Oncology/Hematology

Other Cancers

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

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Towards More Accurate Automatic Sleep Staging via Deep Transfer Learning.

BACKGROUND: Despite recent significant progress in the development of automatic sleep staging method...

Liver fibrosis staging by deep learning: a visual-based explanation of diagnostic decisions of the model.

OBJECTIVES: Deep learning has been proven to be able to stage liver fibrosis based on contrast-enhan...

Exploration of machine learning techniques to examine the journey to neuroendocrine tumor diagnosis with real-world data.

Machine learning reveals pathways to neuroendocrine tumor (NET) diagnosis. Patients with NET and a...

Role of Regulatory Non-Coding RNAs in Aggressive Thyroid Cancer: Prospective Applications of Neural Network Analysis.

Thyroid cancer (TC) is the most common endocrine malignancy. Most TCs have a favorable prognosis, wh...

Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis.

BACKGROUND: COVID-19 is one of the greatest threats to human beings in terms of health care, economy...

Multi-Features-Based Automated Breast Tumor Diagnosis Using Ultrasound Image and Support Vector Machine.

Breast ultrasound examination is a routine, fast, and safe method for clinical diagnosis of breast t...

Deep Learning for Malignancy Risk Estimation of Pulmonary Nodules Detected at Low-Dose Screening CT.

Background Accurate estimation of the malignancy risk of pulmonary nodules at chest CT is crucial fo...

MRI and CT bladder segmentation from classical to deep learning based approaches: Current limitations and lessons.

Precise determination and assessment of bladder cancer (BC) extent of muscle invasion involvement gu...

Machine learning based differentiation of glioblastoma from brain metastasis using MRI derived radiomics.

Few studies have addressed radiomics based differentiation of Glioblastoma (GBM) and intracranial me...

Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care.

In a time of rapid advances in science and technology, the opportunities for radiation oncology are ...

Discovery of primary prostate cancer biomarkers using cross cancer learning.

Prostate cancer (PCa), the second leading cause of cancer death in American men, is a relatively slo...

Artificial intelligence could alert for focal skeleton/bone marrow uptake in Hodgkin's lymphoma patients staged with FDG-PET/CT.

To develop an artificial intelligence (AI)-based method for the detection of focal skeleton/bone mar...

Differential diagnosis of benign and malignant vertebral fracture on CT using deep learning.

OBJECTIVES: To evaluate the performance of deep learning using ResNet50 in differentiation of benign...

Esophageal cancer detection based on classification of gastrointestinal CT images using improved Faster RCNN.

PURPOSE: Esophageal cancer is a common malignant tumor in life, which seriously affects human health...

Role of deep learning in brain tumor detection and classification (2015 to 2020): A review.

During the last decade, computer vision and machine learning have revolutionized the world in every ...

Dual energy CT image prediction on primary tumor of lung cancer for nodal metastasis using deep learning.

Lymph node metastasis (LNM) identification is the most clinically important tasks related to surviva...

Knowledge-infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine.

The automated capability of generating spatial prediction for a variable of interest is desirable in...

Predicting nodal metastases in papillary thyroid carcinoma using artificial intelligence.

BACKGROUND: The presence of nodal metastases is important in the treatment of papillary thyroid carc...

Learning deep features for dead and living breast cancer cell classification without staining.

Automated cell classification in cancer biology is a challenging topic in computer vision and machin...

A deep learning system to diagnose the malignant potential of urothelial carcinoma cells in cytology specimens.

BACKGROUND: Although deep learning algorithms for clinical cytology have recently been developed, th...

Deep learning for predicting COVID-19 malignant progression.

As COVID-19 is highly infectious, many patients can simultaneously flood into hospitals for diagnosi...

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