Oncology/Hematology

Breast Cancer

Latest AI and machine learning research in breast cancer for healthcare professionals.

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Detection of masses in mammograms using a one-stage object detector based on a deep convolutional neural network.

Several computer aided diagnosis (CAD) systems have been developed for mammography. They are widely ...

Development of deep neural network for individualized hepatobiliary toxicity prediction after liver SBRT.

BACKGROUND: Accurate prediction of radiation toxicity of healthy organs-at-risks (OARs) critically d...

A Study of Diagnostic Accuracy Using a Chemical Sensor Array and a Machine Learning Technique to Detect Lung Cancer.

Lung cancer is the leading cause of cancer death around the world, and lung cancer screening remains...

Machine learning and modeling: Data, validation, communication challenges.

With the era of big data, the utilization of machine learning algorithms in radiation oncology is ra...

The radiation oncology ontology (ROO): Publishing linked data in radiation oncology using semantic web and ontology techniques.

PURPOSE: Personalized medicine is expected to yield improved health outcomes. Data mining over massi...

Convolutional Neural Network Using a Breast MRI Tumor Dataset Can Predict Oncotype Dx Recurrence Score.

BACKGROUND: Oncotype Dx is a validated genetic analysis that provides a recurrence score (RS) to qua...

Knowledge-Based Planning for Identifying High-Risk Stereotactic Ablative Radiation Therapy Treatment Plans for Lung Tumors Larger Than 5 cm.

PURPOSE: Stereotactic ablative body radiation therapy (SABR) for lung tumors ≥5 cm can be associated...

CeO Nanoparticles-Loaded pH-Responsive Microparticles with Antitumoral Properties as Therapeutic Modulators for Osteosarcoma.

Osteosarcoma is an aggressive form of bone cancer mostly affecting young people. To date, the most e...

3-D Neural denoising for low-dose Coronary CT Angiography (CCTA).

CCTA has become an important tool for coronary arteries assessment in low and medium risk patients. ...

Immunomarker Support Vector Machine Classifier for Prediction of Gastric Cancer Survival and Adjuvant Chemotherapeutic Benefit.

Current tumor-node-metastasis (TNM) staging system cannot provide adequate information for predicti...

Framework of Computer Aided Diagnosis Systems for Cancer Classification Based on Medical Images.

Early detection of cancer can increase patients' survivability and treatment options. Medical images...

Drug response prediction by ensemble learning and drug-induced gene expression signatures.

Chemotherapeutic response of cancer cells to a given compound is one of the most fundamental informa...

Development and Application of a Machine Learning Approach to Assess Short-term Mortality Risk Among Patients With Cancer Starting Chemotherapy.

IMPORTANCE: Patients with cancer who die soon after starting chemotherapy incur costs of treatment w...

Predicting Post Neoadjuvant Axillary Response Using a Novel Convolutional Neural Network Algorithm.

OBJECTIVES: In the postneoadjuvant chemotherapy (NAC) setting, conventional radiographic complete re...

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