Artificial Intelligence (AI) Applications in Healthcare

AI is being used in healthcare and other industries for the same reasons: streamline tasks, improve operational efficiencies and simplify complex procedures.? Here are some AI applications being developed and deployed in the healthcare sector

1-Providing Real Time Data

With AI, doctors and other medical professionals can leverage immediate and precise data to expedite and optimize critical clinical decision-making. Generating more rapid and realistic results can lead to improved preventative steps, cost-savings and patient wait times.

Real time analytics?can help improve physician-patient relationships. Making vital patient data available through mobile devices can engage patients in their treatments. Mobile alerts can inform doctors and nurses of urgent changes in patient statuses and emergencies.

2-Streamline Tasks

AI in medicine?has already changed healthcare practices everywhere. Innovations include appointment-scheduling, translating clinical details and tracking patient histories. AI is enabling healthcare facilities to streamline more tedious and meticulous tasks. For example, intelligent radiology technology is able to identify significant visual markers, saving hours of intense analysis. Other automated systems exist to automate appointment scheduling, patient tracking and care recommendations.

3-Saving Time and Resources

It’s estimated around $200 billion is wasted in the healthcare industry annually. A good portion of these unnecessary costs are attributed to administrative tasks, such as filing, reviewing and resolving accounts. Another area for improvement is in medical necessity determination. Hours of reviewing patient history and information are traditionally needed to properly assess medical necessity. New Natural Language processing and deep learning (DL) algorithms can assist physicians in reviewing hospital cases and avoiding denials.

4-Assists Research

AI enables researchers to amass large swaths of data from various sources. The ability to draw upon a rich and growing information body allows for more effective analysis of deadly diseases. Related to real-time data, research can benefit from the wide body of information available, as long as it’s easily translated. AI has also been used to assess and detect symptoms earlier in an illness’s progression.?Telehealth solutions?are being implemented to track patient progress, recover vital diagnosis data and contribute population information to shared networks.

The other side of AI usage is its limitations.

1-Needs Human Surveillance

AI has been around for a few decades and continues to mature. As this area advances, there is more interaction between healthcare professionals and tech experts. AI requires human input and review to be leveraged effectively. For example, surgery robots operate logically, as opposed to empathetically. Health practitioners may notice vital behavioral observations that can help diagnose or prevent medical complications.

2-Inaccuracies Are Still Possible

Medical AI depends heavily on diagnosis data available from millions of catalogued cases. In cases where little data exists on particular illnesses, demographics, or environmental factors, a misdiagnosis is entirely possible. This factor becomes especially important when prescribing particular medicine.

3-Susceptible to Security Risks

As AI is generally dependent on data networks, AI systems are susceptible to security risks. As AI uses data to make systems smarter and more accurate, cyberattacks will incorporate AI to become smarter with each success and failure, making them more difficult to predict and prevent. Once damaging threats out-maneuver security defenses, the attacks will be much more challenging to address.

Despite some of the challenges and limits AI faces, this innovative technology promises extraordinary benefits to the medical sector. Whether a patient or physician, lives everywhere are improving thanks to AI.

Ed Cardon

EPC Search International LLC

470-345-0846

[email protected]