Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

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Algorithm predicts speech outcomes after cochlear implant

An algorithm developed by researchers at the Chinese University of Hong Kong has accurately predicted speech improvement in children who use cochlear implants (CIs). Findings were published in the Proceedings of the National Academy of Sciences of the United States of America.

Mayo Clinic, Corindus Vascular Robotics team up to develop 'telestenting'

Corindus Vascular Robotics and Mayo Clinic have partnered to conduct a preclinical study meant to evaluate the viability of “telestenting,” having a remote clinician complete a robot-assisted percutaneous coronary intervention (PCI).

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AI system IDs, sorts bacteria in blood infections by type

Microbiologist at the Beth Israel Deaconess Medical Center (BIDMC) in Boston have developed an artificial intelligence system capable of detecting blood infections to assist in diagnosis. Findings are published in the Journal of Clinical Microbiology.

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Deep learning AI IDs diabetic retinopathy, eye diseases using retinal images

Researchers have developed a deep learning system (DLS) using artificial intelligence (AI) capable of identifying diabetic retinopathy and related eye diseases using retinal images, according to a study published in JAMA. The system's performance was comparable to human graders.

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Machine learning model could accelerate drug discovery

Researchers from the University of Warwick have developed a machine learning model capable of predicting the interactions between proteins and drug molecules with 99 percent accuracy. Findings have been published in Science Advances.

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Improving cloud computing, machine learning with Google

Google has introduced a suite of new partnerships utilizing the power of cloud computing and machine learning to advance the field of diagnostic imaging. Presentations were given at the annual meeting of the Radiological Society of North America (RSNA) in Chicago.

AI robot passes medical licensing exam

An artificial intelligence-powered robot in China has taken and passed the national medical licensing exam.

Bioengineered Robotic Hand With Its Own Nervous System Will Sense Touch

The sense of touch is often taken for granted. For someone without a limb or hand, losing that sense of touch can be devastating. While highly sophisticated prostheses with complex moving fingers and joints are available to mimic almost every hand motion, they remain frustratingly difficult and unnatural for the user. This is largely because they lack the tactile experience that guides every movement. This void in sensation results in limited use or abandonment of these very expensive artificial devices. So why not make a prosthesis that can actually "feel" its environment?  

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A modest proposal to rally AI regulators around a simple game plan

As debate simmers over how best to regulate AI, experts continue to offer guidance on where to start, how to proceed and what to emphasize. A new resource models its recommendations on what its authors call the “SETO Loop.”