography reading system for the diagnosis of lung cancer associated with cystic airspaces.
Scientific reports
Jul 2, 2025
To propose a deep learning model and explore its performance in the auxiliary diagnosis of lung cancer associated with cystic airspaces (LCCA) in computed tomography (CT) images. This study is a retrospective analysis that incorporated a total of 342...
Cervical cancer prediction using machine learning models based on routine blood analysis.
Scientific reports
Jul 2, 2025
Cervical cancer (CC) is the fourth most common cancer among women globally. The key to preventing and treating CC is early detection, diagnosis, and treatment. This study aimed to develop an interpretable model for predicting CC risk using routine bl...
Machine learning model and hemoglobin to red cell distribution width ratio evaluates all-cause mortality in pulmonary embolism.
Scientific reports
Jul 2, 2025
The ratio of hemoglobin (Hb) to red blood cell distribution width (RDW), known as HRR, functions as an innovative indicator related to prognosis. However, whether HRR can predict the mortality for pulmonary embolism (PE) patients remains ambiguous. A...
The construction of HMME-PDT efficacy prediction model for port-wine stain based on machine learning algorithms.
Scientific reports
Jul 2, 2025
Hematoporphyrin monomethyl ether-photodynamic therapy (HMME-PDT) is a safe and effective treatment for port-wine stain (PWS). Comprehensive methods for predicting HMME-PDT efficacy based on clinical factors are lacking. This study aims to develop and...
Comparative study of five-year cervical cancer cause-specific survival prediction models based on SEER data.
Scientific reports
Jul 2, 2025
Cervical cancer (CC) is a major cause of mortality in women, with stagnant survival rates, highlighting the need for improved prognostic models. This study aims to develop and compare machine learning models for predicting five-year cause-specific su...
Development and validation of a transformer model-based early warning score for real-time prediction of adverse outcomes in the emergency department.
Scientific reports
Jul 2, 2025
This study aimed to develop and validate a transformer-based early warning score (TEWS) system for predicting adverse events (AEs) in the emergency department (ED). We conducted a retrospective study analyzing adult ED visits at a tertiary hospital. ...
Automated grading of rectocele with an MRI radiomics model.
Scientific reports
Jul 2, 2025
To develop an automated grading model for rectocele (RC) based on radiomics and evaluate its efficacy. This study retrospectively analyzed a total of 9,392 magnetic resonance imaging (MRI) images obtained from 222 patients who underwent dynamic magne...
Can mutation abundance assess the biological behavior of BRAF-positive papillary thyroid carcinoma?
Journal of translational medicine
Jul 1, 2025
BACKGROUND: BRAF mutation is the most common genetic change in papillary thyroid carcinoma (PTC). Nevertheless, the association between BRAF mutation status and abundance and the biological behavior of PTC is unclear. Thus, this study investigated wh...
Preoperative MRI-based deep learning reconstruction and classification model for assessing rectal cancer.
BMC medical imaging
Jul 1, 2025
BACKGROUND: To determine whether deep learning reconstruction (DLR) could improve the image quality of rectal MR images, and to explore the discrimination of the TN stage of rectal cancer by different readers and deep learning classification models, ...
Male
Image Interpretation, Computer-Assisted
Middle Aged
Image Processing, Computer-Assisted
Humans
Deep Learning
Female
Signal-To-Noise Ratio
Magnetic Resonance Imaging
Retrospective Studies
Aged
ROC Curve
Diffusion Magnetic Resonance Imaging
Neoplasm Staging
Aged, 80 and over
Rectal Neoplasms
Adult
Machine learning-based prediction model for arteriovenous fistula thrombosis risk: a retrospective cohort study from 2017 to 2024.
BMC nephrology
Jul 1, 2025
BACKGROUND: Thrombosis of arteriovenous fistulas represents a prevalent complication among patients undergoing hemodialysis, characterized by a notably high incidence rate. Presently, there is an absence of robust assessment tools capable of predicti...
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