VIST

VIST retrieves and ranks scientific publications relevant to oncological mutation profiles to support precision oncology and clinical decision-making.

Key Features:

• Targeted Search Engine: Identifies and retrieves publications directly pertinent to clinical decision-making in oncology.
• Comprehensive Indexing: Indexes PubMed abstracts and content from ClinicalTrials.gov to provide broad biomedical literature coverage.
• Advanced Text Mining: Detects mentions of genes, variants, and drugs within indexed documents.
• Machine Learning-Based Scoring: Applies machine learning algorithms to assess and score the clinical relevance of each abstract.
• Performance Evaluation: Ranking has been evaluated to outperform PubMed and traditional vector space models in identifying documents with high clinical relevance.

Scientific Applications:

• Precision Oncology: Enables retrieval of literature tailored to a patient's oncological mutation profile to support precision medicine.
• Clinical Decision Support: Aids interpretation of genomic data to inform evidence-based cancer treatment decisions.
• Research and Development: Highlights clinically significant studies to support research on disease progression and development of interventions.

Methodology:

Indexes PubMed abstracts and ClinicalTrials.gov, applies text mining to detect genes, variants, and drugs, and employs machine learning algorithms to score clinical relevance and rank results.