AIMC Topic: Neoplasm Recurrence, Local

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Multitask deep learning model based on multimodal data for predicting prognosis of rectal cancer: a multicenter retrospective study.

BMC medical informatics and decision making
BACKGROUND: Prognostic prediction is crucial to guide individual treatment for patients with rectal cancer. We aimed to develop and validated a multitask deep learning model for predicting prognosis in rectal cancer patients.

Machine learning-based integration develops relapse related signature for predicting prognosis and indicating immune microenvironment infiltration in breast cancer.

Scientific reports
Breast cancer is the most common type of cancer in women, and while current treatments can cure the majority of early-stage primary BC cases, recurrence remains a significant challenge. Traditional methods of assessing patient prognosis, such as AJCC...

Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.

Scientific reports
Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcomes. Our study aimed to assess the predictive risk factors for UR, to develop and validate an easy-to-...

Deep learning for predicting invasive recurrence of ductal carcinoma in situ: leveraging histopathology images and clinical features.

EBioMedicine
BACKGROUND: Ductal Carcinoma In Situ (DCIS) can progress to ipsilateral invasive breast cancer (IBC) but over 75% of DCIS lesions do not progress if untreated. Currently, DCIS that might progress to IBC cannot reliably be identified. Therefore, most ...

Machine learning approaches reveal methylation signatures associated with pediatric acute myeloid leukemia recurrence.

Scientific reports
Acute myeloid leukemia (AML) is a severe hematological malignancy characterized by high recurrence rates, especially in pediatric patients, highlighting the need for reliable prognostic markers. This study proposes methylation signatures associated w...

Training, Validating, and Testing Machine Learning Prediction Models for Endometrial Cancer Recurrence.

JCO precision oncology
PURPOSE: Endometrial cancer (EC) is the most common gynecologic cancer in the United States with rising incidence and mortality. Despite optimal treatment, 15%-20% of all patients will recur. To better select patients for adjuvant therapy, it is impo...

Reirradiation for recurrent glioblastoma: the significance of the residual tumor volume.

Journal of neuro-oncology
PURPOSE: Recurrent glioblastoma has a poor prognosis, and its optimal management remains unclear. Reirradiation (re-RT) is a promising treatment option, but long-term outcomes and optimal patient selection criteria are not well established.

Predicting Recurrence After Surgical Resection for High-Risk Localized Renal Cell Carcinoma: A Radiomics Clinical Integration Approach.

The Journal of urology
PURPOSE: Adjuvant immunotherapy for clear cell renal cell carcinoma (ccRCC) is controversial because of the absence of reliable biomarkers for identifying patients most likely to benefit. The aim of this study was to develop and validate a quantitati...

Prediction of early recurrence in primary central nervous system lymphoma based on multimodal MRI-based radiomics: A preliminary study.

European journal of radiology
OBJECTIVES: To evaluate the role of multimodal magnetic resonance imaging radiomics features in predicting early recurrence of primary central nervous system lymphoma (PCNSL) and to investigate their correlation with patient prognosis.

Decoding Recurrence in Early-Stage and Locoregionally Advanced Non-Small Cell Lung Cancer: Insights From Electronic Health Records and Natural Language Processing.

JCO clinical cancer informatics
PURPOSE: Recurrences after curative resection in early-stage and locoregionally advanced non-small cell lung cancer (NSCLC) are common, necessitating a nuanced understanding of associated risk factors. This study aimed to establish a natural language...