Artificial Intelligence
Healthcare is seen as an area in which AI may be gainfully deployed to improve medical care, especially with big data, exponential computing power and a burgeoning demand on healthcare systems due to ageing populations.
While it cannot solve all problems in healthcare, the ubiquitous nature of technology in every aspect of modern living implies that it is now easier for doctors to care for a larger number of patients with the aid of AI.
According to Frost and Sullivan’s report on Artificial Intelligence & Cognitive Computing Systems in Healthcare in 2015, Artificial Intelligence (AI) as a group of technologies has the potential to improve outcomes by 30 to 40 percent while cutting treatment costs by as much as 50 percent. Even with the moderation of these estimates, it exceeds the best performance of a 23 percent increase in productivity with management optimization.
The increased availability of Electronic Health Records (EHR) and the popularization of machine learning methods in recent years catalyzed a technological revolution in healthcare using Big Data and advanced analytics. Concurrently, technological advancements in Natural Language Processing (NLP), deep neural networks and speech recognition applied to healthcare have spurred innumerable innovations in new services such as telehealth and virtual care services.
These technologies have already permeated other industries such as finance and transport and are set to be long-cycle technology disruptors as they provide enormous savings in operational efficiencies and increased customer satisfaction. This has driven the early adoption of these technologies in healthcare aimed at bringing a higher quality of care through personalized medicine.
The potential for healthcare AI can best be seen in how clinicians, researchers, data scientists, and engineers are now working together to solve health challenges. Keeping this in mind, the following are the key objectives of Artificial Intelligence core:
• Develop and implement models to predict complex diseases
• Develop and implement models to predict rare disease
• Develop and implement models to increase the efficiency of clinical screening
• Develop and implement models to augment doctor’s decision-making process
• Optimize the clinical and non-clinical workflow
• Optimize the health care resources to improve patient care and to reduce cost
AI Researchers: