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[Three decades ago, LAM was launched with the goal of providing scientific information about medicine and its frontiers. From the very beginning, LAM has also concerned a special subject area while connecting medicine with the world of art. In the palette of medical articles, it remained a special feature to this day. The analysis of the history of LAM to date was performed using internationally accepted publication guidelines and scientific databases as a pledge of objectivity. We examined the practice of LAM if it meets the main criteria, the professional expectations of our days, when publishing contents of the traditional printed edition and its electronic version. We explored the visibility of articles in the largest bibliographic and scientific metric databases, and reviewed the LAM's place among the Hun­ga­rian professional journals. Our results show that in recent years LAM has gained international reputation des­pite publishing in Hungarian spoken by a few people. This is due to articles with foreign co-authors as well as references to LAM in articles written exclusively by foreign researchers. The journal is of course full readable in the Hungarian bibliographic databases, and its popularity is among the leading ones. The great virtue of the journal is the wide spectrum of the authors' affiliation, with which they cover almost completely the Hungarian health care institutional sys­tem. The special feature of its columns is enhanced by the publication of writings on art, which may increase Hungarian and foreign interest like that of medical articles.]

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[What has Go to do with making clinical decisions? One of the greatest intellectual challenges of bedside medicine is making decisions under uncertainty. Besides the psychological traps of traditionally intuitive and heuristic medical decision making, lack of information, scarce resources and characteristics of doctor-patient relationship contribute equally to this uncertainty. Formal, mathematical model based analysis of decisions used widely in developing clinical guidelines and in health technology assessment provides a good tool in theoretical terms to avoid pitfalls of intuitive decision making. Nevertheless it can be hardly used in individual situations and most physicians dislike it as well. This method, however, has its own limitations, especially while tailoring individual decisions, under inclusion of potential lack of input data used for calculations, or its large imprecision, and the low capability of the current mathematical models to represent the full complexity and variability of processes in complex systems. Nevertheless, clinical decision support systems can be helpful in the individual decision making of physicians if they are well integrated in the health information systems, and do not break down the physicians’ autonomy of making decisions. Classical decision support systems are knowledge based and rely on system of rules and problem specific algorithms. They are utilized widely from health administration to image processing. The current information revolution created the so-called artificial intelligence by machine learning methods, i.e. machines can learn indeed. This new generation of artificial intelligence is not based on particular system of rules but on neuronal networks teaching themselves by huge databases and general learning algorithms. This type of artificial intelligence outperforms humans already in certain fields like chess, Go, or aerial combat. Its development is full of challenges and threats, while it presents a technological breakthrough, which cannot be stopped and will transform our world. Its development and application has already started also in the healthcare. Health professionals must participate in this development to steer it into the right direction. Lee Sedol, 18-times Go world champion retired three years after his historical defeat from AlphaGo artificial intelligence, be­cause “Even if I become the No. 1, there is an entity that cannot be defeated”. It is our great luck that we do not need to compete or defeat it, we must ensure instead that it would be safe and trustworthy, and in collaboration with humans this entity would make healthcare more effective and efficient. ]