The Future of Artificial Intelligence in Healthcare.

The Future of Artificial Intelligence in Healthcare

AI is transforming the delivery and science of healthcare in a variety of ways. But there are a few challenges that need to be addressed before widespread use of the technology.

First is the issue of data security and compliance. This includes policies like HIPAA and GDPR that regulate how patient information is collected, stored and used.

Predictive Modeling

AI-based predictive modeling enables healthcare providers to promote disease prevention and reduce medical expenses. In fact, a recent economic study has shown that AI solutions can help a medium-sized US hospital save over $500K annually.

The underlying technology of AI is machine learning, where algorithms learn from data and then make predictions about future events. In medicine, this translates to identifying disease symptoms or predicting how patients will respond to treatment.

In drug research and development, AI can be used to comb through large amounts of data for patterns that would be difficult or impossible for humans to identify. This can significantly cut the time to market for new drugs and decrease costs.

For example, a neural network could recognize signs of Parkinson’s disease in video of a patient’s tremor, even though the patient has not revealed that information to anyone else. This raises concerns about privacy and has led to lawsuits against developers of AI healthcare applications.

Automated Decision-Making

AI can help with the administrative and technical tasks that take up a huge chunk of providers’ time. For example, it can queue up the most relevant information in patient records or distill recordings of consultations and conversations into structured data. This frees up doctors’ time for more consultation with and empathic listening to their patients, enhancing shared decision making.

In other cases, it can identify symptoms that might be ignored by medical professionals, such as a general malaise or vague physical discomfort. It can also comb through clinical notes to find relevant data and identify patterns.

AI is helping researchers to select the best candidates for clinical trials, thus speeding up the process and cutting down costs. It is also helping to detect diseases, such as cancer, more accurately and in their early stages. This allows doctors to treat patients more effectively and avoid unnecessary biopsies. Moreover, it is assisting with the identification of fraud by detecting anomalies and irregularities in data.

Prescription Error Reduction

The use of AI can help reduce prescription errors and other medical mistakes by automating tasks like reviewing medical records. It can also identify patterns and generate insights that might elude physicians’ manual efforts.

However, many Americans remain concerned that healthcare organizations and insurance companies will move too fast to implement AI technology before fully understanding its risks for patients. Similarly, they worry that the security of health records will be compromised by hackers or other threats.

Most respondents are comfortable with AI being used to diagnose disease and recommend treatments, but fewer want AI-based tools used for skin cancer screening or to perform parts of surgery. They are also concerned about the potential for AI to exacerbate inequality if it learns from accurate, representative data that reflects underlying biases and inequalities in our healthcare systems. For example, it is possible that an AI system may systematically assign fewer resources to African-American patients because of existing resource allocation disparities.

Personalized Care

One of the flashiest applications for medical AI is pushing the boundaries of what human providers can do. For example, software has been created that can detect signs of kidney injury up to two days before the problem is actually noticeable by a patient, enabling early and often preventive treatment.

Similarly, software can analyze images from mammograms to flag areas that may need further testing or could be indicative of cancer. This has cut the number of unnecessary biopsies and improved the accuracy of diagnoses.

Americans are somewhat divided on how comfortable they would be with their healthcare provider utilizing AI for personalized care. Those with some familiarity with the technology express more openness to using it for things like recommending pain medications after surgery. However, the vast majority of those not familiar with the technology say they would not want their provider to use AI in this way. Privacy concerns also come into play. Many healthcare AI developers require large datasets to develop their systems, and patients may be concerned that this data-sharing violates their privacy.

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