ArticleSensors (Basel, Switzerland)2022
IoMT-Based Osteosarcoma Cancer Detection in Histopathology Images Using Transfer Learning Empowered with Blockchain, Fog Computing, and Edge Computing.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.
- The diagnostic value of machine learning for the classification of malignant bone tumor: a systematic evaluation and meta-analysis.Frontiers in oncology · 2023Pooled it
- Impact of quantization on various CNN architectures for bone fracture detection.Frontiers in medical technology · 2026Article
- Automated bone marrow cell classification using ensemble learning: performance, generalization, and clinical interpretability.Frontiers in medicine · 2026Article
- Cutting-edge optimized multi-source data fusion for trusted execution and management of blockchain transactions on the internet of medical things (IoMT) with machine learning.Scientific reports · 2025Article
- Enhancing bone cancer detection through optimized pre trained deep learning models and explainable AI using the osteosarcoma tumor assessment dataset.Scientific reports · 2025Article
- Privacy preserving skin cancer diagnosis through federated deep learning and explainable AI.Scientific reports · 2025Article
- Smart IoT with the hybrid evolutionary method and image processing for tumor detection.Scientific reports · 2025Article
- Improved leukocyte classification in bone marrow cytology using convolutional neural network with contrast enhancement.Scientific reports · 2025Article
- A fine-tuned convolutional neural network model for accurate Alzheimer's disease classification.Scientific reports · 2025Article
- Explainable label guided lightweight network with axial transformer encoder for early detection of oral cancer.Scientific reports · 2025Article
- Emerging Trends and Challenges of IoT in Smart Healthcare Systems, Smart Cities and Education.Sensors (Basel, Switzerland) · 2024Article
- Assessing Acetabular Index Angle in Infants: A Deep Learning-Based Novel Approach.Journal of imaging · 2023Article
- Design of a Honey Badger Optimization Algorithm with a Deep Transfer Learning-Based Osteosarcoma Classification Model.Cancers · 2022Article
- Network Meddling Detection Using Machine Learning Empowered with Blockchain Technology.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
6 authors at 3 institutions in 3 countries.
Funding
Abstract
Bone tumors, such as osteosarcomas, can occur anywhere in the bones, though they usually occur in the extremities of long bones near metaphyseal growth plates. Osteosarcoma is a malignant lesion caused by a malignant osteoid growing from primitive mesenchymal cells. In most cases, osteosarcoma develops as a solitary lesion within the most rapidly growing areas of the long bones in children. The distal femur, proximal tibia, and proximal humerus are the most frequently affected bones, but virtually any bone can be affected. Early detection can reduce mortality rates. Osteosarcoma's manual detection requires expertise, and it can be tedious. With the assistance of modern technology, medical images can now be analyzed and classified automatically, which enables faster and more efficient data processing. A deep learning-based automatic detection system based on whole slide images (WSIs) is presented in this paper to detect osteosarcoma automatically. Experiments conducted on a large dataset of WSIs yielded up to 99.3% accuracy. This model ensures the privacy and integrity of patient information with the implementation of blockchain technology. Utilizing edge computing and fog computing technologies, the model reduces the load on centralized servers and improves efficiency.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.