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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10 questions clinicians—and patients—ought to ask about every AI they encounter

Technology educators, tech-policy wonks and hospital clinical leaders from three countries have collaborated to produce a helpful guide for end-users of healthcare-specific AI tools—and the patients they serve.

3 noteworthy developments in emerging medical technologies

While big breakthroughs in healthcare AI seem to have slowed in recent weeks, those involving other hot technologies have kept the content coming for publishers of peer-reviewed medical journals.

HIMSS speakers see standards, possibly ‘nutrition labels’ in healthcare AI’s future

Freely hope for the best, but diligently prepare for the worst. Applied to end users of healthcare AI, that adage could have been a key takeaway at last week’s annual meeting of HIMSS in Las Vegas.

Explainable AI’s pros ‘not what they appear’ while its cons are ‘worth highlighting’

Not so fast with explainable AI in healthcare, warns an international and multidisciplinary team of academics.

AI experts to med students: Don’t compete with the machine. Collaborate with it

As machine learning progresses from research settings to clinical practice, how are clinicians to know they can trust the machine’s conclusions to guide care for actual patients?

Virtually trained NICU nurses sensitively respond to babies’ pain

Infants in pain can’t describe the severity of their discomfort, but NICU nurses can e-learn how to gauge pain degrees according to standardized scales, allowing for prompt and appropriate pain-relief interventions.

Retinopathy screening a canary in the coal mine of AI-enabled nonspecialist care

Many cases will be handled by primary-care providers, eye technicians and even patients themselves connected by telehealth and armed with commercial test kits and AI.

10 robots for cranial neurosurgery on the market or in the works

The authors concentrate on robotic technologies that either augment a surgeon’s movements or simplify a multistep process.

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