{"id":4599,"date":"2022-05-04T08:33:37","date_gmt":"2022-05-04T06:33:37","guid":{"rendered":"https:\/\/trentinosalutedigitale.com\/blog\/2022\/05\/04\/lai-per-la-sanita-cosa-ci-aspetta\/"},"modified":"2022-08-11T12:18:48","modified_gmt":"2022-08-11T10:18:48","slug":"lai-per-la-sanita-cosa-ci-aspetta","status":"publish","type":"post","link":"https:\/\/trentinosalutedigitale.com\/en\/blog\/lai-per-la-sanita-cosa-ci-aspetta\/","title":{"rendered":"AI for Health. What lies ahead?"},"content":{"rendered":"

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In this month’s in-depth feature, researcher\u00a0Venet Osmani helps<\/a>\u00a0us better understand why artificial intelligence is increasingly important for healthcare.Osmani<\/a>, who works in the Data Science for Health Research Unit at\u00a0Fondazione Bruno Kessler<\/a>, recently spoke at\u00a0the University of Trento seminar<\/a>\u00a0about “Predicting clinical outcomes with ethical implications, through artificial intelligence<\/em>” (his talk from minute 57<\/a>).<\/p>\n

Dr. Osmani, AI has become an integral part of our daily lives. What does that mean?<\/strong><\/em><\/p>\n

“We often interact with AI algorithms, for example Internet searches, social media or online shopping, which are all supported by AI algorithms. AI is so woven into the fabric of our daily lives that we are sometimes unaware of its existence.”<\/p>\n

Health is no exception.<\/p>\n

“AI is already revolutionizing medicine. We can find it in the exams and tests we do, through early diagnosis, prognosis, but it is also useful in increasing the efficiency of clinical resources. For example, it is widely used in intensive care units, where physicians need to make clinical decisions quickly as a result of a large amount of data generated during continuous monitoring of the patients they are treating.”<\/p>\n

Is the human brain, studies, and experience therefore not enough?<\/strong><\/em><\/p>\n

“The human brain is equipped to process large amounts of data. But processors and neural networks have better capabilities to process specific large amounts of data. AI therefore can support clinical decision making by providing clinical insights as a result of automatic processing of this data.”<\/p>\n

And how does it support clinicians?<\/strong><\/em><\/p>\n

“Our scientific work in the healthcare area has shown that machine learning algorithms can accurately estimate patient prognosis and increase efficiency in resource utilization, which also involves knowing how to prioritize health problems and thus patient care.\u00a0 However, the application of these algorithms in clinical practice raises enormous ethical concerns that require an interdisciplinary approach and exhange of views between legal, social and technical experts. The debate is ongoing, open and very lively.”<\/p>\n

> click\u00a0<\/strong>here to\u00a0review\u00a0the UniTN semina<\/strong>r<\/a>\u00a0of 14 April 2022<\/p>\n

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L'intelligenza artificiale per la sanit\u00e0: prospettive a confronto - 14\/04\/2022<\/div><\/div>
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