The Growing Impact of Artificial Intelligence (AI) in Healthcare

Our world is continually changing, and one form of technology that plays an increasingly growing role in this change is Artificial Intelligence (AI). For most people, AI is probably a technical term that they do not believe applies to them, but what so many individuals do not realize is the considerable impact AI has on each of our lives and even on our day-to-day activities.

From sending out emails to scrolling through social media, ordering groceries online, or using a car service, all these actions require the presence of AI solutions to be performed. With the aid of artificial intelligence algorithms, user experience on these platforms has become highly advanced. An area in which AI has seen rapid growth is in healthcare, as the existence of Artificial Intelligence Solutions in Healthcare has become integral. Additionally, the ongoing pandemic has accelerated digital health care adoption. According to Insider Intelligence, spending on AI in medicine will grow at an annual rate of 48% between 2017 and 2023.

AI presence in healthcare means there is a rising fear that AI healthcare technology may surpass the ability of humans to perform specific tasks. There is no doubt that where AI solutions can provide support, such as managing treatments, clinical decisions, etc., the human ability may not meet the mark.

AI in Healthcare

Artificial Intelligence (AI) in healthcare can play different roles. With the help of AI Solutions, doctors and practitioners can use databases on the web to access diagnostic resources otherwise not accessible. It is no doubt that these doctors and practitioners are already so knowledgeable in healthcare. However, AI solutions allow them to stay up to date with new research carried out.

With AI presence in healthcare combined with the clinical knowledge they already have, these doctors and practitioners put AI healthcare technology to good use and gain better and more efficient results.

That is not to say that AI presence in healthcare comes without its problems. Artificial intelligence solutions can carry out the tasks so well, making humans redundant in specific tasks. The same is true for AI in healthcare, as the need for humans in this field may be reduced with access to AI. However, the research that has been carried out on this subject has suggested the opposite. Data shows that it is more likely that Artificial Intelligence (AI) in healthcare will not decrease clinical needs but instead enhance the diagnostics and decision-making processes.

Let us take a typical example that can result in a delayed diagnosis. Sometimes a patient can come to a doctor and present multiple symptoms that can suggest that they suffer from many conditions. When AI steps in, this process is made much faster. It provides practitioners with the data they need to help them accurately diagnose, develop treatment plans, have a firmer stance on the outcome prediction, and even aid them in early detection.

AI can learn from the data, which, in turn, results in more accurate results in the future based on the given feedback. This feedback comes from various sources, such as the input given from doctors and practitioners, research organizations, etc. Artificial Intelligence (AI) in healthcare carries out its processes in real-time, so the data is constantly updated, ensuring the accuracy of the information.

Data is a compilation of different medical sources such as medical notes, medical device recordings, images from the laboratory, physical examinations, etc.  Before AI, every MRI or scan, or x-ray was required to be reviewed by doctors. Now, AI can detect some clear cases because the model has been trained on a ton of data and coached on what the MRI or scan with tumor looks like. This clearly shows the impact of AI on healthcare and the way it impacts it.

AI Healthcare Technology

The amount of data present and needs to be sorted through makes healthcare workers reliant on artificial intelligence solutions. Artificial intelligence (AI) in healthcare works is to sort through the information to learn from it and form a network based on the data. The types of data present in this field are structured and unstructured data. Structured data can be divided into Machine Learning Techniques (ML), a Neural Network system, and Modern Deep Learning. At the same time, unstructured data utilizes Natural Language Processing (NLP). Let us take a further look at some of these techniques.

Machine Learning Techniques is a form of AI healthcare technology that utilizes algorithms to bring forth a patient’s particular traits. This includes all the data collected upon a patient’s visit to their doctor. For example, the results of exams, medications they are being prescribed, symptoms they are experiencing, etc., can contribute to the gathered data. Using ML, patient outcomes can be determined.

Many medical companies are focusing on using machine learning to make breakthroughs in the field of pathology. They are using AI-Powered technology to find more efficient, fast, and reliable drug development and diagnosis methods.

Additionally, companies are now developing clinical and non-clinical AI powered workflow solutions for radiology diagnosis with deep learning medical tools. These tools analyze unstructured medical data such as blood test results, images, medical history data, etc. to instruct doctors the best possible treatment for a patient.

Another form of AI in healthcare is Natural Language Processing, a technique that uses unstructured data gathered in a clinical environment. This data includes clinical notes and speech that is documented on a patient’s visit to a practitioner. Narratives are included from physical examinations, reports from laboratory visits, etc. With this data, along with a previous database that includes relevant keywords relating to diseases, doctors and practitioners are aided in making a diagnosis. These processes enable doctors and practitioners to provide their patients with a more accurate diagnosis, save time, and speed up treatment processes.

Conclusion: AI Presence In Healthcare

AI in health care has become a resource that is essential as it can help with early diagnosis of diseases and their treatment, especially in the case of patients with health issues relating to cardiovascular, cancer, and neurological disorders, all of which are the leading causes of death. With artificial intelligence (AI) in healthcare, the early detection that has become possible brings about many benefits both for patient and practitioner.

Conclusively, in this article, we have focused on all the large-scale ways AI solutions can aid healthcare. That is not to say that even on a smaller scale, AI is not making its mark. From home implementation to hospital use, AI has become an essential tool in healthcare as it enables doctors and practitioners to provide better care for their patients.

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