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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Why AI will change medical imaging—and won't replace human professionals

As deep learning in medical imaging continues to advance, two leading experts argue in an editorial in the Harvard Business Review that it will only result in positive impacts on the field—rather than replace imaging professionals with computers.

21% of healthcare employees worry about job security due to AI

In healthcare, 21 percent of employees are concerned about their job security due to the adoption of robotics and artificial intelligence (AI), according to a survey conducted by MindEdge.

NTT DATA expands advanced AI capabilities for healthcare with distribution partnership for imaging insights service

Plano, Texas – March 26, 2018 – NTT DATA Services, a recognized leader in global technology services, today announced a partnership with DataFirst, Inc. to deliver clinical artificial intelligence (AI) that will help healthcare organizations improve quality and decrease the cost of patient care.

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Could AI algorithms result in racial bias?

Artificial intelligence might be a hot tech topic, but it could also pose ethical risks—namely racial ones—to healthcare, Clinical Innovation + Technology reported this month.

98% of healthcare executives believe automated healthcare will improve gaps in care

In a report released by World Business Research (WBR) and Conversa Health, 98 percent of healthcare executives believed automated healthcare will be important to closing gaps in transactional care, continuous and collaborative care experiences.

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Machine learning model accurately predicts who would benefit most from mpMRIs

A novel machine learning model could accurately predict which men might benefit most from additional imaging before a prostate biopsy, saving patients both money and discomfort, a new study states.

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Deep learning model as accurate as radiologists determining age of child bones

A recent study published in Radiology has demonstrated that deep-learning bone age assessment models analyzing hand radiographs produced results as accurate as a radiologist.

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Q&A: Keith Dreyer on radiology’s evolving relationship with AI

Few radiologists understand the relationship between radiology and artificial intelligence (AI) quite like Keith Dreyer, DO, PhD, vice chairman and associate professor of radiology at Massachusetts General Hospital in Boston.