AzMed reçoit l'autorisation de la FDA pour une solution de détection des fractures pédiatriques alimentée par l'IA

First, by identifying subtle signals, AI reduces diagnostic uncertainty. Classic problem areas include faint pleural lines, hairline rib fractures, small cortical breaks, and barely perceptible lung nodules. These patterns can be consistently identified at scale by algorithms trained on large, labeled datasets. That improves lesion conspicuity so findings are not overlooked, but it does not eliminate the need for clinical context.

As evidências já sugerem que a IA pode melhorar significativamente o desempenho diagnóstico e, ao mesmo tempo, reduzir a carga de trabalho. À medida que os algoritmos aprendem com dados mais diversificados dos pacientes, espera-se que a precisão atinja um valor preditivo negativo quase perfeito, permitindo que os médicos se concentrem em julgamentos complexos que as máquinas não conseguem replicar.

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Europe’s hospitals are ageing along with their citizens. The share of people over 65 has already reached 21% and is forecast to approach 30% by 2050 [1]. Chronic diseases rise in tandem, while staff shortages deepen. Health-care professionals spend more than half of the time they devote to patient care working inside electronic health records rather than with patients [1].

AI, the study argues, is no longer optional. Even “low-hanging-fruit” applications—triage queues, smart worklists, ambient clinical scribes—can reclaim hours, cut burnout, and widen access to expertise beyond city hospitals [1]. Yet uptake crawls, hamstrung by fragmented rules, outdated servers and, above all, mistrust.

Those obstacles are precisely what Brussels has started to clear.

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