The ‘gold standard’, the best possible move, always comes from a chess computer such as Stockfish. During the live broadcast and in countless YouTube videos, renowned grandmasters commented on every move, every decision of the opponents, and discussed possible better alternatives. He made fewer mistakes than his opponent Ian Nepomniachtchi and repeatedly generated surprise with unexpected moves that the chess computer had not predicted. Magnus Carlsen won again, retaining his status as World Chess Champion. In December 2021, the World Chess Championship took place. In the following, 10 theses are developed to underly the vision described above: To understand this better, let us return to the present. In each of these fields, simulators are available that can be used to generate enormous amounts of data in order to test and improve machine-generated decisions. Learning systems initially came from the gaming industry, robotics and autonomous driving.
How did this development happen? As is often the case, such knowledge was initially developed outside of medicine. But their role has changed, especially when it comes to treating patients with common diseases and uncomplicated disease courses. Non-individual treatment recommendations for diseases no longer exist and treat-to-target strategies are not reviewed every 3–6 months, but daily to hourly. It combines existing and new data, enabling it to treat more accurately with every passing day.
If the treating rheumatologist retires, many years of experience about the individual course of the patient’s disease are not lost, but the model continues to improve. In any desired situation, the options are systematically assessed for their effectiveness and the best ones are suggested. Even in the case of non-drug treatments, such as physiotherapy or diet, the patient now receives personalised support through various algorithms.
In the meantime, it has been shown that for rheumatoid arthritis and other rheumatological disorders, the disease activity and quality of life can be better controlled with these self-learning systems (formerly called artificial intelligence) than by the rheumatologist alone. These consist of digital biomarkers, implanted or skin-integrated sensors and drug delivery systems based on microtechnology and nanotechnology, which have been used for some time in diabetes care. Many clinical decisions, such as dose adjustments of methotrexate or certain biologics, are made neither by the rheumatologist nor by the patient, but by computer systems which are more or less autonomous. For many years now, the concept of ‘shared decision making’ has looked nothing like it did in earlier times.
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