AIMC Topic: Sarcoma
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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),...
Optimizing imaging modalities for sarcoma subtypes in radiation therapy: State of the art.
Critical reviews in oncology/hematology
Mar 24, 2025
The choice of imaging modalities is essential in sarcoma management, as different techniques provide complementary information depending on tumor subtype and anatomical location. This narrative review examines the role of imaging in sarcoma character...
Identification of novel diagnostic and prognostic microRNAs in sarcoma on TCGA dataset: bioinformatics and machine learning approach.
Scientific reports
Mar 4, 2025
The discovery of unique microRNA (miR) patterns and their corresponding genes in sarcoma patients indicates their involvement in cancer development and suggests their potential use in medical management. MiRs were identified from The Cancer Genome At...
Predicting progression-free survival in sarcoma using MRI-based automatic segmentation models and radiomics nomograms: a preliminary multicenter study.
Skeletal radiology
Dec 4, 2024
OBJECTIVES: Some sarcomas are highly malignant, associated with high recurrence despite treatment. This multicenter study aimed to develop and validate a radiomics signature to estimate sarcoma progression-free survival (PFS).
Assessment of Artificial Intelligence Chatbot Responses to Common Patient Questions on Bone Sarcoma.
Journal of surgical oncology
Oct 29, 2024
BACKGROUND AND OBJECTIVES: The potential impacts of artificial intelligence (AI) chatbots on care for patients with bone sarcoma is poorly understood. Elucidating potential risks and benefits would allow surgeons to define appropriate roles for these...
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...
Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas.
Cancer research and treatment
Jul 10, 2024
PURPOSE: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
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.
Multimodal Brain Tumor Classification Using Convolutional Tumnet Architecture.
Behavioural neurology
May 30, 2024
The most common and aggressive tumor is brain malignancy, which has a short life span in the fourth grade of the disease. As a result, the medical plan may be a crucial step toward improving the well-being of a patient. Both diagnosis and therapy are...
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