The most critical industry in the US and the world

The Healthcare sector is among the most critical industry in the US and the world generally. Artificial intelligence plays a significant role in solving issues related to healthcare systems. The chapter has clearly defined artificial intelligence, essential in healthcare systems, and the challenges concerned with its adaptations. Some of the applications of Ai in healthcare include early diagnostics of diseases, managing electronic health records, surgeries, imaging and screening, dermatology, and medical development, among others. Artificial intelligence components include learning, reasoning, problem-solving, perception, and language understanding. Artificial intelligence comprises reactive AI, self-aware AI, theory of mind, and limited memory AI. When it comes to analytical thinking and problem-solving (mainly when dealing with massive volumes of data), artificial intelligence outperforms humans hands down, and it can effectively overcome the limits of human function. Nonetheless, the use of artificial intelligence in healthcare must consider or offset the possible loss of critical medical abilities if AI is overused. Furthermore, even when using deep machine learning, inflexible algorithm methods and decision-making trees are prone to the repercussions of AI’s incapacity to completely take in and comprehend contextual information and distinguish between relevant and non-relevant informational input. In healthcare, contingencies are the norm. Experts must carefully evaluate the human ability necessary to negotiate and handle these off-nominal or unforeseen events against the benefits of adopting artificial intelligence technologies. User interface and data input techniques are crucial since speech recognition and interpretations are vital obstacles when it comes to AI use. The fact that many care and treatment decisions, particularly in emergent and time-limited scenarios, rely on human thought activities that happen in the subconscious, like intuition, insight, personal perception, and the assessment of unclear or qualitative data, creates generalized challenges to the application of artificial intelligence in healthcare.

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