Oncology/Hematology

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

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Showing 1996-2016 of 15,280 articles
A privacy-preserved horizontal federated learning for malignant glioma tumour detection using distributed data-silos.

Malignant glioma is the uncontrollable growth of cells in the spinal cord and brain that look simila...

Deformation registration based on reconstruction of brain MRI images with pathologies.

Deformable registration between brain tumor images and brain atlas has been an important tool to fac...

An accurate and trustworthy deep learning approach for bladder tumor segmentation with uncertainty estimation.

BACKGROUND AND OBJECTIVE: Although deep learning-based intelligent diagnosis of bladder cancer has a...

Real-Time, AI-Guided Photodynamic Laparoscopy Enhances Detection in a Rabbit Model of Peritoneal Cancer Metastasis.

Accurate diagnosis is essential for effective cancer treatment, particularly in peritoneal surface m...

Single-Cell Array Enhanced Cell Damage Recognition Using Artificial Intelligence for Anticancer Drug Discovery.

This work developed a cell damage recognition method based on single-cell arrays using an artificial...

Machine Learning-Enabled Non-Invasive Screening of Tumor-Associated Circulating Transcripts for Early Detection of Colorectal Cancer.

Colorectal cancer (CRC) is a major cause of cancer-related mortality, highlighting the need for accu...

Development of a deep learning system for predicting biochemical recurrence in prostate cancer.

BACKGROUND: Biochemical recurrence (BCR) occurs in 20%-40% of men with prostate cancer (PCa) who und...

A robust deep learning framework for multiclass skin cancer classification.

Skin cancer represents a significant global health concern, where early and precise diagnosis plays ...

Machine learning prediction of breast cancer local recurrence localization, and distant metastasis after local recurrences.

Local recurrences (LR) can occur within residual breast tissue, chest wall, skin, or newly formed sc...

Identifying invasiveness to aid lung adenocarcinoma diagnosis using deep learning and pathomics.

Most classification efforts for primary subtypes of lung adenocarcinoma (LUAD) have not yet been int...

Comparative performance of multiple ensemble learning models for preoperative prediction of tumor deposits in rectal cancer based on MR imaging.

Ensemble learning can effectively mitigate the risk of model overfitting during training. This study...

PhysioEx: a new Python library for explainable sleep staging through deep learning.

Sleep staging is a crucial task in clinical and research contexts for diagnosing and understanding s...

WaveSleepNet: An Interpretable Network for Expert-Like Sleep Staging.

Although deep learning algorithms have proven their efficiency in automatic sleep staging, their "bl...

CT-Less Whole-Body Bone Segmentation of PET Images Using a Multimodal Deep Learning Network.

In bone cancer imaging, positron emission tomography (PET) is ideal for the diagnosis and staging of...

Machine Learning Identification and Classification of Mitosis and Migration of Cancer Cells in a Lab-on-CMOS Capacitance Sensing Platform.

Cell culture assays play a vital role in various fields of biology. Conventional assay techniques li...

A Multimodal Consistency-Based Self-Supervised Contrastive Learning Framework for Automated Sleep Staging in Patients With Disorders of Consciousness.

Sleep is a fundamental human activity, and automated sleep staging holds considerable investigationa...

Interpretable Dynamic Directed Graph Convolutional Network for Multi-Relational Prediction of Missense Mutation and Drug Response.

Tumor heterogeneity presents a significant challenge in predicting drug responses, especially as mis...

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