Oncology/Hematology

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

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Exploring the spatial effects influencing the EGFR/ERK pathway dynamics with machine learning surrogate models.

The fate of cells is regulated by biochemical reactions taking place inside of them, known as intrac...

An explainable longitudinal multi-modal fusion model for predicting neoadjuvant therapy response in women with breast cancer.

Multi-modal image analysis using deep learning (DL) lays the foundation for neoadjuvant treatment (N...

The Segment Anything foundation model achieves favorable brain tumor auto-segmentation accuracy in MRI to support radiotherapy treatment planning.

BACKGROUND: Promptable foundation auto-segmentation models like Segment Anything (SA, Meta AI, New Y...

Supporting the care to breast cancer patients with unique needs: Evidence from online community members' responses.

BACKGROUND: Breast cancer is the most common cancer diagnosed in women globally. Online cancer commu...

Prostate cancer prognosis using machine learning: A critical review of survival analysis methods.

Prostate Cancer is a disease that affects the male reproductive system. The irregularity of the symp...

Automated real-world data integration improves cancer outcome prediction.

The digitization of health records and growing availability of tumour DNA sequencing provide an oppo...

Machine learning models in evaluating the malignancy risk of ovarian tumors: a comparative study.

OBJECTIVES: The study aimed to compare the diagnostic efficacy of the machine learning models with e...

Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.

This study aimed to construct and assess a machine-learning algorithm designed to forecast survival ...

Automatic delineation of cervical cancer target volumes in small samples based on multi-decoder and semi-supervised learning and clinical application.

Radiotherapy has been demonstrated to be one of the most significant treatments for cervical cancer,...

Identification of sentinel lymph node macrometastasis in breast cancer by deep learning based on clinicopathological characteristics.

The axillary lymph node status remains an important prognostic factor in breast cancer, and nodal st...

Optimizing thyroid AUS nodules malignancy prediction: a comprehensive study of logistic regression and machine learning models.

BACKGROUND: The accurate diagnosis of thyroid nodules with indeterminate cytology, particularly in t...

Classifying driver mutations of papillary thyroid carcinoma on whole slide image: an automated workflow applying deep convolutional neural network.

BACKGROUND: Informative biomarkers play a vital role in guiding clinical decisions regarding managem...

Non-small cell lung cancer detection through knowledge distillation approach with teaching assistant.

Non-small cell lung cancer (NSCLC) exhibits a comparatively slower rate of metastasis in contrast to...

Evaluating the Efficacy of Deep Learning Reconstruction in Reducing Radiation Dose for Computer-Aided Volumetry for Liver Tumor: A Phantom Study.

OBJECTIVE: The purpose of this study was to compare radiation dose reduction capability for accurate...

Human-Artificial Intelligence Symbiotic Reporting for Theranostic Cancer Care.

Reporting of diagnostic nuclear images in clinical cancer management is generally qualitative. Thera...

Enhanced NSCLC subtyping and staging through attention-augmented multi-task deep learning: A novel diagnostic tool.

OBJECTIVES: The objective of this study is to develop a novel multi-task learning approach with atte...

Deep Learning-Assisted Label-Free Parallel Cell Sorting with Digital Microfluidics.

Sorting specific cells from heterogeneous samples is important for research and clinical application...

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