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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AI reads mammograms to better predict breast cancer risk

The deep learning-based model yielded a lower false-negative rate for more aggressive cancers compared to traditional approaches.

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Machine learning’s success may depend on addressing 'gray areas' of cancer diagnosis

AI holds tremendous promise for making radiologists more efficient, but when it comes to cancer care, a few experts believe the coming tech revolution may encounter a few problems.

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AI, brain MRI combine to improve detection of ADHD

More than 6.1 million children were diagnosed with ADHD in 2016. Despite these numbers, there is no single test or imaging exam that can confidently diagnose a patient.

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AI reads digital pathology slides to help improve cancer outcomes

The tool, detailed in an EBioMedicine study published last month, can sift through the multitudes of cells in a tissue sample and identify tumors’ growth patterns, along with other highly useful information for predicting health outcomes.

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FDA announces public workshop on AI in radiology

The public workshop will take place this upcoming February and will discuss computer-aided detection and diagnosis software, computer-aided triage systems and image quality enhancement algorithms, among other topics.

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AI predicts patients' future healthcare costs from chest x-rays

The technique combines AI with patient-specific health and cost information for a rough estimate on an individual's five-year healthcare expenditures.

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RSNA names winners of intracranial hemorrhage AI challenge

The challenge tasked teams with developing an algorithm capable of identifying and classifying subtypes of hemorrhages on head CT scans.

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Machine learning creates image ‘atlas' to improve disease diagnoses

Massachusetts Institute of Technology researchers harnessed machine learning to create conditional atlases that can help clinicians diagnose a wider subset of patients. 

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Positron partners with Upbeat Cardiology Solutions to improve cardiac PET/CT access

Positron, a New York-based nuclear imaging company, will now provide Upbeat Cardiology Solutions with advanced PET/CT systems and services. 

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‘A huge win’: CMS significantly increases Medicare payments for cardiac CT

CMS has more than doubled the CCTA payment rate from $175 to $357.13. The move, expected to have a significant impact on the utilization of cardiac CT, received immediate praise from imaging specialists.