Brigette Waldrup

The paper uses AI to analyze genomic data from colorectal cancer patients, finding TP53 pathway alterations are linked to better survival in Hispanic/Latino patients treated with FOLFOX.

AI-HOPE-MAPK identifies age- and ancestry-specific MAPK pathway alterations in colorectal cancer, revealing clinically relevant mutation patterns and survival differences.

This study examines WNT pathway alterations in early-onset colorectal cancer across different populations and treatment groups, finding ancestry-specific effects of FOLFOX chemotherapy on mutation frequencies and survival outcomes.

The paper identifies PI3K pathway alterations as a prognostic biomarker in early-onset colorectal cancer patients receiving FOLFOX and highlights ancestry-specific mutational differences using AI tools.

AI-HOPE-WNT is a conversational AI tool that integrates clinical and genomic data to analyze WNT pathway dysregulation in colorectal cancer, reproducing prior findings and uncovering novel associations.

The paper uses AI to analyze genomic and clinical data from colorectal cancer patients, finding that TGF-beta pathway alterations predict poorer survival in Hispanic/Latino patients treated with FOLFOX.

AI-HOPE-RTK-RAS enables dialogue-driven analysis of RTK-RAS alterations in CRC, revealing novel associations and ancestry-specific patterns in mutation prevalence and prognosis.

The paper introduces AI-HOPE-JAK-STAT, a conversational AI platform that integrates clinical and genomic data to analyze JAK-STAT pathway alterations in colorectal cancer, revealing survival and mutational associations across patient subgroups.

AI-HOPE-PI3K enables real-time, population-aware analysis of PI3K pathway alterations in colorectal cancer using natural language queries, revealing survival differences and ancestry-linked biomarkers.

AI-HOPE-TGFbeta is a conversational AI agent that integrates clinical and genomic data to analyze TGF-β pathway alterations in colorectal cancer, revealing population-specific patterns and clinical outcomes.

AI-HOPE-TP53 analyzes TP53-driven molecular alterations in colorectal cancer using natural language queries and clinical-genomic data to support precision oncology.

This study identifies pathway-specific molecular differences in early-onset colorectal cancer (EOCRC) between Hispanic/Latino and non-Hispanic White populations, revealing distinct genetic alterations and potential ethnicity-specific survival implications.

This study compares oncogenic pathway mutations in hepatocellular carcinoma between Hispanic/Latino and Non-Hispanic White patients, identifying ethnicity-specific alterations in key pathways.

This study identifies higher PI3K and mTOR pathway alterations in early-onset CRC among Hispanic/Latino patients compared to non-Hispanic White patients, with improved outcomes linked to TP53 alterations.

AI-HOPE-PM integrates genomic, clinical, and social determinants of health data using conversational AI to enable real-time, multi-dimensional cancer analysis and uncover disparities in outcomes.

This study identifies ethnicity-specific molecular alterations in MAPK and JAK/STAT pathways in early-onset colorectal cancer, showing higher MAPK mutations in Hispanic/Latino patients and potential prognostic implications.

This study compares molecular alterations in key cancer pathways between Hispanic/Latino and Non-Hispanic White gastric cancer patients, finding ethnic differences in mutation frequencies and prognostic significance.

This study identifies ethnicity-specific genomic alterations in pancreatic cancer pathways among Hispanic/Latino and Non-Hispanic White patients using public datasets.

This study identifies distinct molecular features of early-onset colorectal cancer in Hispanic/Latino patients through multi-omics analysis, revealing significant WNT pathway alterations and potential therapeutic targets.

This study profiles colorectal cancer in Hispanic/Latino patients, finding high genetic similarity to Peruvians-from-Lima-like populations and identifying key mutations and pathways associated with young-onset disease.