AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Neoplasm Staging

Showing 181 to 190 of 491 articles

Clear Filters

Machine Learning-Based Radiomics Signatures for EGFR and KRAS Mutations Prediction in Non-Small-Cell Lung Cancer.

International journal of molecular sciences
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for patients with non-small-cell lung cancer (NSCLC). We proposed a machin...

The use of a next-generation sequencing-derived machine-learning risk-prediction model (OncoCast-MPM) for malignant pleural mesothelioma: a retrospective study.

The Lancet. Digital health
BACKGROUND: Current risk stratification for patients with malignant pleural mesothelioma based on disease stage and histology is inadequate. For some individuals with early-stage epithelioid tumours, a good prognosis by current guidelines can progres...

The impact of site-specific digital histology signatures on deep learning model accuracy and bias.

Nature communications
The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and dri...

Artificial intelligence-based radiomics models in endometrial cancer: A systematic review.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
BACKGROUND: Radiological preoperative assessment of endometrial cancer (EC) is in some cases not precise enough and its performances improvement could lead to a clinical benefit. Radiomics is a recent field of application of artificial intelligence (...

The predictive power of artificial intelligence on mediastinal lymphnode metastasis.

General thoracic and cardiovascular surgery
OBJECTIVE: The aim of this study was to create the preoperative predictive model on mediastinal lymph-node metastasis based on artificial intelligence in surgically resected lung adenocarcinoma.

A different overview of staging PET/CT images in patients with esophageal cancer: the role of textural analysis with machine learning methods.

Annals of nuclear medicine
OBJECTIVE: This study evaluates the ability of several machine learning (ML) algorithms, developed using volumetric and texture data extracted from baseline F-FDG PET/CT studies performed initial staging of patient with esophageal cancer (EC), to pre...

Clinical use of machine learning-based pathomics signature for diagnosis and survival prediction of bladder cancer.

Cancer science
Traditional histopathology performed by pathologists by the naked eye is insufficient for accurate and efficient diagnosis of bladder cancer (BCa). We collected 643 H&E-stained BCa images from Shanghai General Hospital and The Cancer Genome Atlas (TC...