Nowadays, it seems like artificial intelligence has a place in every industry, and it is a conversation we have to have about practically every service that we use. A topic that’s oftentimes controversial, for a variety of reasons, it’s important not to forget or ignore the potential benefits that it could have, either. This is especially true of how it may be helping develop the world of healthcare in ways that could allow for more accurate and precise treatment, and even the development of new treatments. So, how is AI being used in the healthcare world?
Improved Screening For Medical Images
Medical imaging plays a huge part in how we diagnose patients in the modern medical world, with X-rays, MRIs, CT scans, and ultrasound images all used to help pinpoint symptoms and conditions. In many cases, humans are the ones reading the results of the scans, but now AI might be helping to increase the speed and quality of the process. AI analyzes these images and can flag anomalies, including the more subtle ones that the human eye might not catch as easily. These systems learn from millions of prior images, allowing them to detect early signs of cancer, cardiovascular issues, neurological conditions, and other diseases with increasingly high sensitivity. AI-powered tools can also help reduce fatigue by pre-sorting scans based on urgency.
Predictive Analytics For Diagnostics
Preventive care is a major concern for the healthcare world right now, as doctors and health organizations are fighting to reduce the rate of preventable conditions and diseases. The ability for AI to pore over vast amounts of data to develop its insights can help with this through predictive analytics. It can take data from a whole range of sources, including lab results, vitals, lifestyle data, and historical patient records, to identify early warning signs of a host of conditions. This can be used to do everything from scoring the potential for specific chronic diseases to using data to provide more precise preventative treatments, like IV hydration and nutrition treatments designed specifically for the patient’s needs.
Personalizing Their Treatment Plans
The vast amount of data, as mentioned above, can help usher in a new level of personalized medicine. While the technology is still relatively young, there are some working on tools that allow AI to do things like evaluating how patients with similar profiles respond to different treatments, as well as how genetic markers can affect medication metabolism, as well as how lifestyle factors can shape patient outcomes. With the use of these data streams, AI could help clinicians design individualized treatment plans optimized for each person’s unique biology and circumstances. It can help guide treatment choices to avoid trial-and-error, especially when dealing with complex issues such as cancer or autoimmune disorders.
Shaping Drug Development
The computing and data processing power of AI has a lot of potential when it comes to the exploration of new treatments, as well. Machine-learning models can be used to simulate the interactions of molecules, which in turn can help researchers identify promising compounds, giving them a point of focus and testing their potential effectiveness. It can pre-emptively help narrow down research candidates even before testing begins in the laboratory. AI can also be used during the clinical trial process, such as by better selecting patients and monitoring participant responses in real time. The role of AI in drug development could lead to faster development cycles, lower costs, and more innovative solutions that are able to reach the market and reach patients much sooner as a result.
Improving Hearing Health Treatment
While AI may play a much broader role in diagnosis and treatment across the medical field eventually, it’s already starting to show a lot of promise in more specific and niche fields. For instance, AI is shaping hearing health in a number of ways, such as through modern hearing aids that incorporate AI that automatically adjusts settings based on listening environments, improving speech clarity and reducing background noise more effectively than traditional algorithms. AI can also be used in the diagnostic process as well, such as processing large amounts of auditory data from hearing tests and speech recognition evaluations to highlight points of concern that a human audiologist might miss, allowing for a better idea of a patient’s hearing health when making diagnosis decisions.
Remote Monitoring And Telehealth
AI is hot on the heels of another revolutionary healthcare development: the rise of telehealth, which allows medical devices to become powerful tools for monitoring and managing all manner of health conditions. Wearables and smart sensors continuously collect data on heart rate, oxygen levels, blood glucose, sleep quality, and physical activity, which is typically sent to a medical care provider for their analysis. However, AI could soon be playing a bigger role in providing real-time analysis, reading the data to look for indicators of concerning patterns like respiratory issues or glucose fluctuations. This can help patients act on these signs sooner and get in touch with their provider to benefit from more timely interventions.
Running Things Behind The Scenes
While many of the current and potential AI applications we have explored above look at how it can directly influence the treatment of patients, it’s also worth considering the improvements it could bring to the offices that keep our healthcare services running, as well. AI is reshaping how healthcare organizations operate, improving efficiency, financial stability, and patient experience, such as with intelligent scheduling tools that reduce wait times by predicting appointment demand and optimizing clinician availability. AI can also be used, for instance, in billing systems to detect coding errors and reduce costly claim denials. Meanwhile, chatbots and virtual assistants are already being used more widely to help with admin tasks and managing front-line patient communications, allowing healthcare staff to focus on more patient-focused work.
Although it might not be quite as widespread in healthcare as it is in other industries, there are certainly potential applications of AI in our hospitals, clinics, and treatment centers that might become a lot more common as the technology continues to develop.