AI-based medical imaging startup Aidoc raises a $27 million Series B
Aidoc pitches its product as a way to more quickly scan and detect potential issues in medical images.
How Nvidia is trying to overcome the barriers for AI in healthcare
Updates to the company's Clara healthcare platform are trying to make it easier for clinicians to train and adapt deep learning algorithms, while also making the implementation process smoother.
With the Rise of AI, What IP Disputes in Healthcare Are Likely to Emerge?
Munck Wilson Mandala Partner Greg Howison shared his perspective on some of the legal ramifications around AI, IP, connected devices and the data they generate, in response to emailed questions.
Dr. Eric Topol on finding the way back from the “abject failure” of EHR implementation
During a presentation at Nvidia's GTC 2019 Conference in San Jose, Topol sketched out a vision of a world where this multi-modal data is collected and assessed from "the pre-womb to the tomb" and run through clinically validated algorithms that can reveal personalized insights and aid in more accurate diagnoses.
NVIDIA expands AI radiology efforts with new software capabilities and partnerships
The company is hoping to boost the adoption of AI in medical imaging with new software development kits and deals with Ohio State University and the NIH.
Insights on big data from Optum Technology’s first Technical Fellow
In a Q&A, Optum Technology's Kerrie Holley discuses the potential of big data in healthcare, some of the barriers to adoption what can be done to win back the trust of patients.
Is AI set to transform healthcare? Not according to CIOs
Healthcare CIOs understand that without ready-access to quality data to feed AI engines, the technology is simply not going to work.
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A Personalized Approach to Medication Nonadherence
At the Abarca Forward conference earlier this year, George Van Antwerp, managing director at Deloitte, discussed how social determinants of health and a personalized member experience can improve medication adherence and health outcomes.
3 compelling use cases reveal how radiologists can use AI to help the specialty advance
AI-for-radiology advances are being developed by and in partnership with radiologists to improve physician workflows and patient care with real-time assessment, point-of-care interventions, faster exam times, and more confident diagnoses.
How computer vision will redesign healthcare
Machine learning can transform healthcare and but the interoperability barrier is the first domino that needs to fall in order to realize the full scope of its potential.
Aidoc harnesses deep learning to improve the radiologist’s workflow
The Tel Aviv, Israel-based startup is leveraging artificial intelligence and deep learning to improve the radiology workflow. Its technology pinpoints abnormalities in a medical image.
GE Healthcare, Partners embark on decade-long AI collaboration
Over a 10-year span, GE Healthcare and Partners HealthCare will be working together to bring artificial intelligence to all parts of the patient journey.
Maximize Revenue and Patient Care with Strategic Weight Loss Management
We will highlight Build My Health's revenue practice management tools, which could help physician practices add up to $250,000 to their practices.
Startup Arterys wins FDA clearance for AI-assisted cardiac imaging system
Arterys Inc.’s Cardio DL program applies artificial intelligence to automate tasks that radiologists have been performing manually.
Study: Deep learning algorithms show high accuracy for spotting diabetes retinopathy
The study underscores both the interest in developing machine learning tools for clinical decision support and making early detection of diabetic retinopathy easier.
Using deep learning and artificial intelligence to map the genome and predict disease
Deep Genomics, a new University of Toronto spinout, uses artificial intelligence and deep machine learning to try to mimic the way in which the cell works - and predict whether a person will get a disease or not.