Oncology/Hematology

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

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Identification of patients with malignant biliary strictures using a cholangioscopy-based deep learning artificial intelligence (with video).

BACKGROUND AND AIMS: Accurately diagnosing malignant biliary strictures (MBSs) as benign or malignan...

MRI-Based Artificial Intelligence in Rectal Cancer.

Rectal cancer (RC) accounts for approximately one-third of colorectal cancer (CRC), with death rates...

Automated irreversible electroporated region prediction using deep neural network, a preliminary study for treatment planning.

The primary purpose of cancer treatment with irreversible electroporation (IRE) is to maximize tumor...

Field validation of deep learning based Point-of-Care device for early detection of oral malignant and potentially malignant disorders.

Early detection of oral cancer in low-resource settings necessitates a Point-of-Care screening tool ...

Artificial intelligence in radiotherapy.

Radiotherapy is a discipline closely integrated with computer science. Artificial intelligence (AI) ...

A survey on gene expression data analysis using deep learning methods for cancer diagnosis.

Gene Expression Data is the biological data to extract meaningful hidden information from the gene d...

Radiomics and deep learning methods for the prediction of 2-year overall survival in LUNG1 dataset.

In this study, we tested and compared radiomics and deep learning-based approaches on the public LUN...

Deep learning reveals cuproptosis features assist in predict prognosis and guide immunotherapy in lung adenocarcinoma.

BACKGROUND: Cuproptosis is a recently found non-apoptotic cell death type that holds promise as an e...

A deep learning algorithm for detecting lytic bone lesions of multiple myeloma on CT.

BACKGROUND: Whole-body low-dose CT is the recommended initial imaging modality to evaluate bone dest...

Metaheuristic Optimization-Driven Novel Deep Learning Approach for Brain Tumor Segmentation.

Brain tumor has the foremost distinguished etiology of high morality. Neoplasm, a categorization of ...

Breast cancer patient characterisation and visualisation using deep learning and fisher information networks.

Breast cancer is the most commonly diagnosed female malignancy globally, with better survival rates ...

Deep learning can predict survival directly from histology in clear cell renal cell carcinoma.

For clear cell renal cell carcinoma (ccRCC) risk-dependent diagnostic and therapeutic algorithms are...

Attention Mask R-CNN with edge refinement algorithm for identifying circulating genetically abnormal cells.

Recent studies have suggested that circulating tumor cells with abnormalities in gene copy numbers i...

Fusion of CT images and clinical variables based on deep learning for predicting invasiveness risk of stage I lung adenocarcinoma.

PURPOSE: To develop a novel multimodal data fusion model by incorporating computed tomography (CT) i...

Biomarker identification by reversing the learning mechanism of an autoencoder and recursive feature elimination.

RNA-Seq has made significant contributions to various fields, particularly in cancer research. Recen...

Nuclear morphology is a deep learning biomarker of cellular senescence.

Cellular senescence is an important factor in aging and many age-related diseases, but understanding...

Using Sparse Patch Annotation for Tumor Segmentation in Histopathological Images.

Tumor segmentation is a fundamental task in histopathological image analysis. Creating accurate pixe...

Identification of Human Cell Cycle Phase Markers Based on Single-Cell RNA-Seq Data by Using Machine Learning Methods.

The cell cycle is composed of a series of ordered, highly regulated processes through which a cell g...

Deep Learning-Based CT Imaging in the Diagnosis of Treatment Effect of Pulmonary Nodules and Radiofrequency Ablation.

To study the effect of computerized tomography (CT) images based on deep learning algorithms on the ...

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