AITC Consortium | Basic Information | PennAITech Awardees

AI-based device-free Wi-Fi sensing technology to assess daily activities and mobility in low-income older adults with and without cognitive impairment

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Awardee Organization(s): Viginia Commonwealth University
Principal Investigator(s): Jane Chung, PhD, RN | Eyuphan Bulut, PhD | Ingrid Pretzer-Aboff, PhD, RN
Official Project Title: A Device Free WiFi Sensing System to Assess Daily Activities and Mobility in Low-Income Older Adults With and Without Cognitive Impairment
AITC Partner: PennAITech
Website(s):
https://nursing.vcu.edu
https://egr.vcu.edu

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AITC Consortium | Basic Information | PennAITech Awardees

AI-based diagnostic clinical decision support system using collective intelligence and imitation learning to improve primary care diagnostics for older adults

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Awardee Organization(s): University of Pennsylvania
Principal Investigator(s): Gary Weissman, MD, MSHP
Official Project Title: Advancing Diagnostic Excellence for Older Adults Through Collective Intelligence and Imitation Learning
AITC Partner: PennAITech
Website(s): https://www.med.upenn.edu

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AITC Consortium | Basic Information | PennAITech Awardees

AI-driven AD/ADRD risk prediction models using explainable machine learning and bias identification and mitigation techniques to aid point-of-care clinical decision support

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Awardee Organization(s): University of Virginia | University of Pennsylvania
Principal Investigator(s): Aidong Zhang, PhD | Carol Manning, PhD | Li Shen, PhD | Mary Regina Boland, PhD, MPhil
Official Project Title: Fairness and Robust Interpretability of Prediction Approaches for Aging and Alzheimer’s Disease
AITC Partner: PennAITech
Website(s):
https://engineering.virginia.edu
https://www.cs.virginia.edu/~az9eg/website/home.html
https://www.med.upenn.edu

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AITC Consortium | Basic Information | PennAITech Awardees

AI-powered web app using computer vision to analyze knee joint space in older adults using only plain radiographs

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Awardee Organization(s): University of Georgia
Principal Investigator(s): Soheyla Amirian, PhD
Official Project Title: AI-Powered Web Application to Analyze Knee Joint Space for Aging Population
AITC Partner: PennAITech
Website(s): https://engineering.uga.edu/team_member/soheyla-amirian/

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Software | AutoML | Technology: Tools, Hardware, and Software

Auto_ML

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Auto_ML is a Python-based library designed to automate the whole machine learning process. It focuses on simplifying the model selection, feature engineering, hyperparameter tuning, data formatting, robust scaling and analytics. It supports binary and multiclass classification, regression, linear-model-esque interpretation from non-linear models, feature learning, and categorical ensembling. The package includes traditional models, as well as deep learning models, gradient boost models, and catboost models.

Link: https://pypi.org/project/auto_ml/

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