Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Showing 2710-2730 of 15,318 articles
Prediction of benign and malignant pulmonary nodules using preoperative CT features: using PNI-GARS as a predictor.

PURPOSE: The aim of this study was to develop and validate a prediction model for classification of ...

Predicting intraoperative 5-ALA-induced tumor fluorescence via MRI and deep learning in gliomas with radiographic lower-grade characteristics.

PURPOSE: Lower-grade gliomas typically exhibit 5-aminolevulinic acid (5-ALA)-induced fluorescence in...

Evaluating ChatGPT's competency in radiation oncology: A comprehensive assessment across clinical scenarios.

PURPOSE: Artificial intelligence (AI) and machine learning present an opportunity to enhance clinica...

Machine learning approach in canine mammary tumour classification using rapid evaporative ionization mass spectrometry.

Rapid evaporative ionization mass spectrometry (REIMS) coupled with a monopolar handpiece used for s...

Early multi-cancer detection through deep learning: An anomaly detection approach using Variational Autoencoder.

Cancer is a disease that causes many deaths worldwide. The treatment of cancer is first and foremost...

Targeting mitochondria in Cancer therapy: Machine learning analysis of hyaluronic acid-based drug delivery systems.

BACKGROUND: Mitochondrial alterations play a crucial role in the development and progression of canc...

Explainable Machine Learning Models Using Robust Cancer Biomarkers Identification from Paired Differential Gene Expression.

In oncology, there is a critical need for robust biomarkers that can be easily translated into the c...

XAI-driven CatBoost multi-layer perceptron neural network for analyzing breast cancer.

Early diagnosis of breast cancer is exceptionally important in signifying the treatment results, of ...

Convolutional neural network for oral cancer detection combined with improved tunicate swarm algorithm to detect oral cancer.

Early Diagnosis of oral cancer is very important and can save you from some oral malignancies. Howev...

Using machine learning to develop a stacking ensemble learning model for the CT radiomics classification of brain metastases.

The objective of this study was to explore the potential of machine-learning techniques in the autom...

Medication Prescription Policy for US Veterans With Metastatic Castration-Resistant Prostate Cancer: Causal Machine Learning Approach.

BACKGROUND: Prostate cancer is the second leading cause of death among American men. If detected and...

Deep learning based analysis of dynamic video ultrasonography for predicting cervical lymph node metastasis in papillary thyroid carcinoma.

BACKGROUND: Cervical lymph node metastasis (CLNM) is the most common form of thyroid cancer metastas...

Model Based on Ultrasound Radiomics and Machine Learning to Preoperative Differentiation of Follicular Thyroid Neoplasm.

OBJECTIVES: To evaluate the value of radiomics based on ultrasonography in differentiating follicula...

Diagnosis and typing of leukemia using a single peripheral blood cell through deep learning.

Leukemia is highly heterogeneous, meaning that different types of leukemia require different treatme...

A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.

BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathologi...

A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach.

BACKGROUND: Lung cancer is characterized by high morbidity and mortality due to the lack of practica...

The study on ultrasound image classification using a dual-branch model based on Resnet50 guided by U-net segmentation results.

In recent years, the incidence of nodular thyroid diseases has been increasing annually. Ultrasonogr...

Prior information guided deep-learning model for tumor bed segmentation in breast cancer radiotherapy.

BACKGROUND AND PURPOSE: Tumor bed (TB) is the residual cavity of resected tumor after surgery. Delin...

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