AIMC Topic: Neoplasm Recurrence, Local
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Multiparametric MRI-Based Deep Learning Radiomics Model for Assessing 5-Year Recurrence Risk in Non-Muscle Invasive Bladder Cancer.
Journal of magnetic resonance imaging : JMRI
Aug 21, 2024
BACKGROUND: Accurately assessing 5-year recurrence rates is crucial for managing non-muscle-invasive bladder carcinoma (NMIBC). However, the European Organization for Research and Treatment of Cancer (EORTC) model exhibits poor performance.
Reproducibility of Results
Risk Factors
Aged
Radiomics
Humans
Retrospective Studies
Female
Urinary Bladder
Multiparametric Magnetic Resonance Imaging
Non-Muscle Invasive Bladder Neoplasms
Magnetic Resonance Imaging
Urinary Bladder Neoplasms
Neoplasm Invasiveness
Neoplasm Recurrence, Local
Male
Middle Aged
Risk Assessment
Deep Learning
Prediction of non-muscle invasive bladder cancer recurrence using deep learning of pathology image.
Scientific reports
Aug 15, 2024
We aimed to build a deep learning-based pathomics model to predict the early recurrence of non-muscle-infiltrating bladder cancer (NMIBC) in this work. A total of 147 patients from Xuzhou Central Hospital were enrolled as the training cohort, and 63 ...
Utilizing deep learning model for assessing melanocytic density in resection margins of lentigo maligna.
Diagnostic pathology
Aug 3, 2024
BACKGROUND: Surgical excision with clear histopathological margins is the preferred treatment to prevent progression of lentigo maligna (LM) to invasive melanoma. However, the assessment of resection margins on sun-damaged skin is challenging. We dev...
Performance assessment of hybrid machine learning approaches for breast cancer and recurrence prediction.
PloS one
Aug 1, 2024
Breast cancer is a major health concern for women everywhere and a major killer of women. Malignant tumors may be distinguished from benign ones, allowing for early diagnosis of this disease. Therefore, doctors need an accurate method of diagnosing t...
AI-powered prediction of HCC recurrence after surgical resection: Personalised intervention opportunities using patient-specific risk factors.
Liver international : official journal of the International Association for the Study of the Liver
Jul 24, 2024
BACKGROUND: Hepatocellular carcinoma (HCC) recurrence following surgical resection remains a significant clinical challenge, necessitating reliable predictive models to guide personalised interventions. In this study, we sought to harness the power o...
Prognosing post-treatment outcomes of head and neck cancer using structured data and machine learning: A systematic review.
PloS one
Jul 24, 2024
BACKGROUND: This systematic review aimed to evaluate the performance of machine learning (ML) models in predicting post-treatment survival and disease progression outcomes, including recurrence and metastasis, in head and neck cancer (HNC) using clin...
Deep learning-based 3D quantitative total tumor burden predicts early recurrence of BCLC A and B HCC after resection.
European radiology
Jul 19, 2024
OBJECTIVES: This study aimed to evaluate the potential of deep learning (DL)-assisted automated three-dimensional quantitative tumor burden at MRI to predict postoperative early recurrence (ER) of hepatocellular carcinoma (HCC).
Novel Artificial Intelligence Combining Convolutional Neural Network and Support Vector Machine to Predict Colorectal Cancer Prognosis and Mutational Signatures From Hematoxylin and Eosin Images.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Jul 15, 2024
Reducing recurrence following radical resection of colon cancer without overtreatment or undertreatment remains a challenge. Postoperative adjuvant chemotherapy (Adj) is currently administered based solely on pathologic TNM stage. However, prognosis ...
Enhanced deep learning model for precise nodule localization and recurrence risk prediction following curative-intent surgery for lung cancer.
PloS one
Jul 12, 2024
PURPOSE: Radical surgery is the primary treatment for early-stage resectable lung cancer, yet recurrence after curative surgery is not uncommon. Identifying patients at high risk of recurrence using preoperative computed tomography (CT) images could ...
Ultrasound-based nomogram to predict the recurrence in papillary thyroid carcinoma using machine learning.
BMC cancer
Jul 7, 2024
BACKGROUND AND AIMS: The recurrence of papillary thyroid carcinoma (PTC) is not unusual and associated with risk of death. This study is aimed to construct a nomogram that combines clinicopathological characteristics and ultrasound radiomics signatur...
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