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Showing 1240-1260 of 6,118 articles

DeepHCS: Bright-field to fluorescence microscopy image conversion using multi-task learning with adversarial losses for label-free high-content screening.

In this paper, we propose a novel microscopy image translation method for transforming a bright-fiel...

Feb 2021 33640720

Deep learning-augmented radiotherapy visualization with a cylindrical radioluminescence system.

This study aims to demonstrate a low-cost camera-based radioluminescence imaging system (CRIS) for h...

Feb 2021 33361563

Forecasting influenza activity using machine-learned mobility map.

Human mobility is a primary driver of infectious disease spread. However, existing data is limited i...

Feb 2021 33563980

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer.

Natural language processing (NLP), which aims to convert human language into expressions that can be...

Feb 2021 33545300

Differentiation of Pseudoprogression from True Progressionin Glioblastoma Patients after Standard Treatment: A Machine Learning Strategy Combinedwith Radiomics Features from T-weighted Contrast-enhanced Imaging.

BACKGROUND: Based on conventional MRI images, it is difficult to differentiatepseudoprogression from...

Feb 2021 33535988

Transforming UTE-mDixon MR Abdomen-Pelvis Images Into CT by Jointly Leveraging Prior Knowledge and Partial Supervision.

Computed tomography (CT) provides information for diagnosis, PET attenuation correction (AC), and ra...

Feb 2021 32175868

Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy.

PURPOSE: Novel actuarial deep learning neural network (ADNN) architectures are proposed for joint pr...

Feb 2021 33539966

Machine Learning-Based Prediction of 6-Month Postoperative Karnofsky Performance Status in Patients with Glioblastoma: Capturing the Real-Life Interaction of Multiple Clinical and Oncologic Factors.

OBJECTIVE: Ability to thrive after invasive and intensive treatment is an important parameter to ass...

Jan 2021 33516864

Machine learning-based differentiation between multiple sclerosis and glioma WHO II°-IV° using O-(2-[18F] fluoroethyl)-L-tyrosine positron emission tomography.

INTRODUCTION: This study aimed to test the diagnostic significance of FET-PET imaging combined with ...

Jan 2021 33502678

Detecting MLC modeling errors using radiomics-based machine learning in patient-specific QA with an EPID for intensity-modulated radiation therapy.

PURPOSE: We sought to develop machine learning models to detect multileaf collimator (MLC) modeling ...

Jan 2021 33382467

A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging.

Medical ionizing radiation procedures and especially medical imaging are a non negligible source of ...

Jan 2021 33936422

Perceptions of Canadian radiation oncologists, radiation physicists, radiation therapists and radiation trainees about the impact of artificial intelligence in radiation oncology - national survey.

BACKGROUND: Artificial Intelligence (AI) is making a continuous progression into the field of Radiat...

Dec 2020 33323332

Oncology/Hematology

Browse Categories

DeepHCS: Bright-field to fluorescence microscopy image conversion using multi-task learning with adversarial losses for label-free high-content screening.

Deep learning-augmented radiotherapy visualization with a cylindrical radioluminescence system.

Forecasting influenza activity using machine-learned mobility map.

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer.

Differentiation of Pseudoprogression from True Progressionin Glioblastoma Patients after Standard Treatment: A Machine Learning Strategy Combinedwith Radiomics Features from T-weighted Contrast-enhanced Imaging.

Transforming UTE-mDixon MR Abdomen-Pelvis Images Into CT by Jointly Leveraging Prior Knowledge and Partial Supervision.

Integrating Multiomics Information in Deep Learning Architectures for Joint Actuarial Outcome Prediction in Non-Small Cell Lung Cancer Patients After Radiation Therapy.

Machine Learning-Based Prediction of 6-Month Postoperative Karnofsky Performance Status in Patients with Glioblastoma: Capturing the Real-Life Interaction of Multiple Clinical and Oncologic Factors.

Machine learning-based differentiation between multiple sclerosis and glioma WHO II°-IV° using O-(2-[18F] fluoroethyl)-L-tyrosine positron emission tomography.

Detecting MLC modeling errors using radiomics-based machine learning in patient-specific QA with an EPID for intensity-modulated radiation therapy.

A semantic database for integrated management of image and dosimetric data in low radiation dose research in medical imaging.

Solar radiation prediction using boosted decision tree regression model: A case study in Malaysia.

Deep learning magnetic resonance spectroscopy fingerprints of brain tumours using quantum mechanically synthesised data.

Real-time liver tracking algorithm based on LSTM and SVR networks for use in surface-guided radiation therapy.

DaNet: dose-aware network embedded with dose-level estimation for low-dose CT imaging.

Performance of deep learning synthetic CTs for MR-only brain radiation therapy.

Diagnostic value of deep learning reconstruction for radiation dose reduction at abdominal ultra-high-resolution CT.

Data-driven dose calculation algorithm based on deep U-Net.

Feasibility of automated planning for whole-brain radiation therapy using deep learning.

Deep learning-based real-time volumetric imaging for lung stereotactic body radiation therapy: a proof of concept study.

Perceptions of Canadian radiation oncologists, radiation physicists, radiation therapists and radiation trainees about the impact of artificial intelligence in radiation oncology - national survey.

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