Oncology/Hematology

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

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Showing 2059-2079 of 15,280 articles
A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things.

With bio-medical wearables becoming an essential part of Internet of Medical things (IoMT) for monit...

Practical X-ray gastric cancer diagnostic support using refined stochastic data augmentation and hard boundary box training.

Endoscopy is widely used to diagnose gastric cancer and has a high diagnostic performance, but it mu...

Optimizing AI models to predict esophageal squamous cell carcinoma risk by incorporating small datasets of soft palate images.

There is a currently an unmet need for non-invasive methods to predict the risk of esophageal squamo...

Artificial intelligence-based spatial analysis of tertiary lymphoid structures and clinical significance for endometrial cancer.

With the incorporation of immune checkpoint inhibitors into the treatment of endometrial cancer (EC)...

Prompt injection attacks on vision language models in oncology.

Vision-language artificial intelligence models (VLMs) possess medical knowledge and can be employed ...

Use of Artificial Intelligence in Lower Gastrointestinal and Small Bowel Disorders: An Update Beyond Polyp Detection.

Machine learning and its specialized forms, such as Artificial Neural Networks and Convolutional Neu...

Improving Outcomes in Hepatocellular Carcinoma through Integration of Machine Learning: Development of a Tumor-Associated Macrophage Signature.

INTRODUCTION: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors globally. Ma...

External validation of 12 existing survival prediction models for patients with spinal metastases.

BACKGROUND CONTEXT: Survival prediction models for patients with spinal metastases may inform patien...

Optimizing Skin Cancer Diagnosis: A Modified Ensemble Convolutional Neural Network for Classification.

Skin cancer is recognized as one of the most harmful cancers worldwide. Early detection of this canc...

NLP for Analyzing Electronic Health Records and Clinical Notes in Cancer Research: A Review.

This review examines the application of natural language processing (NLP) techniques in cancer resea...

The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update.

This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in...

Multiscale deep learning radiomics for predicting recurrence-free survival in pancreatic cancer: A multicenter study.

PURPOSE: This multicenter study aimed to develop and validate a multiscale deep learning radiomics n...

Predicting survival in malignant glioma using artificial intelligence.

Malignant gliomas, including glioblastoma, are amongst the most aggressive primary brain tumours, ch...

Towards unbiased skin cancer classification using deep feature fusion.

This paper introduces SkinWiseNet (SWNet), a deep convolutional neural network designed for the dete...

Comparison of deep transfer learning models for classification of cervical cancer from pap smear images.

Cervical cancer is one of the most commonly diagnosed cancers worldwide, and it is particularly prev...

Automated recognition and segmentation of lung cancer cytological images based on deep learning.

Compared with histological examination of lung cancer, cytology is less invasive and provides better...

BCT-Net: semantic-guided breast cancer segmentation on BUS.

Accurately and swiftly segmenting breast tumors is significant for cancer diagnosis and treatment. U...

Super-resolution deep-learning reconstruction with 1024 matrix improves CT image quality for pancreatic ductal adenocarcinoma assessment.

OBJECTIVES: To evaluate the efficiency of super-resolution deep-learning reconstruction (SR-DLR) opt...

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