AIMC Topic: Neoadjuvant Therapy
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Establishment and clinical application of a prognostic index for inflammatory status in triple-negative breast cancer patients undergoing neoadjuvant therapy using machine learning.
BMC cancer
Dec 20, 2024
OBJECTIVE: This study aims to establish a new prognostic index using machine learning models to predict the clinical outcomes of triple-negative breast cancer (TNBC) patients receiving neoadjuvant therapy.
Interpretable multi-modal artificial intelligence model for predicting gastric cancer response to neoadjuvant chemotherapy.
Cell reports. Medicine
Dec 4, 2024
Neoadjuvant chemotherapy assessment is imperative for prognostication and clinical management of locally advanced gastric cancer. We propose an incremental supervised contrastive learning model (iSCLM), an interpretable artificial intelligence framew...
Artificial intelligence measured 3D lumbosacral body composition and clinical outcomes in rectal cancer patients.
ANZ journal of surgery
Nov 27, 2024
INTRODUCTION: Patient body composition (BC) has been shown to help predict clinical outcomes in rectal cancer patients. Artificial intelligence algorithms have allowed for easier acquisition of BC measurements, creating a comprehensive BC profile in ...
Using Machine Learning Models to Predict Pathologic Complete Response to Neoadjuvant Chemotherapy in Breast Cancer.
JCO clinical cancer informatics
Nov 22, 2024
PURPOSE: Neoadjuvant chemotherapy (NAC) is increasingly used in breast cancer. Predictive modeling is useful in predicting pathologic complete response (pCR) to NAC. We test machine learning (ML) models to predict pCR in breast cancer and explore met...
Response prediction for neoadjuvant treatment in locally advanced rectal cancer patients-improvement in decision-making: A systematic review.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Nov 15, 2024
BACKGROUND: Predicting pathological complete response (pCR) from pre or post-treatment features could be significant in improving the process of making clinical decisions and providing a more personalized treatment approach for better treatment outco...
Early and noninvasive prediction of response to neoadjuvant therapy for breast cancer via longitudinal ultrasound and MR deep learning: A multicentre study.
Academic radiology
Nov 13, 2024
RATIONALE AND OBJECTIVES: The early prediction of response to neoadjuvant chemotherapy (NAC) will aid in the development of personalized treatments for patients with breast cancer. This study investigated the value of longitudinal multimodal deep lea...
An explainable longitudinal multi-modal fusion model for predicting neoadjuvant therapy response in women with breast cancer.
Nature communications
Nov 7, 2024
Multi-modal image analysis using deep learning (DL) lays the foundation for neoadjuvant treatment (NAT) response monitoring. However, existing methods prioritize extracting multi-modal features to enhance predictive performance, with limited consider...
Clinical evaluation of accelerated diffusion-weighted imaging of rectal cancer using a denoising neural network.
European journal of radiology
Oct 24, 2024
BACKGROUND: To evaluate the effectiveness of a deep learning denoising approach to accelerate diffusion-weighted imaging (DWI) and thus improve diagnostic accuracy and image quality in restaging rectal MRI following total neoadjuvant therapy (TNT).
TopoTxR: A topology-guided deep convolutional network for breast parenchyma learning on DCE-MRIs.
Medical image analysis
Oct 16, 2024
Characterization of breast parenchyma in dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is a challenging task owing to the complexity of underlying tissue structures. Existing quantitative approaches, like radiomics and deep learning ...
A Multicenter Cohort Study on Ultrasound-based Deep Learning Nomogram for Predicting Post-Neoadjuvant Chemotherapy Axillary Lymph Node Status in Breast Cancer Patients.
Academic radiology
Oct 15, 2024
RATIONALE AND OBJECTIVES: The aim of this study was to evaluate the capability of an ultrasound (US)-based deep learning (DL) nomogram for predicting axillary lymph node (ALN) status after neoadjuvant chemotherapy (NAC) in breast cancer patients and ...
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