10 Artificial Intelligence Applications in Health and Wellness

The healthcare sector gone through multiple challenges in the last year since the pandemic hit, and Artificial Intelligence (AI) can help healthcare professionals deal with them. Despite privacy and data integrity concerns, AI seems to be promising for managing health and wellness. Several new technologies are being made available every now and then, broadening the horizons for healthcare professionals and patients alike.

AI is rapidly transforming the processes of medical research as well as medical devices and drug manufacturing. So, how can AI be applied to the health and wellness industry? Let's look at ten ways.

1. Development Of New Vaccines

This is perhaps the most important use in the post-COVID world. Some vaccines need specific compounds, such as adjuvants (compounds that assist the immune system in warding off disease). These compounds have to be discovered after the analysis of a large number of unused compounds. AI can help with analyzing massive databases that would otherwise take a lot more time to analyze. One recent example of this is adjuvant that has been identified by Australian researchers for use in modern flu vaccines.

2. Drug Repurposing

Drug development is a complicated, time-consuming, and expensive process. On average, it is estimated that a new drug takes about $2 million and ten years to move from the development stage and get through federal approval. For this reason, one approach that many drug manufacturers take is to repurpose already-approved drugs and find new applications for them. This process requires comparing the effects and structure of unused drugs to existing treatments. AI can be of significant use in this area as it can enable researchers to select potential drug repurposing candidates in lesser time.

3. Virtual Nurses

Healthcare facilities are often in situations where they are short of staff or funds, for instance, in times of natural disasters or a pandemic. In such cases, patients may be left unattended. This may cause them to stay unaware of their condition and how they can deal with it. Medtech companies have created Virtual AI nurses that are capable of providing 24/7 bedside support. These AI nurses can utilize details from the patients' medical records to update patients about their health, provide treatment recommendations, and build personalized relationships with them.

4. Clinical Support

Treating patients requires doctors to utilize the available medical literature, especially when it comes to rare health issues. However, due to it’s large volume coupled with time constraints, healthcare professionals are often unable to fully utilize it. This can affect the quality of treatment that they can provide.

AI is capable of quickly scanning the literature and presenting it in simple language to make it easier for it to be used almost instantaneously. Several clinical support models have been created using AI to utilize this strength. These models offer unmatched clinical support to doctors and other healthcare professionals.

5. Data Extraction From Medical Records

Maintaining medical records for patients is a crucial requirement in the healthcare field because they hold important information that keeps them informed of diagnosis and treatment. With the huge number of patients and each electronic health record (EHR) containing multiple documents related to the patients' medical history and treatment plan, it is hard for healthcare professionals to extract important information quickly. AI models are useful in this area because they can quickly parse through the medical records, fish out essential information, and present it in a simple format that clinical technicians and doctors can read.

6. Prediction Of Adverse Drug Events

Adverse drug effects refer to problems caused by medicines. Healthcare professionals attempt to avoid causing adverse drug effects when they are prescribing or administering drugs. They do this by carefully selecting the drugs according to the patient's medical history. Nevertheless, sometimes problems can occur due to mistakes. On average, ADEs may lead to up to three more days in the hospital, amounting to $4 billion every year.

This problem can be solved with AI, which can quickly go through a patient's medical records and help doctors make informed decisions that don't lead to negative drug interactions. A good example of AI in action is the Parkland Memorial Hospital in Texas that used a customized AI model to identify the possibility of ADEs. They managed to prevent over 2,000 ADEs over a span of two years.

7. Improvement In Pathology

According to Jeffrey Golden, MD, Chair of the Department of Pathology at BWH and a professor of pathology at HMS, seventy percent of all decisions in healthcare are based on a pathology result. To study signs of diseases like cancer, pathologists have to spend long durations of time analyzing tissue samples. Success is measured by accuracy and time-efficiency, a department where AI has proven to be most helpful. AI models can help quickly identify tissue samples with irregularities, speeding up the process significantly.

8. Lung Cancer Screening

Doctors need to use a standard CT scan of a patient's lungs to screen for lung cancer. While this is one of the most reliable ways of detecting the cancer, it can be time consuming. There is also the risk of overexposure to dangerous levels of radiation.

AI has been helpful in this case as well. The latest AI technology in this area can speed up the screening process and refine the results of completed scans. With this technology, doctors can get the same or better results with low-dose CT scans, allowing them to make the process quicker and safer. It can help improve the tests that determine whether a cancer is progressing or is in remission, grading it on an algorithm rather than the histopathologic grade. It’s a huge advance in the medical field, one that has saved countless hours and lives.

9. Detecting Other Cancers

AI is also helpful in the detection of other types of cancer, such as breast cancer. It is not only helping refine the results but is also streamlining the diagnosis process and saving precious time. Immunotherapy is a relatively new process that is being used to help patients overcome severe cancer diagnoses. However, it is tailored to each individuals genetic make-up rather than a one size fits all.

AI has helped with machine learned algorithms that can help calculate complex data to provide options for patients. The technology and process is still in its infancy, but with the rapid progression in technology and the influx of new data its only a matter of time before the model is successfully implemented in medical institutions around the country.

10. Information Management

AI has made a significant contribution to the management of information in the healthcare sector. It has allowed systems to be more streamlined and accessible. The benefits of this include patients being able to get medical attention faster, their increased comfort, a lesser strain on the healthcare professionals, and the possibility of innovations like telemedicine.

AI is useful in another aspect here. AI-powered educational models can help doctors and other healthcare professionals boost their learning and skills by making access to knowledge and resources much quicker and simpler than ever.

There are many arenas where AI seems to be promising. As healthcare professionals and the general people become more open to giving AI technology a shot, the world will observe a significant transformation in the provision of health and wellness services. It helps reduce the biggest hurdles of time and precision, and as it moves towards an automated process the healthcare industry looks to make more progressive steps than ever before. With the coronavirus changing the world forever, more countries and organizations are investing into medical AI. The healthcare sector is constantly facing a number of challenges, and AI could be the answer.

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