Oncology/Hematology

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

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Showing 1807-1827 of 15,280 articles
Syn-Net: A Synchronous Frequency-Perception Fusion Network for Breast Tumor Segmentation in Ultrasound Images.

Accurate breast tumor segmentation in ultrasound images is a crucial step in medical diagnosis and l...

CDAF-Net: A Contextual Contrast Detail Attention Feature Fusion Network for Low-Dose CT Denoising.

Low-dose computed tomography (LDCT) is a specialized CT scan with a lower radiation dose than normal...

Deep Augmented Metric Learning Network for Prostate Cancer Classification in Ultrasound Images.

Prostate cancer screening often relies on cost-intensive MRIs and invasive needle biopsies. Transrec...

Enhancing Drug Repositioning Through Local Interactive Learning With Bilinear Attention Networks.

Drug repositioning has emerged as a promising strategy for identifying new therapeutic applications ...

TARSL: Triple-Attention Cross-Network Representation Learning to Predict Synthetic Lethality for Anti-Cancer Drug Discovery.

Cancer is a multifaceted disease that results from co-mutations of multi biological molecules. A pro...

StackTHP: A stacking ensemble model for accurate prediction of tumor-homing peptides in cancer therapy.

The tumor-homing peptides (THPs) have emerged as one of the attractive resources for targeted cancer...

Deep learning for hepatocellular carcinoma recurrence before and after liver transplantation: a multicenter cohort study.

Hepatocellular carcinoma (HCC) recurrence after liver transplantation (LT) is a major contributor to...

Impact of [F]FDG PET/CT Radiomics and Artificial Intelligence in Clinical Decision Making in Lung Cancer: Its Current Role.

Lung cancer remains one of the most prevalent cancers globally and the leading cause of cancer-relat...

Comparison of the accuracy of GPT-4 and resident physicians in differentiating benign and malignant thyroid nodules.

OBJECTIVE: To assess the diagnostic performance of the GPT-4 model in comparison to resident physici...

Efficient Brain Tumor Detection and Segmentation Using DN-MRCNN With Enhanced Imaging Technique.

This article proposes a method called DenseNet 121-Mask R-CNN (DN-MRCNN) for the detection and segme...

Predicting the complexity of minimally invasive liver resection for hepatocellular carcinoma using machine learning.

BACKGROUND: Despite technical advancements, minimally invasive liver surgery (MILS) for hepatocellul...

Comparing Artificial Intelligence and Traditional Regression Models in Lung Cancer Risk Prediction Using A Systematic Review and Meta-Analysis.

PURPOSE: Accurately identifying individuals who are at high risk of lung cancer is critical to optim...

Breast cancer prediction based on gene expression data using interpretable machine learning techniques.

Breast cancer remains a global health burden, with an increase in deaths related to this particular ...

Identification of novel diagnostic and prognostic microRNAs in sarcoma on TCGA dataset: bioinformatics and machine learning approach.

The discovery of unique microRNA (miR) patterns and their corresponding genes in sarcoma patients in...

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