Oncology/Hematology

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

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Machine-learning algorithms predict breast cancer patient survival from UK Biobank whole-exome sequencing data.

We tested whether machine-learning algorithm could find biomarkers predicting overall survival in b...

Automatic identification of triple negative breast cancer in ultrasonography using a deep convolutional neural network.

Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detect...

Self-supervised driven consistency training for annotation efficient histopathology image analysis.

Training a neural network with a large labeled dataset is still a dominant paradigm in computational...

Automated detection of leukemia by pretrained deep neural networks and transfer learning: A comparison.

Leukemia is usually diagnosed by viewing the smears of blood and bone marrow using microscopes and c...

Automated detection and grading of Invasive Ductal Carcinoma breast cancer using ensemble of deep learning models.

Invasive ductal carcinoma (IDC) breast cancer is a significant health concern for women all around t...

Raman Spectroscopy and Machine Learning Reveals Early Tumor Microenvironmental Changes Induced by Immunotherapy.

Cancer immunotherapy provides durable clinical benefit in only a small fraction of patients, and ide...

A new prognostic score for predicting survival in patients treated with robotic stereotactic radiotherapy for brain metastases.

The study aimed to analyze potential prognostic factors in patients treated with robotic radiosurger...

Adaptive Diagnosis of Lung Cancer by Deep Learning Classification Using Wilcoxon Gain and Generator.

Cancer is a complicated worldwide health issue with an increasing death rate in recent years. With t...

Anti-cancer Peptide Recognition Based on Grouped Sequence and Spatial Dimension Integrated Networks.

The diversification of the characteristic sequences of anti-cancer peptides has imposed difficulties...

CT classification model of pancreatic serous cystic neoplasms and mucinous cystic neoplasms based on a deep neural network.

BACKGROUND: At present, numerous challenges exist in the diagnosis of pancreatic SCNs and MCNs. Afte...

BCHisto-Net: Breast histopathological image classification by global and local feature aggregation.

Breast cancer among women is the second most common cancer worldwide. Non-invasive techniques such a...

Multimodal kidney-preserving approach in localised and locally advanced high-risk upper tract urothelial carcinoma.

OBJECTIVES: Multimodal kidney-preserving (MKP) strategies may be an option for patients with localis...

Artificial Intelligence Applications in Pediatric Brain Tumor Imaging: A Systematic Review.

OBJECTIVE: Artificial intelligence (AI) has facilitated the analysis of medical imaging given increa...

CST: A Multitask Learning Framework for Colorectal Cancer Region Mining Based on Transformer.

Colorectal cancer is a high death rate cancer until now; from the clinical view, the diagnosis of th...

Phytochemical profile, antioxidant, antiproliferative, and enzyme inhibition-docking analyses of Celep & Doğan.

Celep & Doğan is an endemic species of Turkey. To our knowledge, the number of studies on biologica...

Development of monoclonal antibodies for quantification of bovine tumor necrosis factor-α.

The expression of the proinflammatory cytokine tumor necrosis factor-α (TNF-α) is associated with pr...

Predicting microvascular invasion in hepatocellular carcinoma: a deep learning model validated across hospitals.

BACKGROUND: The accuracy of estimating microvascular invasion (MVI) preoperatively in hepatocellular...

Deep Learning for nasopharyngeal Carcinoma Identification Using Both White Light and Narrow-Band Imaging Endoscopy.

OBJECTIVES/HYPOTHESIS: To develop a deep-learning-based automatic diagnosis system for identifying n...

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