Why DIVA

The exponential growth of biomedical information far exceeds our cognitive abilities to exploit it for the prevention, diagnosis, and treatment of diseases. At the DIVA lab, we use visual analytics to discover and validate patterns in complex datasets, and translate those discoveries into computational innovations that enhance biomedical decision-making.

News

Awards: Distinguished Paper Award from AMIA Summit on Translational Bioinformatics, 2012, 2013 [News]; Rising STAR Award from UT System; Researcher of the Month, UTMB

Grants: IHII pilot grant to analyze infectious diseases; CDC/NIOSH grant to build decision-support systems for first-responders.

Publications: SNP Network Analysis published in JAMIA. CTS researcher analysis published in JMIR. Asthma Network Analysis published in JBI.

Principal Investigator

Suresh K. Bhavnani, Associate Professor, Biomedical Informatics

Mission

Discover meaningful patterns in biomedical data through visual analytics
Innovate approaches to amplify cognition and enhance decision making

Analysis of Renal Diseases and Genes in a 3D Immersive CAVE Analysis of Molecular Similarities and Differences between Renal Diseases Analysis of how Symptoms Overlap across Toxic Chemicals Design of a Decision-Support System for the Rapid Identification of Toxic Chemicals Contextual Analysis of MAIDN in a Fire Truck Analysis of Asthma Patients and Cytokines Analysis of Asthma Genotype and Phenotype Information [by Numan Oezguen] Analysis of how Interventions Co-Occur across Depression Clincal Trials Analysis of Uterine Magnetomyographic Sensor Activity in Pregnant Women Analysis of how Cancer Symptoms Co-Occur across Patients Analysis of how Cancer Symptom Severity Changes over Time Analysis of how Melanoma Facts are Scattered across Healthcare Webpages

 

 

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