AIMC Topic: Neoplasm Staging
Clear Filters Showing 451 to 460 of 530 articles
Evolutionary learning-derived lncRNA signature with biomarker discovery for predicting stage of colon adenocarcinoma.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2024
In recent years, long non-coding RNAs (lncRNAs) have emerged as potential regulators of biological processes and genes, with the potential to serve as valuable biomarkers for cancer diagnosis and prognosis prediction. This work proposes an evolutiona...
Natural Language Processing Algorithm to Extract Multiple Myeloma Stage From Oncology Notes in the Veterans Affairs Healthcare System.
JCO clinical cancer informatics
Jul 1, 2024
PURPOSE: Stage in multiple myeloma (MM) is an essential measure of disease risk, but its measurement in large databases is often lacking. We aimed to develop and validate a natural language processing (NLP) algorithm to extract oncologists' documenta...
A Machine Learning Algorithm Facilitates Prognosis Prediction and Treatment Selection for Barcelona Clinic Liver Cancer Stage C Hepatocellular Carcinoma.
Clinical cancer research : an official journal of the American Association for Cancer Research
Jul 1, 2024
PURPOSE: Given its heterogeneity and diverse clinical outcomes, precise subclassification of Barcelona Clinic Liver Cancer stage C (BCLC-C) hepatocellular carcinoma (HCC) is required for appropriately determining patient prognosis and selecting treat...
Artificial intelligence-empowered cellular morphometric risk score improves prognostic stratification of cutaneous squamous cell carcinoma.
Clinical and experimental dermatology
Jun 25, 2024
BACKGROUND: Risk stratification of cutaneous squamous cell carcinoma (cSCC) is essential for managing patients.
Use of Natural Language Understanding to Facilitate Surgical De-Escalation of Axillary Staging in Patients With Breast Cancer.
JCO clinical cancer informatics
May 1, 2024
PURPOSE: Natural language understanding (NLU) may be particularly well equipped for enhanced data capture from the electronic health record given its examination of both content-driven and context-driven extraction.
Integrating artificial intelligence techniques for advancements in colorectal cancer management: navigating past and predicting future direction.
JPMA. The Journal of the Pakistan Medical Association
Apr 1, 2024
Artificial Intelligence (AI) in the last few years has emerged as a valuable tool in managing colorectal cancer, revolutionizing its management at different stages. In early detection and diagnosis, AI leverages its prowess in imaging analysis, scrut...
Predicting High-Grade Patterns in Stage I Solid Lung Adenocarcinoma: A Study of 371 Patients Using Refined Radiomics and Deep Learning-Guided CatBoost Classifier.
Technology in cancer research & treatment
Jan 1, 2024
INTRODUCTION: This study aimed to devise a diagnostic algorithm, termed the Refined Radiomics and Deep Learning Features-Guided CatBoost Classifier (RRDLC-Classifier), and evaluate its efficacy in predicting pathological high-grade patterns in patien...
Prediction of T Stage of Rectal Cancer After Neoadjuvant Therapy by Multi-Parameter Magnetic Resonance Radiomics Based on Machine Learning Algorithms.
Technology in cancer research & treatment
Jan 1, 2024
INTRODUCTION: Since the response of patients with rectal cancer (RC) to neoadjuvant therapy is highly variable, there is an urgent need to develop accurate methods to predict the post-treatment T (pT) stage. The purpose of this study was to evaluate ...
An XGBoost Machine Learning Based Model for Predicting Ki-67 Value ≥ 15% in TNM Stage Primary Breast Cancer Receiving Neoadjuvant Chemotherapy Using Clinical Data and Delta-Radiomic Features on Ultrasound Images and Overall Survival Analysis: A 5-Year Postoperative Follow-Up Study.
Technology in cancer research & treatment
Jan 1, 2024
To establish a model based on clinical and delta-radiomic features within ultrasound images using XGBoost machine learning to predict proliferation-associated nuclear antigen Ki-67 value ≥ 15% in TNM stage primary breast cancer (BC). Data were coll...
Artificial Intelligence-suggested Predictive Model of Survival in Patients Treated With Stereotactic Radiotherapy for Early Lung Cancer.
In vivo (Athens, Greece)
Jan 1, 2024
BACKGROUND/AIM: Overall survival (OS)-predictive models to clinically stratify patients with stage I Non-Small Cell Lung Cancer (NSCLC) undergoing stereotactic body radiation therapy (SBRT) are still unavailable. The aim of this work was to build a p...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 31984
- Neural Networks, Computer 30211
- Algorithms 27388
- Deep Learning 26888
- Artificial Intelligence 24826
- Robotics 13382
- Image Processing, Computer-Assisted 9732
- Retrospective Studies 9334
- Magnetic Resonance Imaging 6342
- Reproducibility of Results 5670
- Tomography, X-Ray Computed 4864
- Support Vector Machine 4766
- Computational Biology 4331
- Brain 4126
- Computer Simulation 3932
Recent Journals
- Scientific reports 6743
- Sensors (Basel, Switzerland) 4794
- PloS one 4196
- Neural networks : the official journal of the International Neural Network Society 3026
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1916
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1378
- IEEE journal of biomedical and health informatics 1170
- Journal of chemical information and modeling 1064
- Nature communications 1039
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 873
- Journal of medical Internet research 860
- Briefings in bioinformatics 853