AIMC Topic: Bone Neoplasms
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Bone metastasis scintigram generation using generative adversarial learning with multi-receptive field learning and two-stage training.
Medical physics
Sep 3, 2024
BACKGROUND: Deep learning is the primary method for conducting automated analysis of SPECT bone scintigrams. The lack of available large-scale data significantly hinders the development of well-performing deep learning models, as the performance of a...
High-quality expert annotations enhance artificial intelligence model accuracy for osteosarcoma X-ray diagnosis.
Cancer science
Sep 2, 2024
Primary malignant bone tumors, such as osteosarcoma, significantly affect the pediatric and young adult populations, necessitating early diagnosis for effective treatment. This study developed a high-performance artificial intelligence (AI) model to ...
The Fine-Tuned Large Language Model for Extracting the Progressive Bone Metastasis from Unstructured Radiology Reports.
Journal of imaging informatics in medicine
Aug 26, 2024
Early detection of patients with impending bone metastasis is crucial for prognosis improvement. This study aimed to investigate the feasibility of a fine-tuned, locally run large language model (LLM) in extracting patients with bone metastasis in un...
Development and experimental validation of hypoxia-related gene signatures for osteosarcoma diagnosis and prognosis based on WGCNA and machine learning.
Scientific reports
Aug 12, 2024
Osteosarcoma (OS) is the most common primary malignant tumour of the bone with high mortality. Here, we comprehensively analysed the hypoxia signalling in OS and further constructed novel hypoxia-related gene signatures for OS prediction and prognosi...
Development and validation of an artificial intelligence model for predicting de novo distant bone metastasis in breast cancer: a dual-center study.
BMC women's health
Aug 5, 2024
OBJECTIVE: Breast cancer has become the most prevalent malignant tumor in women, and the occurrence of distant metastasis signifies a poor prognosis. Utilizing predictive models to forecast distant metastasis in breast cancer presents a novel approac...
Prediction of bone invasion of oral squamous cell carcinoma using a magnetic resonance imaging-based machine learning model.
European archives of oto-rhino-laryngology : official journal of the European Federation of Oto-Rhino-Laryngological Societies (EUFOS) : affiliated with the German Society for Oto-Rhino-Laryngology - Head and Neck Surgery
Jul 31, 2024
OBJECTIVES: Radiomics, a recently developed image-processing technology, holds potential in medical diagnostics. This study aimed to propose a machine-learning (ML) model and evaluate its effectiveness in detecting oral squamous cell carcinoma (OSCC)...
Computed tomography-based radiomics machine learning models for differentiating enchondroma and atypical cartilaginous tumor in long bones.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Jul 29, 2024
To explore the value of CT-based radiomics machine learning models for differentiating enchondroma from atypical cartilaginous tumor (ACT) in long bones and methods to improve model performance.59 enchondromas and 53 ACTs in long bones confirmed by p...
Machine learning and experimental analyses identified miRNA expression models associated with metastatic osteosarcoma.
Biochimica et biophysica acta. Molecular basis of disease
Jul 20, 2024
Osteosarcoma (OS), as the most common primary bone cancer, has a high invasiveness and metastatic potential, therefore, it has a poor prognosis. This study identified early diagnostic biomarkers using miRNA expression profiles associated with osteosa...
Radiomics based on multiple machine learning methods for diagnosing early bone metastases not visible on CT images.
Skeletal radiology
Jul 19, 2024
OBJECTIVES: This study utilizes [Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine lea...
Enhanced enchondroma detection from x-ray images using deep learning: A step towards accurate and cost-effective diagnosis.
Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Jul 15, 2024
This study investigates the automated detection of enchondromas, benign cartilage tumors, from x-ray images using deep learning techniques. Enchondromas pose diagnostic challenges due to their potential for malignant transformation and overlapping ra...
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