Hematology

Lymphoma

Latest AI and machine learning research in lymphoma for healthcare professionals.

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A Deep Learning Prognosis Model Help Alert for COVID-19 Patients at High-Risk of Death: A Multi-Center Study.

Since its outbreak in December 2019, the persistent coronavirus disease (COVID-19) became a global h...

A Novel Intelligent Computational Approach to Model Epidemiological Trends and Assess the Impact of Non-Pharmacological Interventions for COVID-19.

The novel coronavirus disease 2019 (COVID-19) pandemic has led to a worldwide crisis in public healt...

Early prediction of neoadjuvant chemotherapy response for advanced breast cancer using PET/MRI image deep learning.

This study aimed to investigate the predictive efficacy of positron emission tomography/computed tom...

Leveraging multi-way interactions for systematic prediction of pre-clinical drug combination effects.

We present comboFM, a machine learning framework for predicting the responses of drug combinations i...

Intensity non-uniformity correction in MR imaging using residual cycle generative adversarial network.

Correcting or reducing the effects of voxel intensity non-uniformity (INU) within a given tissue typ...

Comparison of 11 automated PET segmentation methods in lymphoma.

Segmentation of lymphoma lesions in FDG PET/CT images is critical in both assessing individual lesio...

A deep learning diagnostic platform for diffuse large B-cell lymphoma with high accuracy across multiple hospitals.

Diagnostic histopathology is a gold standard for diagnosing hematopoietic malignancies. Pathologic d...

Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer.

We apply for the first-time interpretable deep learning methods simultaneously to the most common sk...

Impact of chronic intermittent hypoxia on the long non-coding RNA and mRNA expression profiles in myocardial infarction.

Chronic intermittent hypoxia (CIH) is the primary feature of obstructive sleep apnoea (OSA), a cruci...

Machine learning to predict early TNF inhibitor users in patients with ankylosing spondylitis.

We aim to generate an artificial neural network (ANN) model to predict early TNF inhibitor users in ...

Risks of Muscle Atrophy in Patients with Malignant Lymphoma after Autologous Stem Cell Transplantation.

OBJECTIVE: Muscle atrophy is associated with autologous stem cell transplantation (ASCT)-related out...

Differentiation of low and high grade renal cell carcinoma on routine MRI with an externally validated automatic machine learning algorithm.

Pre-treatment determination of renal cell carcinoma aggressiveness may help guide clinical decision-...

Deep learning predicts short non-coding RNA functions from only raw sequence data.

Small non-coding RNAs (ncRNAs) are short non-coding sequences involved in gene regulation in many bi...

A fast and fully-automated deep-learning approach for accurate hemorrhage segmentation and volume quantification in non-contrast whole-head CT.

This project aimed to develop and evaluate a fast and fully-automated deep-learning method applying ...

Analysis of Visuo Motor Control between Dominant Hand and Non-Dominant Hand for Effective Human-Robot Collaboration.

The human-in-the-loop technology requires studies on sensory-motor characteristics of each hand for ...

Prediction and prioritization of autism-associated long non-coding RNAs using gene expression and sequence features.

BACKGROUND: Autism spectrum disorders (ASD) refer to a range of neurodevelopmental conditions, which...

Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras.

Live sheep export has become a public concern. This study aimed to test a non-contact biometric syst...

Robotic versus open oncological gastric surgery in the elderly: a propensity score-matched analysis.

Although there is no agreement on a definition of elderly, commonly an age cutoff of ≥ 65 or 75 year...

Automated stroke lesion segmentation in non-contrast CT scans using dense multi-path contextual generative adversarial network.

Stroke lesion volume is a key radiologic measurement in assessing prognosis of acute ischemic stroke...

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