AIMC Topic: Soft Tissue Neoplasms
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Extremity Soft Tissue Sarcoma Reconstruction Nomograms: A Clinicoradiomic, Machine Learning-Powered Predictor of Postoperative Outcomes.
JCO clinical cancer informatics
Jun 11, 2025
PURPOSE: The choice of wound closure modality after limb-sparing extremity soft-tissue sarcoma (eSTS) resection is fraught with uncertainty. Leveraging machine learning and clinicoradiomic data, we developed Sarcoma Reconstruction Nomograms (SARCON),...
AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines.
EBioMedicine
Mar 20, 2025
BACKGROUND: Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches. This systematic review aims to provide an overview of Artificial Intelligence (AI) methods using ...
Radiomics and Deep Learning Model for Benign and Malignant Soft Tissue Tumors Differentiation of Extremities and Trunk.
Academic radiology
Jan 2, 2025
RATIONALE AND OBJECTIVES: To develop radiomics and deep learning models for differentiating malignant and benign soft tissue tumors (STTs) preoperatively based on fat saturation T2-weighted imaging (FS-T2WI) of patients.
Rhabdomyosarcoma Classification: Refining Our Understanding.
Surgical pathology clinics
Dec 10, 2024
Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children, representing approximately 40% of all pediatric soft tissue sarcomas and 3% of all pediatric cancers. RMSs are a heterogeneous group of neoplasms with variations in morphology...
Ultrasound-based artificial intelligence model for prediction of Ki-67 proliferation index in soft tissue tumors.
Academic radiology
Oct 15, 2024
RATIONALE AND OBJECTIVES: To investigate the value of deep learning (DL) combined with radiomics and clinical and imaging features in predicting the Ki-67 proliferation index of soft tissue tumors (STTs).
De Novo Natural Language Processing Algorithm Accurately Identifies Myxofibrosarcoma From Pathology Reports.
Clinical orthopaedics and related research
Oct 2, 2024
BACKGROUND: Available codes in the ICD-10 do not accurately reflect soft tissue sarcoma diagnoses, and this can result in an underrepresentation of soft tissue sarcoma in databases. The National VA Database provides a unique opportunity for soft tiss...
Diagnostic Value of Magnetic Resonance Imaging Radiomics and Machine-learning in Grading Soft Tissue Sarcoma: A Mini-review on the Current State.
Academic radiology
Sep 10, 2024
Soft tissue sarcomas (STS) are a heterogeneous group of rare malignant tumors. Tumor grade might be underestimated in biopsy due to intratumoral heterogeneity. This mini-review aims to present the current state of predicting malignancy grades of STS ...
Evaluating the Alignment of Artificial Intelligence-Generated Recommendations With Clinical Guidelines Focused on Soft Tissue Tumors.
Journal of surgical oncology
Sep 5, 2024
BACKGROUND: The integration of artificial intelligence (AI), particularly, in oncology, has significantly shifted the paradigms of medical diagnostics and treatment planning. However, the utility of AI, specifically OpenAI's ChatGPT, in soft tissue s...
Parallel CNN-Deep Learning Clinical-Imaging Signature for Assessing Pathologic Grade and Prognosis of Soft Tissue Sarcoma Patients.
Journal of magnetic resonance imaging : JMRI
Jun 10, 2024
BACKGROUND: Traditional biopsies pose risks and may not accurately reflect soft tissue sarcoma (STS) heterogeneity. MRI provides a noninvasive, comprehensive alternative.
Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
May 22, 2024
BACKGROUND: Volume of interest (VOI) segmentation is a crucial step for Radiomics analyses and radiotherapy (RT) treatment planning. Because it can be time-consuming and subject to inter-observer variability, we developed and tested a Deep Learning-b...
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