AIMC Topic: Neoplasm Recurrence, Local

Clear Filters Showing 291 to 300 of 456 articles

Distillation of the clinical algorithm improves prognosis by multi-task deep learning in high-risk Neuroblastoma.

PloS one
We introduce the CDRP (Concatenated Diagnostic-Relapse Prognostic) architecture for multi-task deep learning that incorporates a clinical algorithm, e.g., a risk stratification schema to improve prognostic profiling. We present the first application ...

Deep learning provides a new computed tomography-based prognostic biomarker for recurrence prediction in high-grade serous ovarian cancer.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
BACKGROUND AND PURPOSE: Recurrence is the main risk for high-grade serous ovarian cancer (HGSOC) and few prognostic biomarkers were reported. In this study, we proposed a novel deep learning (DL) method to extract prognostic biomarkers from preoperat...

The usefulness of fine-needle aspirates for detection of recurrent carcinoma in the thyroid bed.

Journal of the American Society of Cytopathology
INTRODUCTION: Locoregional recurrence of thyroid carcinoma has a negative impact on patient prognosis. In the current study, we retrospectively reviewed cases of thyroid bed lesions in the last 3 years, correlating cytologic diagnoses with clinical f...

Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Oncotype Dx is a validated genetic analysis that provides a recurrence score (RS) to quantitatively predict outcomes in patients who meet the criteria of estrogen receptor positive / human epidermal growth factor receptor-2 negative (ER+/...

Establishment of a SVM classifier to predict recurrence of ovarian cancer.

Molecular medicine reports
Gene expression data using retrieved ovarian cancer (OC) samples were used to identify genes of interest and a support vector machine (SVM) classifier was subsequently established to predict the recurrence of OC. Three datasets (GSE17260, GSE44104 an...

Information-Based Medicine in Glioma Patients: A Clinical Perspective.

Computational and mathematical methods in medicine
Glioma constitutes the most common type of primary brain tumor with a dismal survival, often measured in terms of months or years. The thin line between treatment effectiveness and patient harm underpins the importance of tailoring clinical managemen...

Robotic Cystectomy-Moving from Innovation to Measurable Impact.

European urology
Data from an experienced center that randomized patients to open vs robotic cystectomy for urothelial cancer demonstrated locational differences in recurrence. While the study was not powered to detect survival differences, overall, cancer-specific, ...

High-Grade Serous Ovarian Cancer: Use of Machine Learning to Predict Abdominopelvic Recurrence on CT on the Basis of Serial Cancer Antigen 125 Levels.

Journal of the American College of Radiology : JACR
PURPOSE: The aim of this study was to use machine learning to predict abdominal recurrence on CT on the basis of serial cancer antigen 125 (CA125) levels in patients with advanced high-grade serous ovarian cancer on surveillance.

Artificial intelligence weights the importance of factors predicting complete cytoreduction at secondary cytoreductive surgery for recurrent ovarian cancer.

Journal of gynecologic oncology
OBJECTIVE: Accumulating evidence support that complete cytoreduction (CC) at the time of secondary cytoreductive surgery (SCS) improves survival in patients affected by recurrent ovarian cancer (ROC). Here, we aimed to determine whether artificial in...

A study of association of Oncotype DX recurrence score with DCE-MRI characteristics using multivariate machine learning models.

Journal of cancer research and clinical oncology
PURPOSE: To determine whether multivariate machine learning models of algorithmically assessed magnetic resonance imaging (MRI) features from breast cancer patients are associated with Oncotype DX (ODX) test recurrence scores.