Methodological Precedence in Health Tech: Why ML/Big Data Analysis Must Follow Basic Epidemiological Consistency. A Case Study

arXiv — cs.LG•Wednesday, November 12, 2025 at 5:00:00 AM

The recent publication titled 'Methodological Precedence in Health Tech' underscores the critical need for basic epidemiological consistency before employing advanced analytical techniques such as Machine Learning and big data analysis in health research. The study reveals that sophisticated analyses can amplify significant methodological flaws rather than rectify them, leading to misleading conclusions. By applying standard statistical methods to a cohort study on vaccine outcomes and psychiatric events, the authors identified multiple statistically irreconcilable paradoxes, including an implausible risk reduction for chronic disorders in high-risk groups. These findings definitively invalidate reported hazard ratios and highlight that observed effects may stem from uncorrected selection biases. This case study serves as a cautionary tale for researchers, emphasizing that the integrity of foundational methodologies is paramount in ensuring the reliability of health research outcomes.

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