AIMC Topic: Neoplasm Staging

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A prognostic and predictive model based on deep learning to identify optimal candidates for intensity-modulated radiotherapy alone in patients with stage II nasopharyngeal carcinoma: A retrospective multicenter study.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
PURPOSE: To develop and validate a prognostic and predictive model integrating deep learning MRI features and clinical information in patients with stage II nasopharyngeal carcinoma (NPC) to identify patients with a low risk of progression for whom i...

Comparative Analysis of Nomogram and Machine Learning Models for Predicting Axillary Lymph Node Metastasis in Early-Stage Breast Cancer: A Study on Clinically and Ultrasound-Negative Axillary Cases Across Two Centers.

Ultrasound in medicine & biology
OBJECTIVE: Early and accurate prediction of axillary lymph node metastasis (ALNM) is crucial in determining appropriate treatment strategies for patients with early-stage breast cancer. The aim of this study was to evaluate the efficacy of radiomic f...

State-of-the-art performance of deep learning methods for pre-operative radiologic staging of colorectal cancer lymph node metastasis: a scoping review.

BMJ open
OBJECTIVES: To assess the current state-of-the-art in deep learning methods applied to pre-operative radiologic staging of colorectal cancer lymph node metastasis. Specifically, by evaluating the data, methodology and validation of existing work, as ...

Development and Validation of Machine Learning Model Platelet Index-based Predictor for Colorectal Cancer Stage.

Asian Pacific journal of cancer prevention : APJCP
INTRODUCTION: Colorectal cancer (CRC) staging is essential for effective treatment planning and prognosis. While platelet indices have shown promise in indicating CRC aggressiveness, a platelet index-based predictor for CRC staging has not been estab...

American College of Surgeons survival calculator for biliary tract cancers: using machine learning to individualize predictions.

Surgery
BACKGROUND: Although cancer prognosis is most commonly estimated by tumor stage, survival is multifactorial. Our objective was to develop an American College of Surgeons "Biliary Tract Cancer Survival Calculator" prototype using machine learning to g...

Application of NotebookLM, a large language model with retrieval-augmented generation, for lung cancer staging.

Japanese journal of radiology
PURPOSE: In radiology, large language models (LLMs), including ChatGPT, have recently gained attention, and their utility is being rapidly evaluated. However, concerns have emerged regarding their reliability in clinical applications due to limitatio...

Subtype-Specific Detection in Stage Ia Breast Cancer: Integrating Raman Spectroscopy, Machine Learning, and Liquid Biopsy for Personalised Diagnostics.

Journal of biophotonics
This study explores the integration of Raman spectroscopy (RS) with machine learning for the early detection and subtyping of breast cancer using blood plasma samples. We performed detailed spectral analyses, identifying significant spectral patterns...

Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer.

Scientific reports
Brain metastases (BMs) in extensive-stage small cell lung cancer (ES-SCLC) are often associated with poor survival rates and quality of life, making the timely identification of high-risk patients for BMs in ES-SCLC crucial. Patients diagnosed with E...

Automatic TNM staging of colorectal cancer radiology reports using pre-trained language models.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Colorectal cancer is one of the major causes of cancer death worldwide. Essential for prognosis and treatment planning, TNM staging offers critical insights into the advancement of colorectal cancer. However, manual TNM stag...