Oncology/Hematology

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

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High-Precision Intelligent Diagnosis of Pancreatic Cancer: Flowing Diffuseness from Single to Whole.

Raman spectroscopy, as a label-free optical technique, provides a unique solution for tissue diagnos...

Enhancing detection and monitoring of circulating tumor cells: Integrative approaches in liquid biopsy advances.

Liquid biopsy offers a minimally invasive method for detecting and monitoring cancer, with key bioma...

B lymphocyte subset-based stratification in primary Sjögren's syndrome: implications for lymphoma risk and personalized treatment.

OBJECTIVE: This study aimed to perform a detailed stratification analysis of B lymphocyte subsets in...

Assessing ChatGPT for clinical decision-making in radiation oncology, with open-ended questions and images.

PURPOSE: This study assesses the practicality and correctness of ChatGPT-4 and 4O's answers to clini...

Identification of M2 macrophage-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches.

M2 macrophages play a crucial role in the initiation and progression of various tumors, including di...

Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma.

BACKGROUND: Ttyrosine kinase inhibitors (TKIs) represent the standard first-line treatment for patie...

Development and validation a radiomics combined clinical model predicts treatment response for esophageal squamous cell carcinoma patients.

PURPOSE: This study is aimed to develop and validate a machine learning model, which combined radiom...

Brain tumor detection empowered with ensemble deep learning approaches from MRI scan images.

Brain tumor detection is essential for early diagnosis and successful treatment, both of which can s...

From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.

Gliomas are the most common primary tumors of the central nervous system, and advances in genetics a...

A practical approach for colorectal cancer diagnosis based on machine learning.

In this paper, we present the results of applying machine learning models to build a Colorectal Canc...

Global-Local Feature Fusion Network Based on Nonlinear Spiking Neural Convolutional Model for MRI Brain Tumor Segmentation.

Due to the differences in size, shape, and location of brain tumors, brain tumor segmentation differ...

Construction of a Multimodal Machine Learning Model for Papillary Thyroid Carcinoma Based on Pathomics and Ultrasound Radiomics Dataset.

The use of machine learning to integrate and analyse multimodal information has broad prospects for ...

Mexican dataset of digital mammograms (MEXBreast) with suspicious clusters of microcalcifications.

Breast cancer is one of the most prevalent cancers affecting women worldwide. Early detection and tr...

Machine Learning-Based Radiomics in Malignancy Prediction of Pancreatic Cystic Lesions: Evidence from Cyst Fluid Multi-Omics.

The malignant potential of pancreatic cystic lesions (PCLs) varies dramatically, leading to difficul...

F-FDG PET/CT-based deep learning models and a clinical-metabolic nomogram for predicting high-grade patterns in lung adenocarcinoma.

BACKGROUND: To develop and validate deep learning (DL) and traditional clinical-metabolic (CM) model...

Impact of fine-tuning parameters of convolutional neural network for skin cancer detection.

Melanoma skin cancer is a deadly disease with a high mortality rate. A prompt diagnosis can aid in t...

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