Artificial intelligence in healthcare

Artificial intelligence (AI) is reshaping the healthcare sector in unimaginable ways. The role of AI in healthcare has been of substantial importance. The 21st century marked the era of innovation and transformation with convergence towards technology and medical algorithms powered by AI.

 AI has redefined the patient-physician relationship and also saved the healthcare industry.  According to Harvard and McKinsey the healthcare industry can save 360 billion dollars annually in the USA if AI is adopted across healthcare widely. Like any technology AI also has some ethical and social dilemmas with some limitations.

In this article, different applications of AI in healthcare will be discussed along with the challenges it can pose.

Pros of AI in Healthcare

From managing disease to preventive care AI is the answer to all problems the health system faces today.

Here are some advantages and applications of AI in advancing health services.

1. Early diagnosis

Machine learning (ML) is an area of AI that uses input data as a resource to combat the difficulties of diagnosing a disease. ML along with deep learning and CNN ( convolutional neural network) can help in identifying key disease detection patterns among large databases. Consequently, with early diagnosis using ML, AI can provide with best and customised treatment of disease.

AI has improved diagnostic accuracy, saved our time and reduced healthcare costs. Through AI medical algorithms and cryptocurrency payment methods, clinical workflow has been streamlined. You can settle your medical bills through tether payment for uninterrupted medical care. This unlikely duo of AI and cryptocurrency has changed the landscape of precise diagnosis and on-time treatment.

2. Predictive analytics

Predictive analytics are used to identify a disease before it comes to the surface. It predicts the future risks for patients of developing chronic diseases. Predictive analytics uses AI and ML along with data modeling and mining. During data analysis different factors of patients are accessed such as lifestyle and medical history. Apart from that, social health factors and demographics are also taken into consideration.

AI uses its algorithm to analyze large amounts of data which is otherwise not possible for human analysts. Data analysis can predict patients at higher risk of readmission to the hospital and early interventions can help prevent readmission. This can greatly reduce hospital costs and help improve patient health.

3. Establishing guidelines and frameworks

AI can help reduce the knowledge gap between the theoretical and practical worlds. It assists in mining information by relating real-world patients with data based on clinical trials. After mining the next step is establishing guidelines. AI algorithms work under the observation of experts and scientists and analyze large amounts of data to recognize a pattern for making guidelines based on evidence.

The guidelines presented by the AI algorithm include recommendations and data-centric insights that can eventually lead to minimum damage, reduced knowledge gaps, preferable outcomes, and efficient decision-making.

4. Telemedicine and AI

Telemedicine is a remote mode of healthcare services from physician to patient through technology and electronic means of communication. The synergy between AI and telemedicine has done wonders for clinicians by effectively interpreting images and making on-time diagnoses. Smartphones have played a vital role in the remote treatment of diseases by supporting AI deep learning.

Especially during COVID-19 AI-equipped applications were developed to analyze the voice or coughing of patients for detection of infection. Many wearable devices such as smartwatches are equipped with AI to monitor the vital signs of patients. AI chatbots have even reduced the need for a physician and can be used for screening potential patients without clogging the hotlines.

Limitations of AI in healthcare

With all the power that comes with AI, it is not without the pitfalls. According to Statista a survey in 2023 showed that 33 percent of healthcare professionals from the USA thought AI would do more harm than help.

Some noteworthy cons of AI in the health sector are as follows

1. Privacy and security breach

AI collects a large amount of data about personal health and it can be misused or exposed if not properly handled. AI after all a technology and is prone to cyberattacks hence breaches of personal medical data.

Cyber attacks can be countered or avoided by pre-emptive measures and predictive analysis for early detection of breaches.

2. Ethical and societal dilemmas

What if AI makes a false diagnosis which results in a life-death situation for the patient? Who is going to be responsible for this? These are the ethical concerns and there are no rules set for it. AI can generate data that can be unfair toward some genders and races or environmental factors. It can trigger disparity and bias.

While healthcare workers follow some codes of conduct before employment. There are no laws and authority for AI applications that’s why AI crime can easily occur. There is a need for proper regulation authority for crimes or false diagnoses done by AI.

Wrapping up

One might think AI will occupy the jobs of healthcare providers but this will not happen as long as ethical dilemmas are there. AI has proven to be helping patients despite the downsides and there are fewer cases of occupational burnout in physicians. AI has the potential to revolutionize the medical field but there is only a need for some regulatory authorities for its application.

DISCLAIMER – “Views Expressed Disclaimer: Views and opinions expressed are those of the authors and do not reflect the official position of any other author, agency, organization, employer or company, including NEO CYMED PUBLISHING LIMITED, which is the publishing company performing under the name Cyprus-Mail…more