AIMC Topic: Pilot Projects
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Predicting Post-Concussion Symptom Recovery in Adolescents Using a Novel Artificial Intelligence.
Journal of neurotrauma
Dec 3, 2020
This pilot study explores the possibility of predicting post-concussion symptom recovery at one week post-injury using only objective diffusion tensor imaging (DTI) data inputs to a novel artificial intelligence (AI) system composed of Genetic Fuzzy ...
Meningioma Consistency Can Be Defined by Combining the Radiomic Features of Magnetic Resonance Imaging and Ultrasound Elastography. A Pilot Study Using Machine Learning Classifiers.
World neurosurgery
Nov 28, 2020
BACKGROUND: The consistency of meningioma is a factor that may influence surgical planning and the extent of resection. The aim of our study is to develop a predictive model of tumor consistency using the radiomic features of preoperative magnetic re...
Aged
Male
Middle Aged
Pilot Projects
Computational Biology
Logistic Models
Support Vector Machine
Magnetic Resonance Imaging
Neural Networks, Computer
Machine Learning
Retrospective Studies
Female
Supratentorial Neoplasms
Humans
Meningioma
Elasticity Imaging Techniques
Decision Trees
Meningeal Neoplasms
Bayes Theorem
Diffusion Magnetic Resonance Imaging
Preoperative Care
Intraoperative Care
A Pilot Study on Convolutional Neural Networks for Motion Estimation From Ultrasound Images.
IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Nov 24, 2020
In recent years, deep learning (DL) has been successfully applied to the analysis and processing of ultrasound images. To date, most of this research has focused on segmentation and view recognition. This article benchmarks different convolutional ne...
Detection of multiple lesions of gastrointestinal tract for endoscopy using artificial intelligence model: a pilot study.
Surgical endoscopy
Nov 13, 2020
BACKGROUND: This study was aimed to develop a computer-aided diagnosis (CAD) system with deep-learning technique and to validate its efficiency on detecting the four categories of lesions such as polyps, advanced cancer, erosion/ulcer and varices at ...
Multiclass machine learning vs. conventional calculators for stroke/CVD risk assessment using carotid plaque predictors with coronary angiography scores as gold standard: a 500 participants study.
The international journal of cardiovascular imaging
Nov 12, 2020
Machine learning (ML)-based algorithms for cardiovascular disease (CVD) risk assessment have shown promise in clinical decisions. However, they usually predict binary events using only conventional risk factors. Our overall goal was to develop the "m...
Coronary Stenosis
Stroke
Heart Disease Risk Factors
Plaque, Atherosclerotic
Carotid Stenosis
Risk Assessment
Diagnosis, Computer-Assisted
Pilot Projects
Ultrasonography
Support Vector Machine
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Aged
Cross-Sectional Studies
Male
Middle Aged
Decision Support Techniques
Prognosis
Female
Reproducibility of Results
Humans
Machine Learning
Acceptability of Using a Robotic Nursing Assistant in Health Care Environments: Experimental Pilot Study.
Journal of medical Internet research
Nov 12, 2020
BACKGROUND: According to the US Bureau of Labor Statistics, nurses will be the largest labor pool in the United States by 2022, and more than 1.1 million nursing positions have to be filled by then in order to avoid a nursing shortage. In addition, t...
Use of Artificial Intelligence Deep Learning to Determine the Malignant Potential of Pancreatic Cystic Neoplasms With Preoperative Computed Tomography Imaging.
The American surgeon
Nov 1, 2020
BACKGROUND: Society consensus guidelines are commonly used to guide management of pancreatic cystic neoplasms (PCNs). However, downsides of these guidelines include unnecessary surgery and missed malignancy. The aim of this study was to use computed ...
The prognostic role of end-of-treatment FDG-PET/CT in diffuse large B cell lymphoma: a pilot study application of neural networks to predict time-to-event.
Annals of nuclear medicine
Oct 22, 2020
PURPOSE: To evaluate the prognostic role of end-of-treatment (EoT) FDG-PET/CT parameters in diffuse large B cell lymphoma (DLBCL), and then to explore a pilot application of Neural Networks (NN) in predicting time-to-relapse.
Population health AI researchers' perceptions of the public portrayal of AI: A pilot study.
Public understanding of science (Bristol, England)
Oct 21, 2020
This article reports how 18 UK and Canadian population health artificial intelligence researchers in Higher Education Institutions perceive the use of artificial intelligence systems in their research, and how this compares with their perceptions abo...
A comparison of the effects and usability of two exoskeletal robots with and without robotic actuation for upper extremity rehabilitation among patients with stroke: a single-blinded randomised controlled pilot study.
Journal of neuroengineering and rehabilitation
Oct 19, 2020
BACKGROUND: Robotic rehabilitation of stroke survivors with upper extremity dysfunction may yield different outcomes depending on the robot type. Considering that excessive dependence on assistive force by robotic actuators may interfere with the pat...
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