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Healthcare is quickly becoming one of the most critical industries that AI is expected to transform.
FREMONT, CA: Artificial Intelligence is infiltrating everyday lives in far more ways than it seems. AI is transforming the digital experiences and our lives in various industry, from automotive to finance. One sector is expected to benefit immensely from AI, affecting the daily lives more than any other, and it is the healthcare sector.
The field of AI research in medicine is rapidly expanding. In 2016, more money was invested in healthcare AI ventures than in any other area of the global economy. This exponential growth can be attributed to several factors, including the growing acceptance of big-data solutions and the need for technical solutions to adapt healthcare to crises like the COVID-19 pandemic.
AI will assist medical professionals such as surgeons, nurses, and medical technicians in detecting early signs of illness and empowering them to offer even more advantages to their patients. In the AI Healthcare area, at least three trends are identified.
Electronic Health Records (EHRs)
The first trend may not appear to be directly linked to AI, but it is the most significant because it influences others. Electronic Health Records (EHRs) are digital records of a patient's medical history, treatments, and health journey over time, like a digital version of a doctor's notes.
There are several record-keeping standards currently in use, but the most well-known, FHIR (Fast Healthcare Interoperability Resources), is quickly becoming the preferred protocol for companies such as Google. One of its aims is to make it easier for legacy healthcare systems to connect with one another so that medical professionals and individuals can get information quickly.
The field of early diagnosis prediction is another important area where AI can and is already revolutionizing healthcare. This field entails utilizing Machine Learning models to predict the onset of a disease or even before it manifests.
These models rely on broad datasets to accurately capture the underlying relationships between certain patient features, like age and current conditions, and the progression of the target disease.
Finally, with the help of these ML-based models, several companies have started to develop solutions that enable patients to receive care similar to that is provided in a hospital without having to leave their home.