Oncology/Hematology

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

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Machine-learning derived identification of prognostic signature to forecast head and neck squamous cell carcinoma prognosis and drug response.

INTRODUCTION: Head and neck squamous cell carcinoma (HNSCC), a highly heterogeneous malignancy is of...

A Machine Learning Model to Predict De Novo Hepatocellular Carcinoma Beyond Year 5 of Antiviral Therapy in Patients With Chronic Hepatitis B.

BACKGROUND AND AIMS: This study aims to develop and validate a machine learning (ML) model predictin...

Deep learning detected histological differences between invasive and non-invasive areas of early esophageal cancer.

The depth of invasion plays a critical role in predicting the prognosis of early esophageal cancer, ...

[Impact of artificial intelligence on the evolution of clinical practices in oncology: Focus on language models].

Artificial intelligence (AI) is addressing many expectations for healthcare practitioners and patien...

Reduced-dose deep learning iterative reconstruction for abdominal computed tomography with low tube voltage and tube current.

BACKGROUND: The low tube-voltage technique (e.g., 80 kV) can efficiently reduce the radiation dose a...

Novel artificial intelligence-based identification of drug-gene-disease interaction using protein-protein interaction.

The evaluation of drug-gene-disease interactions is key for the identification of drugs effective ag...

A potential predictive model based on machine learning and CPD parameters in elderly patients with aplastic anemia and myelodysplastic neoplasms.

BACKGROUND: Aplastic anemia (AA) and myelodysplastic neoplasms (MDS) have similar peripheral blood m...

The Depth Estimation and Visualization of Dermatological Lesions: Development and Usability Study.

BACKGROUND: Thus far, considerable research has been focused on classifying a lesion as benign or ma...

Machine learning-assisted pattern recognition and imaging of multiplexed cancer cells a porphyrin-embedded dendrimer array.

Early cancer detection plays a vital role in improving the survival rate of cancer patients, undersc...

Lymphoma triage from H&E using AI for improved clinical management.

AIMS: In routine diagnosis of lymphoma, initial non-specialist triage is carried out when the sample...

Dysregulation of saliva and fecal microbiota as novel biomarkers of colorectal cancer.

The aim of this study was to investigate the biomarkers of salivary and fecal microbiota in Colorect...

Convolutional neural network-assisted Raman spectroscopy for high-precision diagnosis of glioblastoma.

Glioblastoma multiforme (GBM) is the most lethal intracranial tumor with a median survival of approx...

Attention-based Fusion Network for Breast Cancer Segmentation and Classification Using Multi-modal Ultrasound Images.

OBJECTIVE: Breast cancer is one of the most commonly occurring cancers in women. Thus, early detecti...

Development of Deep Learning-Based Virtual Lugol Chromoendoscopy for Superficial Esophageal Squamous Cell Carcinoma.

BACKGROUND: Lugol chromoendoscopy has been shown to increase the sensitivity of detection of esophag...

Artificial intelligence-enhanced magnetic resonance imaging-based pre-operative staging in patients with endometrial cancer.

OBJECTIVE: Evaluation of prognostic factors is crucial in patients with endometrial cancer for optim...

Advancing miRNA cancer research through artificial intelligence: from biomarker discovery to therapeutic targeting.

MicroRNAs (miRNAs), a class of small non-coding RNAs, play a vital role in regulating gene expressio...

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