AutoML Systems For Medical Imaging

Due to developments in electronic medical records and medical imaging technology, the healthcare industry has witnessed a significant increase in the volume of medical data [1, 2]. This enormous growth in medical data has made it a great tool for enhancing medical diagnosis and therapy. Unfortunately, healthcare practitioners frequently confront difficulties in evaluating and utilizing this huge amount of data effectively. In potential lead exposure at the zip code level is predicted using machine learning on patients' Blood Lead Levels (BLL) dataset. Machine learning provides a way to automate the interpretation and analysis of medical data, including medical images, by recognizing patterns within the information [3].