You can download our latest newsletter here. We are launching our webinar series for this academic year. The purpose of this webinar is to foster a dialogue exploring clinical, ethical and technological opportunities and challenges associated with the use of technology to promote aging, and to introduce different perspectives at the intersection of informatics and gerontology.
View ResourcePennAITech Resources
March 5, 2023
by
Ray
The overarching goal of the Technology Identification and Training Core is to use evidence from the literature, stakeholder and expert inputs to identify the technology needs of older Americans, as well as develop training activities for artificial intelligence (AI) and technology for scientists, engineers, clinicians, medical professionals, patients, policy makers, and investors.
View ResourcePennAITech Youtube Channel
March 5, 2023
by
Ray
The overarching goal of the Penn Artificial Intelligence and Technology (PennAITech) Collaboratory for Healthy Aging is to identify, develop, evaluate, commercialize, and disseminate innovative technology and artificial intelligence (AI) methods and software to support older adults and those with Alzheimer’s Disease (AD) and Alzheimer’s Disease and Related Dementias (ADRD) in their home environment. The Collaboratory is motivated by the need for a comprehensive pipeline from technology-based monitoring of older adults in the home, collection and processing monitoring data, integration of those data with clinical data from electronic health records, analysis with cutting-edge AI methods and software, and deployment of validated AI models at point of care for decision support. We share PennAITech videos (e.g., webinars, call for applications) in this youtube channel.
View ResourcePhysiological Detection and Monitoring of Alzheimer’s Disease
March 5, 2023
by
Ray
Using wireless dry-sensor EEG wearables and an AI-based neural algorithms to detect early-stage AD/ADRD
Awardee Organization(s): Cogwear LLC
Principal Investigator(s): David Yonce, MS, MBA
Official Project Title: Physiological Detection and Monitoring of Alzheimer’s Disease
AITC Partner: PennAITech
Website(s): www.cogweartech.com
PRECISE
September 1, 2022
by
Nursing ITS
The PRECISE (Penn Research In Embedded Computing and Integrated Systems Engineering) Center was established in 2008 to bring together experts from the electrical systems engineering and computer science fields to study the way machines interact with the physical world through their computing systems, aka Cyber-Physical Systems (CPS) and the Internet of Things (IoT). CPS and IoT work has a direct, powerful impact on healthcare, energy, and transportation – all essential and important facets of modern society.
View ResourceProgram for Diversity and Inclusion (PDI)
March 5, 2023
by
Ray
IDEAL MEd supports the educational mission of the Perelman School of Medicine by promoting an inclusive, welcoming, supportive and socially engaged medical student community, while cultivating an equitable student experience.
View ResourceRandom Forests (StatQuest)
March 5, 2023
by
Ray
Random Forests make a simple, yet effective, machine learning method. They are made out of decision trees, but don’t have the same problems with accuracy. In this video, I walk you through the steps to build, use and evaluate a random forest.
View ResourceRelief-based Algorithm Training Environment (REBATE)
March 5, 2023
by
Ray
This package includes a scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning. These Relief-Based algorithms (RBAs) are designed for feature weighting/selection as part of a machine learning pipeline (supervised learning). Presently this includes the following core RBAs: ReliefF, SURF, SURF*, MultiSURF*, and MultiSURF. Additionally, an implementation of the iterative TuRF mechanism and VLSRelief is included. It is still under active development and we encourage you to check back on this repository regularly for updates. These algorithms offer a computationally efficient way to perform feature selection that is sensitive to feature interactions as well as simple univariate associations, unlike most currently available filter-based feature selection methods. The main benefit of Relief algorithms is that they identify feature interactions without having to exhaustively check every pairwise interaction, thus taking significantly less time than exhaustive pairwise search.
View Resource
RGBd+ Thermal Computer Vision Platform for Home Monitoring and Telehealth
March 5, 2023
by
Ray
Combining AI-enabled RGBd+ stereo vision and thermal sensors for home monitoring and telehealth
Awardee Organization(s): Bestie Bot
Principal Investigator(s): Richard Everts
Official Project Title: RGBd+ Thermal Computer Vision Platform for Home Monitoring and Telehealth
AITC Partner: PennAITech
Website(s): www.bestiebot.com
Rule-Based Machine Learning
March 5, 2023
by
Ray
A collection of educational videos focusing on rule-based machine learning and/or the more specific family of ‘learning classifier system’ machine learning algorithms. These algorithms are uniquely able to detect, model, and characterize complex multivariate associations in data while yielding much more interpretable models.
View Resource