Artificial Intelligence or AI applications in healthcare systems.

Artificial intelligence in healthcare is the application of artificial intelligence (AI) to analyze and understand complex medical and healthcare data. In some cases, it can exceed or augment human capabilities by providing better or faster ways to diagnose, treat, or prevent disease.

As widespread use of AI in healthcare is relatively new, research is ongoing into its application in various subdisciplines of medicine and related industries. AI programs are applied to practices such as diagnostics, treatment protocol development, drug development, personalized medicine, and patient monitoring and care. Because radiographs are the most common imaging tests conducted in radiology departments, the potential for AI to help with triage and interpretation of radiographs is particularly noteworthy.

Using AI also presents unprecedented ethical concerns related to issues such as data privacy, automation of jobs, and amplifying already existing biases. Furthermore, new technologies such as AI are often resisted by healthcare leaders, leading to slow and erratic adoption. In contrast, there are also several cases where AI has been put to use in healthcare without proper testing. Moreover, meta-studies have found that the scientific literature on AI in healthcare often suffers from a lack of reproducibility.

Let's dive into the details of AI Applications in healthcare systems:

AI in Disease diagnosis:
Accurate and early diagnosis of diseases is still a challenge in healthcare. Recognizing medical conditions and their symptoms is a complex problem. AI can assist clinicians with its data processing capabilities to save time and improve accuracy. Through the use of machine learning, artificial intelligence can be able to substantially aid doctors in patient diagnosis through the analysis of mass electronic health records (EHR). AI can help early prediction, for example, of Alzheimer's disease and dementias, by looking through large numbers of similar cases and possible treatments.

Doctors' decision making could also be supported by AI in urgent situations, for example in the emergency department. Here AI algorithms can help prioritize more serious cases and reduce waiting time. Decision support systems augmented with AI can offer real-time suggestions and faster data interpretation to aid the decisions made by healthcare professionals.