Oncology/Hematology

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

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Diagnostic performance of deep learning models for detecting bone metastasis on whole-body bone scan in prostate cancer.

PURPOSE: We evaluated the performance of deep learning classifiers for bone scans of prostate cancer...

Detection of Lung Nodules in Micro-CT Imaging Using Deep Learning.

We are developing imaging methods for a co-clinical trial investigating synergy between immunotherap...

A Soft Robot for Peripheral Lung Cancer Diagnosis and Therapy.

Lung cancer is one of the deadliest forms of cancers and is often diagnosed by performing biopsies w...

Resolution-based distillation for efficient histology image classification.

Developing deep learning models to analyze histology images has been computationally challenging, as...

Interpretable deep recommender system model for prediction of kinase inhibitor efficacy across cancer cell lines.

Computational models for drug sensitivity prediction have the potential to significantly improve per...

Discriminant Projection Shared Dictionary Learning for Classification of Tumors Using Gene Expression Data.

With a variety of tumor subtypes, personalized treatments need to identify the subtype of a tumor as...

Cell Mechanics Based Computational Classification of Red Blood Cells Via Machine Intelligence Applied to Morpho-Rheological Markers.

Despite fluorescent cell-labelling being widely employed in biomedical studies, some of its drawback...

Hybrid Machine Learning Models for Predicting Types of Human T-cell Lymphotropic Virus.

Life threatening diseases like adult T-cell leukemia, neurodegenerative diseases, and demyelinating ...

REUR: A unified deep framework for signet ring cell detection in low-resolution pathological images.

Detecting signet ring cells (SRCs) in pathological images is essential for carcinoma diagnosis. Howe...

Axillary lymph node metastasis prediction by contrast-enhanced computed tomography images for breast cancer patients based on deep learning.

When doctors use contrast-enhanced computed tomography (CECT) images to predict the metastasis of ax...

Unsupervised machine learning reveals key immune cell subsets in COVID-19, rhinovirus infection, and cancer therapy.

For an emerging disease like COVID-19, systems immunology tools may quickly identify and quantitativ...

Application of Pet-CT Fusion Deep Learning Imaging in Precise Radiotherapy of Thyroid Cancer.

This article explores the value of wall F-FDG PET/Cr imaging in the diagnosis of thyroid cancer, stu...

Automatic segmentation of lung tumors on CT images based on a 2D & 3D hybrid convolutional neural network.

OBJECTIVE: A stable and accurate automatic tumor delineation method has been developed to facilitate...

Machine learning for evolutive lymphoma and residual masses recognition in whole body diffusion weighted magnetic resonance images.

BACKGROUND: After the treatment of the patients with malignant lymphoma, there may persist lesions t...

Deep learning for colon cancer histopathological images analysis.

Nowadays, digital pathology plays a major role in the diagnosis and prognosis of tumours. Unfortunat...

A Novel Deep Learning System for Diagnosing Early Esophageal Squamous Cell Carcinoma: A Multicenter Diagnostic Study.

INTRODUCTION: This study aims to construct a real-time deep convolutional neural networks (DCNNs) sy...

Surgical outcomes of robot-assisted laparoscopic partial nephrectomy for cystic renal cell carcinoma.

To compare the surgical outcomes of robot-assisted partial nephrectomy (RAPN) between patients with ...

Applications of machine and deep learning to patient-specific IMRT/VMAT quality assurance.

In order to deliver accurate and safe treatment to cancer patients in radiation therapy using advanc...

Automatic segmentation of rectal tumor on diffusion-weighted images by deep learning with U-Net.

PURPOSE: Manual delineation of a rectal tumor on a volumetric image is time-consuming and subjective...

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