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• W3174124519 abstract "The relationship between artificial intelligence and medicine has a long history. Artificial intelligence initially set out to replicate human reasoning starting with explicit “if then else” rules. One of the most interesting results dates back to the 1970s with the MYCIN system based on a set of 600 rules entered by physicians able to recommend antibiotic treatments. This direction, although promising, implied a long input process, a difficult consistency check and was computationally too heavy. These methodologies have continued over the years with episodes of small successes and large failures until it was realized that the way forward was to train artificial systems starting from real examples, through a methodology called machine learning and in particular deep learning. The direction was to start from digital model of the human brain based on artificial neurons, synapses and axons. Early work involves recognizing of cancer cells from histological images hand-annotated by physicians. Artificial neural networks are trained showing the artificial neural networks hundreds of “raw” bit by bit images so that the machine automatically learns how to identify (sometimes with superhuman performance) cancer cells in new, unannotated images. The path has then been laid out, with successful new applications ranging from diagnostics, drug development, effects of treatments predicting, patient classification, DNA analysis, personalized medicine, including robotics for surgery, and the construction of artificial prostheses to support patients with disabilities. In this content, it is increasingly important to manage big data without forgetting issues of privacy and anonymization. Of great importance are also new methodologies able to analyze texts and extract information automatically, thus allowing the integration of information of different nature and type, but also techniques usefull to manage uncertainty and lack of data, a phenomenon very often present in this domain. In this talk we focus on the recent trends and successes of artificial intelligence in the medical field, with practical examples in which artificial intelligence supports physicians in their work, without forgetting current and future challenges and opportunities, at scientific, application, business but also regulatory level, in an increasingly hybrid world where humans and artificial intelligence will increasingly interact to improve the quality of life and well-being of people. Keywords: Bioinformatics; Computational and Systems Biology No conflicts of interests pertinent to the abstract." @default.
• W3174124519 created "2021-07-05" @default.
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• W3174124519 date "2021-06-01" @default.
• W3174124519 modified "2023-09-25" @default.
• W3174124519 title "ARTIFICIAL INTELLIGENCE AND MEDICINE: PAST AND FUTURE" @default.
• W3174124519 doi "https://doi.org/10.1002/hon.7_2879" @default.
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