AIMC Topic: Sarcoma

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Treatment-related features improve machine learning prediction of prognosis in soft tissue sarcoma patients.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
BACKGROUND AND PURPOSE: Current prognostic models for soft tissue sarcoma (STS) patients are solely based on staging information. Treatment-related data have not been included to date. Including such information, however, could help to improve these ...

Acute gastrointestinal toxicity and bowel bag dose-volume parameters for preoperative radiation therapy for retroperitoneal sarcoma.

Practical radiation oncology
PURPOSE: Acute gastrointestinal (GI) toxicity has been studied in GI and gynecological (GYN) cancers, with volume receiving 15 Gy (V15) <830 mL, V25 <650 mL, and V45 <195 mL identified as dose constraints for the peritoneal space (bowel bag [BB]). Th...

Machine learning based diagnostics of veterinary cancer on ultrasound and optical imaging data.

The veterinary quarterly
Study advances current diagnostic efficiency of canine/feline (sub-)cutaneous tumors using machine learning and multimodal imaging data. White light (WL), fluorescence (FL) and ultrasound (US) imaging were combined into hybrid approaches to different...

Differentiation of canine and feline neoplasms using multi-modal imaging and machine learning.

Scientific reports
Canine/feline (sub-)cutaneous tumors, which include lipomas, mastocytomas and soft tissue sarcomas, introduce diagnostic challenges due to inherent tissue heterogeneity, accompanied by diverse clinical pathogenesis. Current study integrates conventio...

Prediction of prognosis using artificial intelligence-based histopathological image analysis in patients with soft tissue sarcomas.

Cancer medicine
BACKGROUND: Prompt histopathological diagnosis with accuracy is required for soft tissue sarcomas (STSs) which are still challenging. In addition, the advances in artificial intelligence (AI) along with the development of pathology slides digitizatio...

MRI-Based Deep Learning Segmentation and Radiomics of Sarcoma in Mice.

Tomography (Ann Arbor, Mich.)
Small-animal imaging is an essential tool that provides noninvasive, longitudinal insight into novel cancer therapies. However, considerable variability in image analysis techniques can lead to inconsistent results. We have developed quantitative ima...

Deep multi-modality collaborative learning for distant metastases predication in PET-CT soft-tissue sarcoma studies.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Soft-tissue Sarcomas (STS) are a heterogeneous group of malignant neoplasms with a relatively high mortality rate from distant metastases. Early prediction or quantitative evaluation of distant metastases risk for patients with STS is an important st...