Oncology/Hematology

Other Cancers

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

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Detection of flat colorectal neoplasia by artificial intelligence: A systematic review.

OBJECTIVES: This study review focuses on a deep learning method for the detection of colorectal lesi...

PathoNet introduced as a deep neural network backend for evaluation of Ki-67 and tumor-infiltrating lymphocytes in breast cancer.

The nuclear protein Ki-67 and Tumor infiltrating lymphocytes (TILs) have been introduced as prognost...

Feasibility of automatic detection of small hepatocellular carcinoma (≤2 cm) in cirrhotic liver based on pattern matching and deep learning.

Early detection of hepatocellular carcinoma (HCC) is crucial for clinical management. Current studie...

Use of Endoscopic Images in the Prediction of Submucosal Invasion of Gastric Neoplasms: Automated Deep Learning Model Development and Usability Study.

BACKGROUND: In a previous study, we examined the use of deep learning models to classify the invasio...

Analysis of Tumor Microenvironment Characteristics in Bladder Cancer: Implications for Immune Checkpoint Inhibitor Therapy.

The tumor microenvironment (TME) plays a crucial role in cancer progression and recent evidence has ...

A deep learning model for the classification of indeterminate lung carcinoma in biopsy whole slide images.

The differentiation between major histological types of lung cancer, such as adenocarcinoma (ADC), s...

Latent Correlation Representation Learning for Brain Tumor Segmentation With Missing MRI Modalities.

Magnetic Resonance Imaging (MRI) is a widely used imaging technique to assess brain tumor. Accuratel...

Jaya Ant lion optimization-driven Deep recurrent neural network for cancer classification using gene expression data.

Cancer is one of the deadly diseases prevailing worldwide and the patients with cancer are rescued o...

A review and comparison of breast tumor cell nuclei segmentation performances using deep convolutional neural networks.

Breast cancer is currently the second most common cause of cancer-related death in women. Presently,...

Tens of images can suffice to train neural networks for malignant leukocyte detection.

Convolutional neural networks (CNNs) excel as powerful tools for biomedical image classification. It...

Magnetic tri-bead microrobot assisted near-infrared triggered combined photothermal and chemotherapy of cancer cells.

Magnetic micro/nanorobots attracted much attention in biomedical fields because of their precise mov...

Impact of image compression on deep learning-based mammogram classification.

Image compression is used in several clinical organizations to help address the overhead associated ...

Estimation of tumor parameters using neural networks for inverse bioheat problem.

BACKGROUND AND OBJECTIVE: Some types of cancer cause rapid cell growth, while others cause cells to ...

Diagnosis of cholangiocarcinoma from microscopic hyperspectral pathological dataset by deep convolution neural networks.

This paper focuses on automatic Cholangiocarcinoma (CC) diagnosis from microscopic hyperspectral (HS...

Ability of artificial intelligence to detect T1 esophageal squamous cell carcinoma from endoscopic videos and the effects of real-time assistance.

Diagnosis using artificial intelligence (AI) with deep learning could be useful in endoscopic examin...

Role of AI and Histopathological Images in Detecting Prostate Cancer: A Survey.

Prostate cancer is one of the most identified cancers and second most prevalent among cancer-related...

Predicting cell invasion in breast tumor microenvironment from radiological imaging phenotypes.

BACKGROUND: The abundance of immune and stromal cells in the tumor microenvironment (TME) is informa...

An integrated deep learning and dynamic programming method for predicting tumor suppressor genes, oncogenes, and fusion from PDB structures.

Mutations in proto-oncogenes (ONGO) and the loss of regulatory function of tumor suppression genes (...

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