AIMC Topic: Pilot Projects
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Investigating muscle synergies changes after rehabilitation robotics training on stroke survivors: a pilot study.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
The current knowledge about muscle synergies does not clearly explain how both rehabilitation and brain plasticity act on the way they evolve after a cortical stroke. In this preliminary study, the authors analyzed the correlation between healthy and...
A Pilot Study on Scatterer Density Classification of Ultrasound Images Using Deep Neural Networks.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Jul 1, 2020
Quantitative ultrasound estimates different intrinsic tissue properties, which can be used for tissue characterization. Among different tissue properties, the effective number of scatterers per resolution cell is an important parameter, which can be ...
Classification of Intracranial Hemorrhage Subtypes Using Deep Learning on CT Scans.
Studies in health technology and informatics
Jun 26, 2020
Intracranial hemorrhage is a pathological condition that requires fast diagnosis and decision making. Recently, a neural network model for classification of different intracranial hemorrhage types was proposed by a member of our research group Konsta...
The Classification of Scientific Literature for Its Topical Tracking on a Small Human-Prepared Dataset.
Studies in health technology and informatics
Jun 26, 2020
The number of scientific publications is constantly growing to make their processing extremely time-consuming. We hypothesized that a user-defined literature tracking may be augmented by machine learning on article summaries. A specific dataset of 67...
Efficacy of deep convolutional neural network algorithm for the identification and classification of dental implant systems, using panoramic and periapical radiographs: A pilot study.
Medicine
Jun 26, 2020
Convolutional neural networks (CNNs), a particular type of deep learning architecture, are positioned to become one of the most transformative technologies for medical applications. The aim of the current study was to evaluate the efficacy of deep CN...
Artificial intelligence in the age of cognitive endoscopy.
Gastrointestinal endoscopy
Jun 1, 2020
Natural language processing of prehospital emergency medical services trauma records allows for automated characterization of treatment appropriateness.
The journal of trauma and acute care surgery
May 1, 2020
BACKGROUND: Incomplete prehospital trauma care is a significant contributor to preventable deaths. Current databases lack timelines easily constructible of clinical events. Temporal associations and procedural indications are critical to characterize...
Deep learning-based quantitative visualization and measurement of extraperitoneal hematoma volumes in patients with pelvic fractures: Potential role in personalized forecasting and decision support.
The journal of trauma and acute care surgery
Mar 1, 2020
INTRODUCTION: Admission computed tomography (CT) is a widely used diagnostic tool for patients with pelvic fractures. In this pilot study, we hypothesized that pelvic hematoma volumes derived using a rapid automated deep learning-based quantitative v...
Texture analysis and machine learning algorithms accurately predict histologic grade in small (< 4 cm) clear cell renal cell carcinomas: a pilot study.
Abdominal radiology (New York)
Mar 1, 2020
PURPOSE: To predict the histologic grade of small clear cell renal cell carcinomas (ccRCCs) using texture analysis and machine learning algorithms.
Consumer health information and question answering: helping consumers find answers to their health-related information needs.
Journal of the American Medical Informatics Association : JAMIA
Feb 1, 2020
OBJECTIVE: Consumers increasingly turn to the internet in search of health-related information; and they want their questions answered with short and precise passages, rather than needing to analyze lists of relevant documents returned by search engi...
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