[HTML][HTML] Explainable artificial intelligence (XAI) in deep learning-based medical image analysis
With an increase in deep learning-based methods, the call for explainability of such methods
grows, especially in high-stakes decision making areas such as medical image analysis …
grows, especially in high-stakes decision making areas such as medical image analysis …
External validation of deep learning algorithms for radiologic diagnosis: a systematic review
Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
Multi-task deep learning for medical image computing and analysis: A review
The renaissance of deep learning has provided promising solutions to various tasks. While
conventional deep learning models are constructed for a single specific task, multi-task deep …
conventional deep learning models are constructed for a single specific task, multi-task deep …
Toward generalizability in the deployment of artificial intelligence in radiology: role of computation stress testing to overcome underspecification
T Eche, LH Schwartz, FZ Mokrane… - Radiology: Artificial …, 2021 - pubs.rsna.org
The clinical deployment of artificial intelligence (AI) applications in medical imaging is
perhaps the greatest challenge facing radiology in the next decade. One of the main …
perhaps the greatest challenge facing radiology in the next decade. One of the main …
Multitask deep learning for segmentation and classification of primary bone tumors on radiographs
CE von Schacky, NJ Wilhelm, VS Schäfer, Y Leonhardt… - Radiology, 2021 - pubs.rsna.org
Background An artificial intelligence model that assesses primary bone tumors on
radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep …
radiographs may assist in the diagnostic workflow. Purpose To develop a multitask deep …
A scalable physician-level deep learning algorithm detects universal trauma on pelvic radiographs
Pelvic radiograph (PXR) is essential for detecting proximal femur and pelvis injuries in
trauma patients, which is also the key component for trauma survey. None of the currently …
trauma patients, which is also the key component for trauma survey. None of the currently …
Use of machine learning in osteoarthritis research: a systematic literature review
Objective The aim of this systematic literature review was to provide a comprehensive and
exhaustive overview of the use of machine learning (ML) in the clinical care of osteoarthritis …
exhaustive overview of the use of machine learning (ML) in the clinical care of osteoarthritis …
[HTML][HTML] Studying osteoarthritis with artificial intelligence applied to magnetic resonance imaging
The 3D nature and soft-tissue contrast of MRI makes it an invaluable tool for osteoarthritis
research, by facilitating the elucidation of disease pathogenesis and progression. The recent …
research, by facilitating the elucidation of disease pathogenesis and progression. The recent …
[HTML][HTML] John charnley award: deep learning prediction of hip joint center on standard pelvis radiographs
SJ Jang, KN Kunze, JM Vigdorchik, SA Jerabek… - The Journal of …, 2022 - Elsevier
Background Accurate hip joint center (HJC) determination is critical for preoperative
planning, intraoperative execution, clinical outcomes after total hip arthroplasty, and …
planning, intraoperative execution, clinical outcomes after total hip arthroplasty, and …
Deep learning approach for diagnosing early osteonecrosis of the femoral head based on magnetic resonance imaging
X Shen, J Luo, X Tang, B Chen, Y Qin, Y Zhou… - The Journal of …, 2023 - Elsevier
Background The diagnosis of early osteonecrosis of the femoral head (ONFH) based on
magnetic resonance imaging (MRI) is challenging due to variability in the surgeon's …
magnetic resonance imaging (MRI) is challenging due to variability in the surgeon's …