Oncology/Hematology

Other Cancers

Latest AI and machine learning research in other cancers for healthcare professionals.

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A Human Microrobot Interface Based on Acoustic Manipulation.

Micro/nanorobotic systems capable of targeted transporting and releasing hold considerable promise f...

Cross-modality (CT-MRI) prior augmented deep learning for robust lung tumor segmentation from small MR datasets.

PURPOSE: Accurate tumor segmentation is a requirement for magnetic resonance (MR)-based radiotherapy...

Machine learning application for prediction of locoregional recurrences in early oral tongue cancer: a Web-based prognostic tool.

Estimation of risk of recurrence in early-stage oral tongue squamous cell carcinoma (OTSCC) remains ...

An improved fuzzy-differential evolution approach applied to classification of tumors in liver CT scan images.

Fuzzy inference systems have been frequently used in medical diagnosis for managing uncertainty sour...

Documentation of Palliative and End-of-Life Care Process Measures Among Young Adults Who Died of Cancer: A Natural Language Processing Approach.

Few studies have investigated palliative and end-of-life care processes among young adults (YAs), ag...

Classification and Segmentation of Hyperspectral Data of Hepatocellular Carcinoma Samples Using 1-D Convolutional Neural Network.

Pathological diagnosis plays an important role in the diagnosis and treatment of hepatocellular carc...

An augmented reality microscope with real-time artificial intelligence integration for cancer diagnosis.

The microscopic assessment of tissue samples is instrumental for the diagnosis and staging of cancer...

An investigation of CNN models for differentiating malignant from benign lesions using small pathologically proven datasets.

Cancer has been one of the most threatening diseases to human health. There have been many efforts d...

Cytokeratin-Supervised Deep Learning for Automatic Recognition of Epithelial Cells in Breast Cancers Stained for ER, PR, and Ki-67.

Immunohistochemistry (IHC) of ER, PR, and Ki-67 are routinely used assays in breast cancer diagnosti...

Machine learning applications in prostate cancer magnetic resonance imaging.

With this review, we aimed to provide a synopsis of recently proposed applications of machine learni...

Gene Ontology and Expression Studies of Strigolactone Analogues on a Hepatocellular Carcinoma Cell Line.

Human hepatocellular carcinoma (HCC) is the most common and recurrent type of primary adult liver ca...

3D segmentation of nasopharyngeal carcinoma from CT images using cascade deep learning.

In the paper, we propose a new deep learning-based method for segmenting nasopharyngeal carcinoma (N...

Support Vector Machine Classification of Nonmelanoma Skin Lesions Based on Fluorescence Lifetime Imaging Microscopy.

Early diagnosis of malignant skin lesions is critical for prompt treatment and a clinical prognosis ...

Automated detection and classification of early AMD biomarkers using deep learning.

Age-related macular degeneration (AMD) affects millions of people and is a leading cause of blindnes...

A whole slide image-based machine learning approach to predict ductal carcinoma in situ (DCIS) recurrence risk.

BACKGROUND: Breast ductal carcinoma in situ (DCIS) represent approximately 20% of screen-detected br...

A Fundamental Study Assessing the Diagnostic Performance of Deep Learning for a Brain Metastasis Detection Task.

PURPOSE: Increased use of deep convolutional neural networks (DCNNs) in medical imaging diagnosis re...

Brain Tumor Segmentation Using Convolutional Neural Networks in MRI Images.

In medical image processing, Brain tumor segmentation plays an important role. Early detection of th...

Recurrent Saliency Transformation Network for Tiny Target Segmentation in Abdominal CT Scans.

We aim at segmenting a wide variety of organs, including tiny targets (e.g., adrenal gland), and neo...

Residual convolutional neural network for predicting response of transarterial chemoembolization in hepatocellular carcinoma from CT imaging.

BACKGROUND: We attempted to train and validate a model of deep learning for the preoperative predict...

Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging.

PURPOSE: A noninvasive diagnostic method to predict the degree of malignancy accurately would be of ...

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