AIMC Topic: Female

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Artificial Intelligence for Breast Cancer Risk Assessment.

Radiologic clinics of North America
Breast cancer risk prediction models based on common clinical risk factors are used to identify women eligible for high-risk screening and prevention. Unfortunately, these models have only modest discriminatory accuracy with disparities in performanc...

Proteomics landscape and machine learning prediction of long-term response to splenectomy in primary immune thrombocytopenia.

British journal of haematology
This study aimed to identify key proteomic analytes correlated with response to splenectomy in primary immune thrombocytopenia (ITP). Thirty-four patients were retrospectively collected in the training cohort and 26 were prospectively enrolled as val...

Deep learning-based image reconstruction for the multi-arterial phase images: improvement of the image quality to assess the small hypervascular hepatic tumor on gadoxetic acid-enhanced liver MRI.

Abdominal radiology (New York)
PURPOSE: To evaluated the impact of a deep learning (DL)-based image reconstruction on multi-arterial-phase magnetic resonance imaging (MA-MRI) for small hypervascular hepatic masses in patients who underwent gadoxetic acid-enhanced liver MRI.

Abnormal Brachial Plexus Differentiation from Routine Magnetic Resonance Imaging: An AI-based Approach.

Neuroscience
Automatic abnormality identification of brachial plexus (BP) from normal magnetic resonance imaging to localize and identify a neurologic injury in clinical practice (MRI) is still a novel topic in brachial plexopathy. This study developed and evalua...

The features associated with mammography-occult MRI-detected newly diagnosed breast cancer analysed by comparing machine learning models with a logistic regression model.

La Radiologia medica
PURPOSE: To compare machine learning (ML) models with logistic regression model in order to identify the optimal factors associated with mammography-occult (i.e. false-negative mammographic findings) magnetic resonance imaging (MRI)-detected newly di...

Dental age estimation: A comparative study of convolutional neural network and Demirjian's method.

Journal of forensic and legal medicine
The aim of this study is to compare a technique using Convolutional Neural Network (CNN) with the Demirjian's method for chronological age estimation of living individuals based on tooth age from panoramic radiographs. This research used 5898 panoram...

Cardiac Tamponade Caused By Carbon Dioxide Insufflation During Robot-Assisted Thoracic Surgery: A Case Report.

A&A practice
Various complications can occur during robot-assisted thoracic surgery for mediastinal tumors owing to carbon dioxide (CO2) insufflation. This study reports the case of a 43-year-old woman who underwent robot-assisted surgery for an anterior mediasti...

Multiparametric MRI-Based Interpretable Radiomics Machine Learning Model Differentiates Medulloblastoma and Ependymoma in Children: A Two-Center Study.

Academic radiology
RATIONALE AND OBJECTIVES: Medulloblastoma (MB) and Ependymoma (EM) in children, share similarities in age group, tumor location, and clinical presentation. Distinguishing between them through clinical diagnosis is challenging. This study aims to expl...

Diagnosing schizophrenia using deep learning: Novel interpretation approaches and multi-site validation.

Brain research
Schizophrenia is a profound and enduring mental disorder that imposes significant negative impacts on individuals, their families, and society at large. The development of more accurate and objective diagnostic tools for schizophrenia can be expedite...