AIMC Topic: Neoplasm Staging
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Automated tumor localization and segmentation through hybrid neural network in head and neck cancer.
Medical dosimetry : official journal of the American Association of Medical Dosimetrists
Oct 10, 2024
PURPOSE: Head and Neck (H&N) cancer accounts for 3% of cancer cases in the United States. Precise tumor segmentation in H&N is of utmost importance for treatment planning and administering personalized treatment dose. We aimed to develop an automatic...
Prediction and validation of pathologic complete response for locally advanced rectal cancer under neoadjuvant chemoradiotherapy based on a novel predictor using interpretable machine learning.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Oct 6, 2024
BACKGROUND: Precise evaluation of pathological complete response (pCR) is essential for determining the prognosis of patients with locally advanced rectal cancer (LARC) undergoing neoadjuvant chemoradiotherapy (NCRT) and can offer clues for the selec...
Prognostic insights after surgery for advances in understanding signet ring cell gastric cancer: a machine learning approach.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Oct 3, 2024
BACKGROUND: Signet ring cell (SRC) gastric carcinoma is traditionally associated with a poor prognosis. However, the literature has presented contradictory results. Linear models are the standard statistical tools typically used to study these condit...
Comparing the Management Recommendations of Large Language Model and Colorectal Cancer Multidisciplinary Team: A Pilot Study.
Diseases of the colon and rectum
Sep 27, 2024
BACKGROUND: Management of anorectal cancers requires a multidisciplinary team approach. Recently, large language models have been suggested as potential tools for various applications in health care.
Efficacy of a whole slide image-based prediction model for lymph node metastasis in T1 colorectal cancer: A systematic review.
Journal of gastroenterology and hepatology
Sep 26, 2024
BACKGROUND AND AIM: Accurate stratification of the risk of lymph node metastasis (LNM) following endoscopic resection of submucosal invasive (T1) colorectal cancer (CRC) is imperative for determining the necessity for additional surgery. In this syst...
Application of machine learning for predicting lymph node metastasis in T1 colorectal cancer: a systematic review and meta-analysis.
Langenbeck's archives of surgery
Sep 23, 2024
BACKGROUND: We review and analyze research on the application of machine learning (ML) and deep learning (DL) models to lymph node metastasis (LNM) prediction in patients with T1 colorectal cancer (CRC). Predicting LNM before radical surgery is impor...
Machine learning to predict distant metastasis and prognostic analysis of moderately differentiated gastric adenocarcinoma patients: a novel focus on lymph node indicators.
Frontiers in immunology
Sep 19, 2024
BACKGROUND: Moderately differentiated gastric adenocarcinoma (MDGA) has a high risk of metastasis and individual variation, which strongly affects patient prognosis. Using large-scale datasets and machine learning algorithms for prediction can improv...
Artificial Intelligence Algorithm Can Predict Lymph Node Malignancy from Endobronchial Ultrasound Transbronchial Needle Aspiration Images for Non-Small Cell Lung Cancer.
Respiration; international review of thoracic diseases
Sep 14, 2024
INTRODUCTION: Endobronchial ultrasound transbronchial needle aspiration (EBUS-TBNA) for lung cancer staging is operator dependent, resulting in high rates of non-diagnostic lymph node (LN) samples. We hypothesized that an artificial intelligence (AI)...
Deep neural networks integrating genomics and histopathological images for predicting stages and survival time-to-event in colon cancer.
PloS one
Sep 3, 2024
MOTIVATION: There exists an unexplained diverse variation within the predefined colon cancer stages using only features from either genomics or histopathological whole slide images as prognostic factors. Unraveling this variation will bring about imp...
Prostate cancer treatment recommendation study based on machine learning and SHAP interpreter.
Cancer science
Sep 2, 2024
This study utilized data from 140,294 prostate cancer cases from the Surveillance, Epidemiology, and End Results (SEER) database. Here, 10 different machine learning algorithms were applied to develop treatment options for predicting patients with pr...
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