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As defined by Merriam-Webster: "In the Middle Ages and the Renaissance, alchemists who sought to concoct the "elixir of life" (which would give eternal life) and the "philosopher's stone" (which would turn ordinary metals into gold) also labored to find the panacea. But no such medicine was ever found, just as no solution to all of a society's difficulties has ever been found. Thus, panacea is almost always used to criticize the very idea of a total solution. "

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In current times people think that machine learning is the panacea, a belief that is far from the truth. At panacea lab we aim to build machine learning, computer vision, and NLP methods that help to generate insights from multi-modal large-scale data sources. With applications to precision medicine, medical informatics, astroinformatics and other domains, our work addresses domain-specific problems with data science methods and practices. Additionally, we are fully invested in helping science reproducibility by releasing (when possible) open-source and publicly available datasets and tools to aid reproducibility efforts.

With the new challenges brought by the data deluge in all fields, we are open to collaborations. Contact us here.

Our lab is supported by: Department of Veterans Affairs (Grant 1 I01 HX002487-01) and National Institute of Aging through Stanford Universitiy's Stanford Aging & Ethnogeriatrics Transdisciplinary Collaborative Center (SAGE) center (Grant 3P30AG059307-02S1)

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R package for Automated PHenotype Routine for Observational Definition, Identification, Training and Evaluation (APHRODITE). Built the OHDSI collaborative.

Github Link

ANANKE

R package for Mapping Between OHDSI Concept Identifiers to Unified Medical Language System (UMLS). Built for the OHDSI collaborative.

Github Link

AEOLUS

A curated and standardized adverse drug event resource to accelerate drug safety research. Built for the 旋风加速器专业版下载安装

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LIDDI

Provenance-centered dataset of drug-drug interactions.

Github Link

ImageFARMER

Introducing a Data Mining Framework for the Creation of Large-scale Content-based Image Retrieval Systems

Github Link

For a other code and datasets visit the lab's github page.

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    1. All
    2. Biomedical Informatics
    3. Solar Informatics

Advances in Electronic Phenotyping: From Rule-Based Definitions to Machine Learning Models

Project Title

A large-scale solar dynamics observatory image dataset for computer vision applications

Project Title

Characterizing treatment pathways at scale using the OHDSI network

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Electronic phenotyping with APHRODITE and the Observational Health Sciences and Informatics (OHDSI) data network

Project Title

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Project Title

Regional content-based image retrieval for solar images: Traditional versus modern methods

Project Title

Provenance-Centered Dataset of Drug-Drug Interactions

Project Title

Solar Event Classification Using Deep Convolutional Neural Networks

Project Title

For a full list of publications go here.

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wallless官方网址-雷轰加速器

Principal Investigator

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CS PhD Student

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Bhaskar Ray

CS PhD Student

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MS Student

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Geeth Anirudh Suryadevara

MS Student

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Kimberly Luviano-Garcia

UAP Scholar

wallless官方网址-雷轰加速器


Contact info

25 Park Place - Suite 752,
Atlanta, GA 30303

jmbanda@panacealab.org

+1 404-413-5585

Leave us a message

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