AI and ML algorithms are detecting signs of depression in young kids. Cardiac arrest is being predicted. Health chatbots are answering health-related questions, and helping patients manage medications. Unique AI algorithm is assisting radiologists by improving cancer detection rates.
A healthcare revolution is indeed unleashing, and AI is fast-tracking it. When we think of AI, the first thing that comes to our mind is machines and robots, just like how they show it in sci-fi movies. However, the reality is far from that, intelligence in healthcare represents a great new frontier. AI is the thing right now, and marketers are chasing it.
A study published by scientists from Weill Cornell Medicine used about 12000 pictures of human embryos that were clicked 5 days prior fertilization. These were then used to train an AI algorithm on how to tell which in vitro fertilized embryo would lead to a successful pregnancy, basis its quality.
The technology is gaining traction in many fields. Though, a bit slow to join the movement, the pharmaceutical industry has also jumped on the bandwagon and is exploring innovative ways to use this powerful technology.
From the initial screening of drug compounds to estimating the success rate of a drug, AI can prove highly beneficial to pharma. More precisely, AI may play a crucial role in drug target identification and validation. Utilizing AI in drug trials can drastically reduce the overall time it takes a drug to reach the market, after going through different stages of approvals, thus, consequently reducing the overall cost.
Likewise, it has the potential to ease the life of doctors and patients respectively. With its ability to aggregate and analyze colossal data, AI can lead to not just earlier diagnosis, but also an accurate one, again reducing the overall cost.
But, with all its development, breakthrough and efficacy, the question remains, can AI pose a threat to doctors? Well, at least for now, it surely can’t. AI and machine learning algorithms are heavily dependent on enormous amount of effective data. And this data needs human hands for its collection and human eyes for its analysis.
Besides, being entirely dependent on AI for medical statements and predictions, may not be a safe choice. What if the machine makes a false prediction due to a technical glitch? Whom to blame then? While AI can be the best source for disease detection, for treating purposes, one cannot undermine the brain of an expert.
Cognitive computing systems can prove to be a beneficial partner to clinicians. Their ability to understand questions, natural language processing, and logical output, can give them intrinsic ease of use that can simplify interactions with clinicians. AI can’t replace clinicians for sure, but it has the ability to free them from tedious paperwork so that they can focus on the components of care that only a human can take care of.
Hence, with all its potential, it is safe to say, that in its present form, AI in healthcare could be a shiny object that many are eyeing. But it goes without saying how important it is to turn this shiny object into a constructive one. It’s important to not just chase it but to explore, utilize and understand the value it will bring, and how it can change the industry into high-performing ecosystem through logical, independent decision-making.