[HTML][HTML] Artificial intelligence in detection, management, and prognosis of bone metastasis: a systematic review

GF Papalia, P Brigato, L Sisca, G Maltese, E Faiella… - Cancers, 2024 - mdpi.com
Simple Summary Bone metastases represent a serious and common challenge in advanced
cancer patients, making early detection crucial. The growing implementation of artificial …

Application of artificial intelligence technology in the field of orthopedics: a narrative review

P Liu, J Zhang, S Liu, T Huo, J He, M Xue… - Artificial Intelligence …, 2024 - Springer
Artificial intelligence (AI) was a new interdiscipline of computer technology, mathematic,
cybernetics and determinism. These years, AI had obtained a significant development by the …

The efficacy of machine learning models in lung cancer risk prediction with explainability

RK Pathan, IJ Shorna, MS Hossain, MU Khandaker… - Plos one, 2024 - journals.plos.org
Among many types of cancers, to date, lung cancer remains one of the deadliest cancers
around the world. Many researchers, scientists, doctors, and people from other fields …

Systematic comparison of semi-supervised and self-supervised learning for medical image classification

Z Huang, R Jiang, S Aeron… - Proceedings of the …, 2024 - openaccess.thecvf.com
In typical medical image classification problems labeled data is scarce while unlabeled data
is more available. Semi-supervised learning and self-supervised learning are two different …

[HTML][HTML] Oncologic applications of artificial intelligence and deep learning methods in CT spine imaging—a systematic review

W Ong, A Lee, WC Tan, KTD Fong, DD Lai, YL Tan… - Cancers, 2024 - mdpi.com
Simple Summary In recent years, advances in deep learning have transformed the analysis
of medical imaging, especially in spine oncology. Computed Tomography (CT) imaging is …

[HTML][HTML] Accuracy of artificial intelligence in detecting tumor bone metastases: a systematic review and meta-analysis

H Tao, X Hui, Z Zhang, R Zhu, P Wang, S Zhou… - BMC …, 2025 - pmc.ncbi.nlm.nih.gov
Background Bone metastases (BM) represent a prevalent complication of tumors. Early and
accurate diagnosis, however, is a significant hurdle for radiologists. Recently, artificial …

Diffusion equation quantification: selective enhancement algorithm for bone metastasis lesions in CT images

Y Anetai, K Doi, H Takegawa, Y Koike… - Physics in Medicine …, 2024 - iopscience.iop.org
Objective. Diffusion equation (DE) imaging processing is promising to enhance images
showing lesions of bone metastasis (LBM). The Perona–Malik diffusion (PMD) model, which …

Deep learning image segmentation approaches for malignant bone lesions: a systematic review and meta-analysis

JM Rich, LN Bhardwaj, A Shah, K Gangal… - Frontiers in …, 2023 - frontiersin.org
Introduction Image segmentation is an important process for quantifying characteristics of
malignant bone lesions, but this task is challenging and laborious for radiologists. Deep …

[HTML][HTML] Reducing the workload of medical diagnosis through artificial intelligence: A narrative review

J Jeong, S Kim, L Pan, D Hwang, D Kim, J Choi… - Medicine, 2025 - journals.lww.com
Artificial intelligence (AI) has revolutionized medical diagnostics by enhancing efficiency,
improving accuracy, and reducing variability. By alleviating the workload of medical staff, AI …

Artificial Intelligence in Bone Metastasis Analysis: Current Advancements, Opportunities and Challenges

M Afnouch, F Bougourzi, O Gaddour… - arxiv preprint arxiv …, 2024 - arxiv.org
In recent years, Artificial Intelligence (AI) has been widely used in medicine, particularly in
the analysis of medical imaging, which has been driven by advances in computer vision and …