Martin Schoenthaler1, Martin Boeker2,3, Petar Horki2,3. 1. Department of Urology. 2. Institute of Medical Biometry and Statistics. 3. Tumor Center Freiburg (CCCF), Medical Center - University of Freiburg, Faculty of Medicine, University of Freiburg, Germany.
Abstract
PURPOSE OF REVIEW: To elucidate the keywords big data and artificial intelligence and corresponding literature in the field of urolithiasis. RECENT FINDINGS: Numbers of publications on big data and artificial intelligence in the field of urolithiasis are rising, but still low. Most publications describe the development, testing, and validation of automated computational analyses of clinical data sets and/or images in a preclinical setting. SUMMARY: In the field of digital health services, there is a discrepancy between the enormous commitment of large private companies and investments of public funds. This situation means a still small number of medical publications on this topic in the urolithiasis field. Nevertheless, as doctors and scientists, we should try to provide our patients with secure and worthwhile digital services.
PURPOSE OF REVIEW: To elucidate the keywords big data and artificial intelligence and corresponding literature in the field of urolithiasis. RECENT FINDINGS: Numbers of publications on big data and artificial intelligence in the field of urolithiasis are rising, but still low. Most publications describe the development, testing, and validation of automated computational analyses of clinical data sets and/or images in a preclinical setting. SUMMARY: In the field of digital health services, there is a discrepancy between the enormous commitment of large private companies and investments of public funds. This situation means a still small number of medical publications on this topic in the urolithiasis field. Nevertheless, as doctors and scientists, we should try to provide our patients with secure and worthwhile digital services.