RxNorm provides normalized names for clinical drugs and links its names to many of the drug vocabularies commonly used in pharmacy management and drug interaction software, including those of First Databank, Micromedex, Multum, and Gold Standard Drug Database. By providing links between these vocabularies, RxNorm can mediate messages between systems not using the same software and vocabulary.
View ResourceSemi-automated Term Harmonization Pipeline
This repository includes a set of Python-based Jupyter notebooks that comprise a semi-automated term harmonization pipeline applied to harmonize medical history terms across 28 clinical trials of pulmonary arterial hypertension. These notebooks pair with the paper ‘A Semi-Automated Term Harmonization Pipeline Applied to Pulmonary Arterial Hypertension Clinical Trials’. Below, we offer an overview of these pipelines and provide guidance for users on how to adapt these notebooks to their own target harmonization tasks.
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Simple, Transparent, End-to-end Automated Machine Learning Pipeline (STREAMLINE)
STREAMLINE is an end-to-end automated machine learning (AutoML) pipeline that empowers anyone to easily run, interpret, and apply a rigorous and customizable analysis for data mining or predictive modeling. Notably, this tool is currently limited to supervised learning on tabular, binary classification data but will be expanded as our development continues. The development of this pipeline focused on (1) overall automation, (2) avoiding and detecting sources of bias, (3) optimizing modeling performance, (4) ensuring complete reproducibility (under certain STREAMLINE parameter settings), (5) capturing complex associations in data (e.g. feature interactions), and (6) enhancing interpretability of output. Overall, the goal of this pipeline is to provide a transparent framework to learn from data as well as identify the strengths and weaknesses of ML modeling algorithms or other AutoML algorithms.
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Smart patch and intervention system using RFID technology to prevent medical patch overdose among individuals with AD/ADRD
Awardee Organization(s): Vaaji LLC
Principal Investigator(s): Sandeep Patil, MD, PhD | William Z. Potter, MD, PhD
Official Project Title: Prevention of Patch Poisoning in Elderly Alzheimer’s Patients
AITC Partner: PennAITech
Website(s): https://vaaji.io
SNOMED
SNOMED CT is one of a suite of designated standards for use in U.S. Federal Government systems for the electronic exchange of clinical health information and is also a required standard in interoperability specifications of the U.S. Healthcare Information Technology Standards Panel. The clinical terminology is owned and maintained by SNOMED International, a not-for-profit association.
View ResourceThe Alzheimer’s Disease Neuroimaging Initiative (ADNI)
The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a longitudinal multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer’s disease (AD). Since its launch more than a decade ago, the landmark public-private partnership has made major contributions to AD research, enabling the sharing of data between researchers around the world.Data from several dementia studies complementary to ADNI are also available through the IDA. These include the DoD-ADNI study, which measures the effects of traumatic brain injury and post-traumatic stress disorder on Alzheimer’s disease in veterans, and the AIBL study (Australian Imaging Biomarkers and Lifestyle Study of Aging).
View ResourceThe Alzheimer’s Disease Sequencing Project (ADSP)
This dataset includes sequencing data and harmonized phenotypes from cohorts sequenced by the Alzheimer’s Disease Sequencing Project and other AD and Related Dementia’s studies. Samples are processed using a common workflow called VCPA (Variant Calling Pipeline and data management tool), a functionally equivalent CCDG/TOPMed pipeline.
View ResourceThe Gene Ontology Resource
The Gene Ontology (GO) knowledgebase is the world’s largest source of information on the functions of genes. This knowledge is both human-readable and machine-readable, and is a foundation for computational analysis of large-scale molecular biology and genetics experiments in biomedical research.
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The Inclusion, Diversity, Anti-Racism, and Equity in Neurology (IDARE Neurology) Program
The mission IDARE is to create and sustain a diverse, inclusive, and antiracist culture that ensures equitable treatment of patients and of all members of the department of Neurology at the University of Pennsylvania.
View ResourceTranslational Centers of Excellence (TCE) in Neurology
The department of Neurology is committed to be a center of excellence and innovation dedicated to the pursuit of curing neurologic diseases through compassionate, patient-centered care, transformative research and education of the future leaders in neurology. The Department of Neurology has setup Translational Centers of Excellence (TCE). The goal of the TCE program is to support pilot projects to accelerate high impact areas, uniquely suited to the Department of Neurology, aiming towards self-sustainability. Four TCEs are currently active and two more will be added soon.
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