Guest post by Ripal Vyas, president, Softweb Solutions Inc.
The healthcare sector is one of those that has always embraced emerging technologies to make better use of technological innovations. And now artificial intelligence (AI) is gradually making its way into the healthcare market with all its power to disrupt.
The annual investment in artificial intelligence for healthcare will grow tenfold in the next five years, becoming a $6 billion industry by 2021 – estimates Frost & Sullivan. They have also forecasted that by 2025, AI systems could be involved in everything from population health management to digital avatars capable of answering specific patient queries.
In healthcare, the opportunity for AI is not just limited to making doctors and medical providers more competent in their work; in fact, it’s about saving lives and making the lives of the patients better. Whether it is for improving the standard of treatment, patient outcomes, healthful behavior, new drug development, weight loss advice or cost reduction, the possibilities of artificial intelligence in the healthcare industry are enormous.
Six amazing use cases of artificial intelligence in healthcare sector:
AI for effective treatment
Although, healthcare generates a huge amount of data due to record keeping, patient care, and compliance & regulatory requirements, it struggles to efficiently utilize the flood of data and convert it into useful insights to improve the value of care. Artificial intelligence helps in making sense of the huge data streams gathered from hospitals and health IT systems by identifying the relationships and patterns between patients, symptoms, and more to provide the right treatment at the right time.
AI for the patient’s caregivers
A lot of modern healthcare providers have adopted AI-driven apps for scanning the findings of a patient’s laboratory tests, as well as drug orders, and sending relevant updates, alerts, and reminders to patients. This application interacts with patients just as a human would to understand the mental condition of the patient and have an impact on monitoring patients when clinicians are not available. For example, AiCure is a clinically authenticated artificial intelligence platform that visually confirms whether the patient has consumed the prescribed medicines on time.
AI for smart drug development
According to figures from a Tufts University study and the U.S. Food and Drug Administration, developing a new drug costs an average of nearly $2.6 billion and can take as long as 14 years. This lengthy process covers identifying the demographic information, multi-gene interaction, proteins, environmental effects, optimizing the molecule for effective delivery to patients, carrying out clinical trials, drug efficacy testing and more. The latest innovations in AI can greatly aid in converting a drug discovery idea from initial inception to a market-ready product rapidly by predicting the therapeutic use of new drugs before they are put to test. This might sound like a small thing to some, however, for researchers it a huge one, who otherwise would have to make these predictions after conducting various tedious experiments. For example, Johnson & Johnson and Sanofi are using IBM Watson to discover new targets for FDA approved drugs.