Healthcare is one of the central areas for Machine Learning (ML). Deep learning is mainly used for the analysis of X‑ray images and in magnetic resonance and computer tomography. Anonymous patient data supports clinical diagnostics as well as applications in radiology, pathology and dermatology.
Currently, ML techniques already allow the detection of breast cancer, heart disease, osteoporosis and the first signs of skin cancer. It is expected that in the near future such systems will be able to detect pandemics at an early stage and take timely preventive measures. In addition, the first service robots for nursing support are being developed.
The prerequisite and particular challenge lies in compliance with data protection regulations, in particular in the use of patient data, but also in the transparency of the systems and not least in user acceptance. More about this in today’s use case about the importance of data for the pharmaceutical industry and for clinical studies.