Stem Cell Research

Deep Learning for Automated Contouring of Primary Tumor Volumes by MRI for Nasopharyngeal Carcinoma.

Background Nasopharyngeal carcinoma (NPC) may be cured with radiation therapy. Tumor proximity to critical structures demands accuracy in tumor delineation to avoid toxicities from radiation therapy; however, tumor target contouring for head and neck radiation therapy is labor intensive and highly variable among radiation oncologists. Purpose To construct and validate an artificial intelligence (A...

A modality-adaptive method for segmenting brain tumors and organs-at-risk in radiation therapy planning.

In this paper we present a method for simultaneously segmenting brain tumors and an extensive set of organs-at-risk for radiation therapy planning of glioblastomas. The method combines a contrast-adaptive generative model for whole-brain segmentation with a new spatial regularization model of tumor shape using convolutional restricted Boltzmann machines. We demonstrate experimentally that the meth...

Swarm-Fuzzy Rule-Based Targeted Nano Delivery Using Bioinspired Nanomachines.

Cooperative navigation and swarm decision making take center stage in a broad range of distributed applications with high-environmental and measuremen...

Medical ethics considerations on artificial intelligence.

Artificial intelligence (AI) is currently one of the mostly controversial matters of the world. This article discusses AI in terms of the medical ethi...

Deep Learning Neural Networks Highly Predict Very Early Onset of Pluripotent Stem Cell Differentiation.

Deep learning is a significant step forward for developing autonomous tasks. One of its branches, computer vision, allows image recognition with high ...

Use of artificial neural networks to identify the predictive factors of extracorporeal shock wave therapy treating patients with chronic plantar fasciitis.

The purpose of our study is to identify the predictive factors for a minimum clinically successful therapy after extracorporeal shock wave therapy for...

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 numerous potential applications. They have great p...

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-assisted therapy [RT] + modified constraint-induced...

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 do not have access to effective herbicides. High-v...

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. Therapy is an important factor in improving these aspec...

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 various therapeutics. For transient structures, wh...

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 phototherapy within a single nanoplatform is still c...

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

Artificial intelligence (AI) involves computational networks (neural networks) that simulate human intelligence. The incorporation of AI in radiology ...

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 improved, but at the cost of increased treatment ...

Building Moral Robots: Ethical Pitfalls and Challenges.

This paper examines the ethical pitfalls and challenges that non-ethicists, such as researchers and programmers in the fields of computer science, art...

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 intelligence. Such research draws on a range of clinic...

Intensity-modulated radiation therapy of anal squamous cell carcinoma: Relationship between delineation quality and regional recurrence.

BACKGROUND AND PURPOSE: Intensity-modulated radiation therapy (IMRT) is currently indicated to treat anal squamous cell carcinoma (ASCC). Conformal do...

Demarcating the membrane damage for the extraction of functional mitochondria.

Defective mitochondria have been linked to several critical human diseases such as neurodegenerative disorders, cancers and cardiovascular disease. Ho...

Predictors of Nodal and Metastatic Failure in Early Stage Non-small-cell Lung Cancer After Stereotactic Body Radiation Therapy.

INTRODUCTION/BACKGROUND: Many patients with early stage non-small-cell lung cancer (ES-NSCLC) undergoing stereotactic body radiation therapy (SBRT) de...

Project INSIDE: towards autonomous semi-unstructured human-robot social interaction in autism therapy.

This paper describes the INSIDE system, a networked robot system designed to allow the use of mobile robots as active players in the therapy of childr...