Journal of Theoretical & Computational Science
Open Access

Artificial Intelligence in the Field of Medicine

Cecilia Andrews^{* *}Correspondence: Cecilia Andrews, Department of Health and Medicine, University of Tasmania, Australia, Email:

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Introduction

A Artificial intelligence (AI) is the potential of a computer or a device robot to accomplish tasks that would normally be performed by conscious species. Here machine learning or artificial intelligence refers to creating a novel database which has the abilities of the human brain perception like learning, analysis, decision making, creation etc. Since its inception, AI research has explored and rejected a variety of methodologies, including mimicking the brain, modelling human problem solving, formal logic, massive knowledge libraries, and imitating animal behaviour. This method has proven to be quite effective in solving a variety of difficult challenges in both industry and academics.

The use of machine learning models to explore medical data and reveal insights to assist improve health outcomes and patient experiences is known as artificial intelligence in medicine.Artificial intelligence (AI) is rapidly becoming a crucial component of modern healthcare.In clinical settings and ongoing research, AI algorithms and other AI-powered apps are being used to assist medical personnel. Clinical decision support tools assist practitioners in making therapy, medicine, mental health, and other patient-related decisions by providing quick access to relevant information or research. In the present tools like X-rays, CT scan and MRI are being used for the diagnostic purpose.

In medicine, artificial intelligence can be divided into two types: virtual and physical. The virtual portion includes anything from electronic health record systems to neural network-based treatment decision help. The physical section covers robotic surgery assistants, intelligent prosthetics for handicapped persons, and senior care. With virtual AI aid, precision medicine may become easier to support. Because AI models can learn and remember preferences, AI has the ability to give patients with personalised real-time recommendations at any moment. A virtual assistant driven by artificial intelligence that might respond to queries depending on the patient's medical history, preferences, and personal needs.

Pill discovery is frequently one of the most time-consuming and expensive aspects of drug development. AI has the potential to assist lower the costs of producing new medications in two ways: by improving drug design and identifying viable novel drug combinations. Many of the life sciences industry's big data concerns could be solved using AI. AI has been used to predict the risk of cardiovascular disease, such as acute coronary syndrome and heart failure, better than traditional scales when applied to electronic medical information. Patients with diabetes can view real-time interstitial glucose measurements and get information on the direction and rate of change of their blood glucose levels with continuous glucose monitoring.

While technological discovery in generating new solutions to improve modern healthcare should remain rigorous and transparent, health policies should now focus on addressing the ethical and financial challenges linked with this cornerstone of medicine's progression. Machine intelligence is already assisting us in more effectively diagnosing diseases, developing medications, personalising therapies, and even editing genes. But this is only the start. The more we digitise and integrate our medical data, the more AI can assist us in identifying useful patterns patterns that can be used to make correct, cost-effective judgments in complex analytical procedures.