Gone are the days when artificial intelligence (AI) was confined to science fiction. The usage of AI in healthcare is changing how we think about absolutely everything. Who would have thought something we can’t see could comprehend so much more than humans? It really was the stuff of movies. And no, it isn’t taking over jobs just yet. Nurses, radiologists, and healthcare assistants are all essential. And we’re sure it’ll never take over physicians, with websites like MASC Medical (mascmedical.com always advertising for positions.
But what exactly does AI mean for medicine? The following dive takes us through.
Diagnosis and Early Detection Redefined
When it comes to diagnostic accuracy and early disease detection, one of the massive impacts of AI on medicine has been its ability to enhance them.
Classic diagnosis methods may occasionally be tardy or prone to human mistakes. AI algorithms, trained on large amounts of data, can perform much quicker and with incredible precision in medical image analysis, lab result interpretation, and patient histories. Still, there’s the risk of bias and AI error, so we’re not truly there yet.
But we’re trying – AI-driven tools for detecting cancer at the earliest stages. Google’s DeepMind developed an artificial intelligence that can identify breast tumors on mammograms better than human radiologists do.
AI is also being used successfully to diagnose conditions like heart disease, diabetes, and nerve diseases.
Personalized Treatment Plans
We no longer live in a world where treatment plans are intended for everyone at large – that never went down well.
Personalized medicine is a massive trend, referring to when treatment interventions are matched with individual genetic makeup and clinical appearance. That ensures patients get the best treatment options but suffer minimal side effects.
There are also AI algorithms analyzing genetic information to predict the drug responses of particular patients. For example, IBM’s Watson for Oncology utilizes this technology to evaluate a patient’s genetic profile and determine the most favorable treatment for cancer.
AI systems are also capable of continuously learning from new information – they can adjust treatments according to the changing conditions of a patient.
Chronic illnesses have been approached from an individualized perspective, which has improved their management and resulted in better lives for patients.
Accelerating Drug Discovery
Traditionally, discovering new drugs has been a long and expensive undertaking, taking up to 10–15 years and costing billions.
In general, drug discovery involves identifying a molecular target, designing a drug to hit it, and testing it for safety and efficacy. It involves screening many possible compounds, which can be a painfully slow process. AI is doing it all, significantly reducing the time it would typically take.
For example, Insilico Medicine enrolled its first patient in phase I clinical trials of an anti-fibrotic drug for idiopathic pulmonary fibrosis (IPF), which is a disease that leads to the stiffening of lung tissue. AI-instigated molecules are targeted by the same mechanism identified by AI itself. Unbelievably, this took only thirty months compared to previous methods used, which were much slower. Although no drugs created using AI have yet been approved by the Food and Drug Administration (FDA), there are very promising prospects for faster and less expensive drug development processes.
AI is changing healthcare more than people realize. The benefits of AI are clear-cut and far-reaching despite the challenges associated with its application in medicine. It’ll be interesting to see how it changes healthcare in the future.
