KI EndoLIST: Endometriosis Longitudinal Individualized Symptoms Tracking Dataset

Endometriosis affects approximately 10% of reproductive-age women globally,
yet the time to diagnosis is four to twelve years due to clinical challenges
and the normalization of symptoms by patients and healthcare providers.
Additionally, highly diverse symptom profiles of patients lead to suboptimal
treatment approaches and prolonged patient suffering.

This unique database addresses the critical gap in curating individual
endometriosis symptoms longitudinally. Unlike periodical standardized
questionnaires, our custom-developed app allowed each of 34 Israeli
endometriosis patients to document their unique disease burden daily, using
individualized symptom sets and severity scales.

The dataset includes an onboarding patient information file, an onboarding
code dictionary, per-user longitudinal daily symptom monitoring data (and a
corresponding data dictionary), and standardized mapping of symptoms to the
Medical Dictionary for Regulatory Activities (MedDRA) for clinical
interpretation. It enables dynamic evaluation of symptom variability,
severity, and individual disease complexity at the patient level.

This dataset represents a valuable resource for researchers and clinicians
seeking to understand the true complexity of endometriosis symptom experience.
It enables examination of personalized symptom patterns and severity, with the
purpose of promoting optimized clinician-patient engagement and individualized
treatment approaches. By capturing the nuanced reality of living with
endometriosis, this dataset can inform more effective diagnostic strategies
and management protocols tailored to individual patient needs.