AI is steadily penetrating almost all industries, and healthcare is no exception. With the help of Artificial Intelligence, various problems in the medical and healthcare industry are being solved faster and at affordable costs.
While the evolution of AI seems to be going through its nascent stage, it has already shown that its future applications will have a tremendous impact on the masses. And when it comes to the healthcare industry, AI’s impact may revolutionize it in a way that we may have never thought of before.
In this article, we will take a look at various ways in which AI is significantly helping the healthcare sector at the present moment.
AI In Radiology
Image interpretation in healthcare can be very time-consuming. The ability to successfully detect abnormalities such as tumors, fractures, and infections can speed up the interpretation of hundreds of images.
For e.g. AI based lung nodule detection can find nodules 26% faster as compared to traditional manual inspection. This allows radiologists to interpret more images in a time-critical environment. The AI can also serve as a set of second eyes which may quickly identify nodules that may have gotten overlooked.
AI In Medical Field Administration
Multiple AI-based software and tools have emerged in the market such as Cohere Health and Olive AI that greatly streamline the laborious process of authorization and improve operational efficiency.
According to the McKinsey report, the use of the latest AI and Gen AI technology can help in almost 25% savings in administrative costs with a nearly 3 to 12% increase in revenue.
Then there are automatic documentation tools to record and convert doctor-patient interactions and summaries into electronic data. According to a report by Nuance, one of the leading AI player in the medical industry, there is nearly 5 5-minute reduction of time per clinician per encounter.
AI For Mental Health Diagnostics
According to a study, AI-based systems can be effective in the range of 21 to 100% for accurately diagnosing psychiatric illness. The study also opined that AI models can diagnose a whopping 90% of mental disorders with the help of questions that are extremely effective in clinical evaluation by the expert.
With the help of Predictive Analysis, experts may be able to determine mental health outcomes solely based on demographic information, treatment history, and psychosocial factors.
AI In Robotic Surgery
If you think robots will never be able to perform complex surgeries, you may be in for a surprise. According to a report from India, an AI-powered Robotic surgery was performed on a patient for knee replacement. The AI system provided real-time data, 3D imaging, and a perfect anatomical axis of the limb, allowing for superior precision that surpassed human capabilities.
AI in Clinical Trials
Clinical Trials are really expensive. Before a drug comes into the market, it goes through extensive research and development followed by clinical trials. This whole affair can cost billions of dollars for the pharmaceutical company.
Finding effective number of eligible patients for clinical trials is time consuming and challenging.
However, with the arrival of AI systems in Healthcare, results have shown that patient selection for clinical trials may get easier in future with AI embedded systems.
According to a study by Ncbi, screening time of eligible patients for drug trials took fifth of the time through AI embedded system as compared to manual eligibility screening.
The same report cites that it was easier to find nearly 24 – 50% more eligible patients for clinical trials as compared to conventional screening.
AI In Remote Patient Monitoring
AI is playing a huge role in Remote Patient Monitoring, especially for the cardiovascular segment.
The likes of Idoven opines that their AI powered solutions can enable clinicians to reduce time for ECG Interpretation. It also claims rapid rapid identification of arrhythmias and cardiac patterns.
As per Thomas M. Maddox, MD, SM, professor of medicine at BJC HealthCare, Washington University School of Medicine, remote patient monitoring will significantly help in keeping an eye on the patient’s diesease and other biometrics so that its progression or worsening can be identified at the earliest. And this can all be done without patient’s intervention.
AI In Predictive Analytics
AI can be very effective in prediction in healthcare including diagnosis, tailored treatment, risk stratification, and prognosis. When it comes to post-operative recovery, it can be very hard to predict its rate. According to a report, this can be managed effectively through AI.
Not only that, the AI system can come handy in forecasting an unexpected complication during post-operative recovery.
Predictive Analysis with AI is also enabling self-management of chronic dieseases like diabetes which has shown improvement in the patient’s quality of life.
AI In Personalized Medicine and Drug Discovery
AI is likely to play a pivotal role when it comes to personalized medicine which is also known as precision medicine. There is a growing need of precision medicine due to individual variations in genetics and lifestyle. The environment also greatly impacts how the treatment will affect the recipient.
AI can scan staggering amount of genetic data to identify specific markers associated with the dieseases. This can help the clinician to predict the susceptibility of the diesease and to select treatment plans that can be very effective for that particular patient.
It also appear that AI systems will also be used heavily for drug discovery. In 2022, Insilico Medicine completed Phase 0 clinical study for its new anti-fibrotic novel drug whose chemical composition was determined by the in-house built AI intelligence system. The AI systems can predict the chemical structure of the potential drugs that could bind to a particular target.
