Automated machine learning with interpretation: A systematic review of methodologies and applications in healthcare

H Yuan, K Yu, F Xie, M Liu, S Sun - Medicine Advances, 2024 - Wiley Online Library
Abstract Machine learning (ML) has achieved substantial success in performing healthcare
tasks in which the configuration of every part of the ML pipeline relies heavily on technical …

Research Progress of Artificial Intelligence in the Grading and Classification of Meningiomas

Y Gui, J Zhang - Academic Radiology, 2024 - Elsevier
A meningioma is a common primary central nervous system tumor. The histological features
of meningiomas vary significantly depending on the grade and subtype, leading to …

[HTML][HTML] Automated segmentation of meningioma from contrast-enhanced T1-weighted MRI images in a case series using a marker-controlled watershed …

S Mohammadi, S Ghaderi, K Ghaderi… - International Journal of …, 2023 - Elsevier
Introduction and importance Accurate segmentation of meningiomas from contrast-
enhanced T1-weighted (CE T1-w) magnetic resonance imaging (MRI) is crucial for …

Two-Stage Segmentation and Ensemble Modeling: Kidney Tumor Analysis in CT Images

S Lee, H Won, Y Lee - International Challenge on Kidney and Kidney …, 2023 - Springer
In the realm of kidney cancer, accurate segmentation is pivotal for effective diagnosis and
treatment. Participating in the 2023 KiTS Challenge as a platform, our research introduces a …

M3F: Multi-Field-of-View Feature Fusion Network for Aortic Vessel Tree Segmentation in CT Angiography

Y Byeon, H Kim, K Kim, D Park, E Choi… - MICCAI Challenge on …, 2023 - Springer
Accurate segmentation of the aortic vessel tree (AVT) in computed tomography angiography
(CTA) is crucial for diagnosing and monitoring vascular conditions. However, achieving …

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J Lee¹, JS Yoon - … , Smart Ageing, and Managing Disability: 20th …, 2023 - books.google.com
This study aimed to quantitatively analyze pressure parameters in different high-risk areas
depending on the position. We reviewed the clinical records of trials of 20 healthy adults on …

DL-Modell zur auto-matischen Segmentierung und Klassifizierung von Meningeomen

Y Jun - thieme-connect.com
Die Mehrheit (80%) der intrakraniellen Meningeome entsprechen der WHO-Klassifikation
Grad 1 und sind gutartig, die aggressiven mit WHO-Grad 2 und 3 rezidivieren und haben …