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Stem Cell Research

Latest AI and machine learning research in stem cell research for healthcare professionals.

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Reinforcement learning-based control of tumor growth under anti-angiogenic therapy.

BACKGROUND AND OBJECTIVES: In recent decades, cancer has become one of the most fatal and destructiv...

DeephESC 2.0: Deep Generative Multi Adversarial Networks for improving the classification of hESC.

Human embryonic stem cells (hESC), derived from the blastocysts, provide unique cellular models for ...

Hybrid Rehabilitation Therapies on Upper-Limb Function and Goal Attainment in Chronic Stroke.

This study examined the treatment effects between unilateral hybrid therapy (UHT; unilateral robot-a...

Radiation Therapy Quality Assurance Tasks and Tools: The Many Roles of Machine Learning.

The recent explosion in machine learning efforts in the quality assurance (QA) space has produced a ...

Robot-assisted Therapy for the Upper Limb after Cervical Spinal Cord Injury.

Tetraplegia resulting from cervical injury is the most frequent neurologic category after spinal cor...

Robotic weeders can improve weed control options for specialty crops.

Specialty crop herbicides are not a priority for the agrochemical industry, and many of these crops ...

A motor learning therapeutic intervention for a child with cerebral palsy through a social assistive robot.

Children with cerebral palsy have difficulty to sit, stand, walk, run and jump independently. Thera...

Simultaneous spatiotemporal tracking and oxygen sensing of transient implants in vivo using hot-spot MRI and machine learning.

A varying oxygen environment is known to affect cellular function in disease as well as activity of ...

Plasmonic MoO nanoparticles incorporated in Prussian blue frameworks exhibit highly efficient dual photothermal/photodynamic therapy.

Development of near infrared (NIR) light-responsive nanomaterials for high performance multimodal ph...

Electroconvulsive Therapy Induces Cortical Morphological Alterations in Major Depressive Disorder Revealed with Surface-Based Morphometry Analysis.

Although electroconvulsive therapy (ECT) is one of the most effective treatments for major depressiv...

Artificial intelligence and the radiologist: the future in the Armed Forces Medical Services.

Artificial intelligence (AI) involves computational networks (neural networks) that simulate human i...

A feasibility study for predicting optimal radiation therapy dose distributions of prostate cancer patients from patient anatomy using deep learning.

With the advancement of treatment modalities in radiation therapy for cancer patients, outcomes have...

Building Moral Robots: Ethical Pitfalls and Challenges.

This paper examines the ethical pitfalls and challenges that non-ethicists, such as researchers and ...

Defining ethical standards for the application of digital tools to population health research.

There is growing interest in population health research, which uses methods based on artificial inte...

A review on machine learning methods for in silico toxicity prediction.

In silico toxicity prediction plays an important role in the regulatory decision making and selectio...

Machine learning in suicide science: Applications and ethics.

For decades, our ability to predict suicide has remained at near-chance levels. Machine learning has...

Machine learning-based radiomic models to predict intensity-modulated radiation therapy response, Gleason score and stage in prostate cancer.

OBJECTIVE: To develop different radiomic models based on the magnetic resonance imaging (MRI) radiom...

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