A wealth of data is available from electronic health records (EHR) that are collected as part
of routine clinical care in hospitals worldwide. These rich, longitudinal data offer an attractive …

Background Data provenance refers to the origin, processing, and movement of data.
Reliable and precise knowledge about data provenance has great potential to improve …

The number of papers presenting machine learning (ML) models that are being submitted to
and published in the Journal of Medical Internet Research and other JMIR Publications …

Dynamic predictive modeling using electronic health record (EHR) data has gained
significant attention in recent years. The reliability and trustworthiness of such models …

References [1] de Kok JWTM, van Bussel BCT, Schnabel R, van Herpt TTW, Driessen RGH,
Meijs DAM, et al. Table 0; documenting the steps to go from clinical database to research …

Polycystic ovary syndrome (PCOS) is a prevalent endocrine disorder in women, often
accompanied by various symptoms including significant pain, such as dysmenorrhea …

Background Electronic health records (EHRs) play a crucial role in healthcare decision-
making by giving physicians insights into disease progression and suitable treatment …

Abstract Background: Adverse drug reactions (ADRs) pose significant concerns in
healthcare, yet their underreporting remains a challenge. Extracting spontaneous and non …

Medical tabular data, abundant in Electronic Health Records (EHRs), is a valuable resource
for diverse medical tasks such as risk prediction. While deep learning approaches …

Background Automated and data-driven methods for screening using natural language
processing (NLP) and machine learning may replace resource-intensive manual …