Bukhari Lab Biomedical Data Science & Healthcare AI

Projects

Our Socio-technical Approach for Biomedical Content Authoring and Structured Web Publishing
Our Socio-technical Approach for Biomedical Content Authoring and Structured Web Publishing NSF Award 2101350

Balancing the speed and accuracy in structured biomedical content authoring

Ontology-based Scientific Metadata Generation
Ontology-based Scientific Metadata Generation

Public biomedical data repositories often provide web-based interfaces to collect experimental metadata. …

Reporting and connecting cell type names and gating definitions through ontologies
Reporting and connecting cell type names and gating definitions through ontologies

Human immunology studies often rely on the isolation and quantification of cell populations from an input sample based on flow cytometry and related techniques. …

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How Representative Is a SPARQL Benchmark An Analysis of RDF Triplestore Benchmarks
How Representative Is a SPARQL Benchmark? An Analysis of RDF Triplestore Benchmarks

Triplestores are data management systems for storing and querying RDF data. …

Formal representation of immunology related data with ontologies
Formal representation of immunology related data with ontologies

The Human Immunology Project Consortium (HIPC) is a multicenter collaboration between research centers performing large-scale human immunology studies that focus on profiling the human immune response to natural infection and vaccination. …

A linked data graph approach to integration of immunological data
A linked data graph approach to integration of immunological data

Systems biology involves the integration of multiple data types (across different data sources) to offer a more complete picture of the biological system being studied. …

The ADC API: a web API for the programmatic query of the AIRR Data Commons
The ADC API: a web API for the programmatic query of the AIRR Data Commons

The Adaptive Immune Receptor Repertoire (AIRR) Community is a research-driven group that is establishing a clear set of community-accepted data and metadata standards. …

Predicting 30-days All-cause Hospital Readmissions Considering Discharge-to-alternate-care-facilities
Predicting 30-days All-cause Hospital Readmissions Considering Discharge-to-alternate-care-facilities

Hospital discharge is a decision based on several data points including diagnostic, physiological, demographic and caretaker information. …

Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists
Multimodal Brain Tumor Classification Using Deep Learning and Robust Feature Selection: A Machine Learning Application for Radiologists

Manual identification of brain tumors is an error-prone and tedious process for radiologists; therefore, it is crucial to adopt an automated system. …

Statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit
Statistically rigorous deep neural network approach to predict mortality in trauma patients admitted to the intensive care unit

Trauma patients admitted to critical care are at high risk of mortality because of their injuries. …

Classification of positive COVID-19 CT scans using deep learning
Classification of positive COVID-19 CT scans using deep learning

In medical imaging, computer vision researchers are faced with a variety of features for verifying the authenticity of classifiers for an accurate diagnosis. …

A Deep Learning Approach for COVID-19 8 Viral Pneumonia Screening with X-ray Images
A Deep Learning Approach for COVID-19 8 Viral Pneumonia Screening with X-ray Images

Beginning in December 2019, the spread of the novel Coronavirus (COVID-19) has exposed weaknesses in healthcare systems across the world. …