Methodology
Illness Researcher uses a systematic approach to transform medical research articles into actionable health recommendations. Here's how we process the data:
Article Collection
We aggregate open-access research articles from CORE, the world's largest collection of open-access research papers, focusing on medical and health-related publications.
Relevance Screening
Each article is screened for relevance using AI. We look for research about actionable health recommendations including diet, supplements, lifestyle actions, and warning signs. Articles about drug side effects or medication interactions are excluded.
Study Quality Assessment
Articles are classified by study type (e.g., systematic review, randomized controlled trial, cohort study). Only studies meeting a minimum evidence quality threshold are included. Meta-analyses and systematic reviews receive the highest confidence scores.
Knowledge Extraction
AI extracts specific recommendations from each article, identifying the illness, the recommended action (diet, supplement, action, or red flag), and the supporting evidence including sample sizes, effect sizes, and statistical significance.
Evidence Summarization
When multiple studies support the same recommendation, the evidence is synthesized into a concise summary. This includes aggregate statistics across studies and highlights consistent findings.
Important Notes
- We prioritize high-quality evidence (systematic reviews, meta-analyses, RCTs) but include other study types with appropriate confidence indicators.
- This is not medical advice. Always consult a healthcare professional before making health decisions.
- We continuously update our database as new research becomes available.