AIMC Topic: Neoplasm Recurrence, Local

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Multimodal prediction of metastatic relapse using federated deep learning in soft-tissue sarcoma with a complex genomic profile.

Scientific reports
Soft Tissue sarcomas (STS) are a group of heterogeneous and complex diseases where being able to predict the appearance of metastases is key to inform clinical decisions, especially the prescription of adjuvant chemotherapy. We developed SarcNet: a m...

Multimodal deep learning model for prediction of breast cancer recurrence risk and correlation with oncotype DX.

Breast cancer research : BCR
BACKGROUND: Proper stratification of recurrence risk in breast cancer is crucial for guiding treatment decisions. This study aims to predict the recurrence risk of breast cancer patients using a multimodal deep learning model that integrates multiple...

Predicting outcomes in head and neck cancer using CT images via transfer learning.

BMC medical imaging
BACKGROUND: Accurate preoperative risk stratification for patients with head and neck (H&N) cancer remained a critical challenge, as long-term survival rates are poor despite aggressive multimodality treatment. While deep learning models showed promi...

Assessing the risk of recurrence in early-stage breast cancer through H&E stained whole slide images.

Scientific reports
Accurate prediction of the likelihood of recurrence is important in the selection of postoperative treatment for patients with early-stage breast cancer. In this study, we investigated whether deep learning algorithms can predict patients' risk of re...

Artificial intelligence for the prediction of posthepatectomy recurrence in hepatocellular carcinoma: a systematic review and meta-analysis.

Annals of medicine
OBJECTIVE: Posthepatectomy recurrence of hepatocellular carcinoma (HCC) is a major cause of poor prognosis. Accurate prediction is essential for reducing the burden of advanced disease and improving outcomes.

Machine learning-based prediction of post-operative outcomes in robotic-assisted radical prostatectomy: a multi-variable analysis of 758 cases.

Journal of robotic surgery
Robotic-assisted radical prostatectomy (RARP) has become the gold standard treatment for localized prostate cancer. However, predicting post-operative outcomes remains challenging. This study aims to develop and validate predictive models for key out...

Diagnostic Performance of Computed Tomography-Based Artificial Intelligence for Early Recurrence of Cholangiocarcinoma: Systematic Review and Meta-Analysis.

Journal of medical Internet research
BACKGROUND: Despite artificial intelligence (AI) models demonstrating high predictive accuracy for early cholangiocarcinoma recurrence, their clinical application faces challenges, such as reproducibility, generalizability, hidden biases, and uncerta...

Development of a prostate cancer biochemical recurrence risk signature using machine learning and motor protein-related genes.

PloS one
BACKGROUND: Motor proteins play significant roles in cancer progression, but their involvement in biochemical recurrence (BCR) of prostate cancer remains unclear. The objective of the study is to develop a prognostic indicator for BCR using machine l...