Clinical decision-making summary

Clinical decision-making

            Health specialists can use artificial intelligence in some healthcare processes to diagnose and treat patients more quickly. Medical professionals can act more rapidly and save more lives due to this. In contrast to traditional workflows, machine learning (ML) methods can assess risk faster and with far greater precision. Automating inefficient, time-consuming manual processes with these algorithms can reduce medical malpractice claims by accelerating diagnosis and eliminating diagnostic errors. Additionally, AI-enabled technologies can assemble and sift through massive amounts of clinical data, providing doctors with a broader perspective of patient populations’ health state. These technologies provide care teams with access to actionable information in real-time or near-real-time to improve care outcomes at the proper time and location significantly. By automating the gathering and analyzing the enormous amounts of data that pass inside the hospital’s walls, the whole care team can operate at peak performance.

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