AIMC Topic: Adult

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Early prediction of ventricular peritoneal shunt dependency in aneurysmal subarachnoid haemorrhage patients by recurrent neural network-based machine learning using routine intensive care unit data.

Journal of clinical monitoring and computing
Aneurysmal subarachnoid haemorrhage (aSAH) can lead to complications such as acute hydrocephalic congestion. Treatment of this acute condition often includes establishing an external ventricular drainage (EVD). However, chronic hydrocephalus develops...

Transcranial Magnetic Stimulation-Based Machine Learning Prediction of Tumor Grading in Motor-Eloquent Gliomas.

Neurosurgery
BACKGROUND: Navigated transcranial magnetic stimulation (nTMS) is a well-established preoperative mapping tool for motor-eloquent glioma surgery. Machine learning (ML) and nTMS may improve clinical outcome prediction and histological correlation.

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...

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...

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...

Survey on Value Elements Provided by Artificial Intelligence and Their Eligibility for Insurance Coverage With an Emphasis on Patient-Centered Outcomes.

Korean journal of radiology
OBJECTIVE: This study aims to explore the opinions on the insurance coverage of artificial intelligence (AI), as categorized based on the distinct value elements offered by AI, with a specific focus on patient-centered outcomes (PCOs). PCOs are disti...