@Achille Goerger My Six-Month Cancer Research Journey Over the past six months, I began an in-depth cancer research project using Grok. I opened a dedicated long-term conversation and systematically asked nearly 300 questions to understand cancer mechanisms, detection technologies such as microfluidic biochips and CTC analysis, and global epidemiology challenges. While Grok provided structured explanations, the complexity of oncology required extensive manual clarification and iteration. I then shifted focus to data collection, where I discovered that global cancer statistics were highly fragmented across sources, with inconsistent years, formats, and mostly country-level data only. Using Excel’s Power Query, I merged multi-year incidence, mortality, and prevalence data from dozens of sources into a unified structure. I standardized country names, cancer types, and fields, then built a three-layer database: raw CSV as the foundation, Excel for processing and cleaning, and Power BI with DAX for dynamic analysis and visualization. To overcome the limitation of country-level data, I used complex formulas to simulate city-level insights by integrating hospital resources and population indicators. Supporting metrics such as cure rates, recurrence, and treatment methods were linked to each cancer type for greater accuracy. The major breakthrough occurred when I combined Claude AI with coding capabilities. This hybrid approach reduced my overall research time and effort by more than half compared to relying on Grok alone, allowing faster data integration and deeper exploration of complex cancer topics.