AIMC Topic: Lymphatic Metastasis
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Evaluating the prognostic value of tumor deposits in non-metastatic lymph node-positive colon adenocarcinoma using Cox regression and machine learning.
International journal of colorectal disease
Jun 26, 2024
BACKGROUND: The 8th AJCC TNM staging for non-metastatic lymph node-positive colon adenocarcinoma patients(NMLP-CA) stages solely by lymph node status, irrespective of the positivity of tumor deposits (TD). This study uses machine learning and Cox reg...
A non-invasive artificial intelligence model for identifying axillary pathological complete response to neoadjuvant chemotherapy in breast cancer: a secondary analysis to multicenter clinical trial.
British journal of cancer
Jun 25, 2024
BACKGROUND: This study aims to develop a stacking model for accurately predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) using longitudinal MRI in breast cancer.
Artificial Intelligence in Head and Neck Surgery.
Otolaryngologic clinics of North America
Jun 22, 2024
This article explores artificial intelligence's (AI's) role in otolaryngology for head and neck cancer diagnosis and management. It highlights AI's potential in pattern recognition for early cancer detection, prognostication, and treatment planning, ...
Dual-source dual-energy CT and deep learning for equivocal lymph nodes on CT images for thyroid cancer.
European radiology
Jun 21, 2024
OBJECTIVES: This study investigated the diagnostic performance of dual-energy computed tomography (CT) and deep learning for the preoperative classification of equivocal lymph nodes (LNs) on CT images in thyroid cancer patients.
A pathologist-AI collaboration framework for enhancing diagnostic accuracies and efficiencies.
Nature biomedical engineering
Jun 19, 2024
In pathology, the deployment of artificial intelligence (AI) in clinical settings is constrained by limitations in data collection and in model transparency and interpretability. Here we describe a digital pathology framework, nuclei.io, that incorpo...
Noninvasive prediction of lymph node metastasis in pancreatic cancer using an ultrasound-based clinicoradiomics machine learning model.
Biomedical engineering online
Jun 18, 2024
OBJECTIVES: This study was designed to explore and validate the value of different machine learning models based on ultrasound image-omics features in the preoperative diagnosis of lymph node metastasis in pancreatic cancer (PC).
Smart scanning: automatic detection of superficially located lymph nodes using ultrasound - initial results.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Jun 17, 2024
Over the last few years, there has been an increasing focus on integrating artificial intelligence (AI) into existing imaging systems. This also applies to ultrasound. There are already applications for thyroid and breast lesions that enable AI-assis...
Diagnostic accuracy of CT-based radiomics and deep learning for predicting lymph node metastasis in esophageal cancer.
Clinical imaging
Jun 16, 2024
BACKGROUND: Esophageal cancer remains a global challenge due to late diagnoses and limited treatments. Lymph node metastasis (LNM) is crucial for prognosis, yet traditional diagnostics fall short. Integrating radiomics and deep learning (DL) with CT ...
Deep learning-based pathological prediction of lymph node metastasis for patient with renal cell carcinoma from primary whole slide images.
Journal of translational medicine
Jun 14, 2024
BACKGROUND: Metastasis renal cell carcinoma (RCC) patients have extremely high mortality rate. A predictive model for RCC micrometastasis based on pathomics could be beneficial for clinicians to make treatment decisions.
Using machine learning to develop preoperative model for lymph node metastasis in patients with bladder urothelial carcinoma.
BMC cancer
Jun 13, 2024
BACKGROUND: Lymph node metastasis (LNM) is associated with worse prognosis in bladder urothelial carcinoma (BUC) patients. This study aimed to develop and validate machine learning (ML) models to preoperatively predict LNM in BUC patients treated wit...
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