Oncology/Hematology

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

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Showing 1975-1995 of 15,280 articles
Use of machine learning algorithms to construct models of symptom burden cluster risk in breast cancer patients undergoing chemotherapy.

PURPOSE: To develop models using different machine learning algorithms to predict high-risk symptom ...

MLAR-UNet: LDCT image denoising based on U-Net with multiple lightweight attention-based modules and residual reinforcement.

Computed tomography (CT) is a crucial medical imaging technique which uses x-ray radiation to identi...

Diagnosis and treatment of a rare bilateral primary thyroid cancer: a case report.

Preoperative ultrasound examination of thyroid nodules is the most economical and effective screenin...

Artificial intelligence in gastrointestinal cancer research: Image learning advances and applications.

With the rapid advancement of artificial intelligence (AI) technologies, including deep learning, la...

A metabolic fingerprint of ovarian cancer: a novel diagnostic strategy employing plasma EV-based metabolomics and machine learning algorithms.

Ovarian cancer (OC) is the third most common malignant tumor of women and is accompanied by an alter...

A machine learning-based investigation of integrin expression patterns in cancer and metastasis.

Integrins, a family of transmembrane receptor proteins, are well known to play important roles in ca...

Cross prior Bayesian attention with correlated inception and residual learning for brain tumor classification using MR images (CB-CIRL Net).

BACKGROUND: Brain tumor classification from magnetic resonance (MR) images is crucial for early diag...

Artificial intelligence in digital pathology - time for a reality check.

The past decade has seen the introduction of artificial intelligence (AI)-based approaches aimed at ...

Artificial intelligence-assisted point-of-care devices for lung cancer.

Lung cancer is the leading cause of cancer-related deaths worldwide, primarily due to late-stage det...

ChatExosome: An Artificial Intelligence (AI) Agent Based on Deep Learning of Exosomes Spectroscopy for Hepatocellular Carcinoma (HCC) Diagnosis.

Large language models (LLMs) hold significant promise in the field of medical diagnosis. There are s...

Detection of metastatic breast carcinoma in sentinel lymph node frozen sections using an artificial intelligence-assisted system.

We developed an automatic method based on a convolutional neural network (CNN) that identifies metas...

Deep learning paradigms in lung cancer diagnosis: A methodological review, open challenges, and future directions.

Lung cancer is the leading cause of global cancer-related deaths, which emphasizes the critical impo...

Multi-modality medical image classification with ResoMergeNet for cataract, lung cancer, and breast cancer diagnosis.

The variability in image modalities presents significant challenges in medical image classification,...

Does Deep Learning Reconstruction Improve Ureteral Stone Detection and Subjective Image Quality in the CT Images of Patients with Metal Hardware?

Diagnosing ureteral stones with low-dose CT in patients with metal hardware can be challenging beca...

A novel method for screening malignant hematological diseases by constructing an optimal machine learning model based on blood cell parameters.

BACKGROUND: Screening of malignant hematological diseases is of great importance for their diagnosis...

A promising AI based super resolution image reconstruction technique for early diagnosis of skin cancer.

Skin cancer can be prevalent in people of any age group who are exposed to ultraviolet (UV) radiatio...

Deep Learning Radiomics for Survival Prediction in Non-Small-Cell Lung Cancer Patients from CT Images.

This study aims to apply a multi-modal approach of the deep learning method for survival prediction ...

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