How Is AI Used In Healthcare – Here Are 5 Powerful Real-World Examples
When it comes to our health, especially in matters of life and death, the promise of artificial intelligence (AI) to improve outcomes is very intriguing. While there is still much to overcome to achieve AI-dependent health...
Montreal-Toronto AI Startups Have Wide Range of Focus
Includes Healthcare, Biomed, Text Analysis, Legal Research, Image Analysis, Drug Discovery, Education
Canada has made a commitment for many years to the study of AI at universities across the county, and today robust business incubation...
Executive Interview: Michael Ringel, Boston Consulting Group on AI and Pharma
Impacts of AI in Pharma Seen as Potential to Lower Failure Rate for New Drug Testing, and a Redesigned Research Process from Start to Finish
Artificial intelligence and machine learning may still be decades away...
Machine Learning in Medical Imaging and Analysis
By Pawel Godula, Director of Customer Analytics, deepsense.ai.
Machine learning is useful in many medical disciplines that rely heavily on imaging, including radiology, oncology and radiation therapy.
According to IBM estimations, images currently account for up...
How 3 Companies Use AI to Forge Advances in Healthcare
When you think of artificial intelligence (AI), you might not immediately think of the healthcare sector.
However, that would be a mistake. AI has the potential to do everything from predicting readmissions, cutting human error...
Deep Learning is Seen as a Help to Cardiologists – Not a Job Threat
Applying a deep learning approach to echocardiography could save clinicians time while improving diagnostic accuracy, one Georgia-based cardiologist reported at the American College of Cardiology’s annual meeting in Orlando, this year.
Randolph P. Martin, MD,...
3 Companies Using AI to Forge New Advances in Healthcare
When you think of artificial intelligence (AI), you might not immediately think of the healthcare sector.
However, that would be a mistake. AI has the potential to do everything from predicting readmissions, cutting human error...
Big Pharma and Biotech are Betting Big on AI to Speed Drug Discovery
Developing new medicines isn’t for the faint of heart. On average, it takes about a decade of research — and an expenditure of $2.6 billion — to shepherd an experimental drug from lab to market....
Pharma’s AI Hierarchy of Needs Outlined at AI World 2018
By Allison Proffitt, Editorial Director, Bio-IT World
Why not pharma?
That was Peter Henstock’s challenge to the audiences recently at the AI World Conference & Expo in Boston. Henstock, the AI and Machine Learning lead at Pfizer, argues...
MIT Researchers Pushing Machine Learning to Speed Drug Development
Designing new molecules for pharmaceuticals is primarily a manual, time-consuming process that’s prone to error. But MIT researchers have now taken a step toward fully automating the design process, which could drastically speed things...
