Faced with ongoing U.S healthcare reform that forces hospitals to bear financial risk for patient outcomes, Partners Healthcare should embrace the power of machine learning to cut costs and improve quality of care
Machine learning has the power to fundamentally reinvent healthcare. In a world where industries have been radically transformed by technology – we watch technology finally slowly, but steadily disrupt healthcare delivery. Ready to meet your AI doctor?
Roche, the Swiss pharmaceuticals giant, is caught in a race against time. After making a big bet on breakthrough drugs and personalized medicine, the company has spent much of the last 18 months thinking ahead to the challenges that machine learning and artificial intelligence pose to a traditional, integrated pharmaceutical business model.
Many U.S. physicians feel that health care digitization has created serious headaches with limited benefits for patients. Will machine learning soon change their minds? Partners HealthCare, a health care system that oversees two world-class Boston hospitals, certainly thinks so.
3-D printing of cellular structures is changing the way we trial preclinical pharmaceuticals and consider the future of organ transplants.
Machine learning and artificial intelligence are looming disruptors in the field of radiology. What are leading health systems doing to tackle this issue?
Through industry partnerships, a 200 million life database, and the use of artificial intelligence (AI), Optum Labs is confronting the daunting cost and quality challenges facing the U.S. health care system
Will developing countries with lack of data and problems of affordability be able to benefit from AI in healthcare? And how?
Google AI researchers use machine learning to predict risk factors for cardiovascular disease using photographs of the retina.
The introduction of artificial intelligence to healthcare has sent shockwaves through the system with the promise of dramatic increases in quality of care and organizational efficiencies coupled with much needed cost reductions. The promise of AI in healthcare predicts a futuristic world where machines are primary and human doctors are secondary. The reality is tempered by the many challenges facing the widespread adoption of AI in US hospitals. A review of the adoption of IBM Watson Health at Memorial Sloan-Kettering Cancer Center provides a case study.
