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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Deep learning validated on 20K patients uses CT scans to predict cardiovascular risk

Coronary artery calcium scores generated by the system matched those manually performed by a human expert.

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$3.1M project will combine neuroimaging, AI to enhance Army battlefield training and care

Rensselaer Polytechnic Institute researchers hope to use brain activity data, along with other metrics, to enhance prolonged field care certification.

Cardiologist’s AI software tracks the health of COVID-19 patients, updating every 2 seconds

“Vital sign measurements and labs can come too late, but early detection through predictive analytics has the power to improve patients’ outcomes, especially for catastrophic illnesses like COVID-19,” the software's creator said. 

People with diabetes open to remote digital monitoring; more concerned about intrusiveness than AI per se

One turnoff is remote food monitoring. Another is real-time feedback—whether from a live healthcare professional or an AI algorithm.

One of AI’s leading lights discovers the indispensability of humility

A noted AI researcher and educator who was drawn to the field by its escalating penetration of “the mysteries of perception and cognition” has found a sort of missing link in its evolution. 

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New AI tool analyzes MRI information to generate precision prostate cancer treatment

Case Western Reserve University researchers teamed up with a number of institutions, including the Cleveland Clinic and Mount Sinai Hospital, among others, to develop RadClip.

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RadNet touts AI offshoot’s early success, pinpointing cancer a year earlier than current practice

DeepHealth, a subsidiary of the Los Angeles-based imaging giant, said its novel algorithm demonstrated higher performance than a group of trained breast radiologists. 

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Nanox moves to further disrupt radiology with new AI second opinion platform

A number of other leading organizations are involved in the project, including Zebra Medical, Aidoc and Qure.ai, along with the Israeli firm's collaborative partner USARAD.