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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EHR voice assistant lets docs stay attentive to patients

Physicians fed up with all the time they have to spend staring at a computer screen—even when the patient is sitting right there—may find relief in the form of a talking digital assistant.

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Ultrasound-guided IV placement improves first-attempt success in children

Physicians who used ultrasound to guide the placement of intravenous (IV) lines in young patients had better first-attempt success rates than those who used traditional methods, according to a study published in the July issue of Annals of Emergency Medicine.

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AI can triage screening mammograms, save radiologists time

Using deep learning models to triage screening mammograms can improve radiologist specificity without hurting sensitivity, according to new research published in Radiology.

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Deep learning triages mammograms, reduces radiologists' workload nearly 20%

Deep learning can be used to triage cancer-free mammograms and improve the efficiency of radiologists, according to an Aug. 6 feasibility study published in Radiology.

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Ultrathin human-machine interface device could let robots touch, feel

Scientists at the University of Houston have developed a wearable device that can gather and transmit enough biometric information to go unnoticed by human wearers and could give robots a virtual sense of touch.

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Prepare for more AI at RSNA 2019

The 2019 Radiological Society of North America (RSNA) annual meeting in Chicago is expanding its artificial intelligence offerings.

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AI improves accuracy, cuts reading times associated with DBT exams

Deep learning can improve the accuracy and efficiency of digital breast tomosynthesis (DBT) examinations, according to new findings published in Radiology: Artificial Intelligence.

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Neuroimaging important for evaluating Zika-exposed infants

MRI and CT scans of infants exposed to the Zika virus in the womb revealed a range of brain abnormalities, reported authors of a recent study published in JAMA Network Open. The findings place neuroimaging as an important step in evaluating such patients.