Radiology

27 Posts

Rigorous Trial: AI matches humans in breast cancer diagnosis.
Radiology

Rigorous Trial: AI matches humans in breast cancer diagnosis.

A deep learning system detected breast cancer in mammograms as well as experienced radiologists, according to a landmark study.
AI system recognizes normal chest x-rays
Radiology

AI Enters the Radiology Department: ChestLink, an AI X-Ray Tool Approved by European Officials

The European Union approved for clinical use an AI system that recognizes normal chest X-rays. ChestLink is the first autonomous computer vision system to earn the European Economic Area’s CE mark for medical devices...
Doctors using AI-related tools on different devices
Radiology

Insurance Coverage for AI: Medicare covers AI stroke detection.

The U.S. government’s largest national health insurance plan will pay for hospital use of a deep learning model, building momentum for AI to become an integral part of the doctor’s toolkit.
X-rays and charts about AI use in radiology
Radiology

Radiologists Eye AI: Radiologists increasingly rely upon computer vision.

AI lately has achieved dazzling success interpreting X-rays and other medical imagery in the lab. Now it’s catching on in the clinic. Roughly one-third of U.S. radiologists use AI in some form in their work.
Data related to a diagnostic advice received from a machine learning model vs a human expert
Radiology

Would Your Doctor Take AI’s Advice?: Some doctors are skeptical of AI diagnoses.

Some doctors don’t trust a second opinion when it comes from an AI system. A team at MIT and Regensburg University investigated how physicians responded to diagnostic advice they received from a machine learning model versus a human expert.
Sequence showing a training step that uses different perspectives of the same patient to enhance unsupervised pretraining
Radiology

Same Patient, Different Views: Contrastive pretraining improves medical imaging AI.

When you lack labeled training data, pretraining a model on unlabeled data can compensate. New research pretrained a model three times to boost performance on a medical imaging task.
Graph showing system that examines X-ray images to predict which Covid-19 patients are at greatest risk of decline
Radiology

Covid-19 Triage: Computer vision for x-rays helps triage Covid-19 patients.

The pandemic has pushed hospitals to their limits. A new machine learning system could help doctors make sure the most severe cases get timely, appropriate care.
Series of images showing a variety of medical AI products
Radiology

Medical AI’s Hidden Data: Why many medical AI devices are black boxes.

U.S. government approval of medical AI products is on the upswing — but information about how such systems were built is largely unavailable. The U.S. Food and Drug Administration (FDA) has approved a a plethora of AI-driven medical systems.
Radiology

Pain Points in Black and White: Medical AI system predicts knee pain from Black patients.

A model designed to assess medical patients’ pain levels matched the patients’ own reports better than doctors’ estimates did — when the patients were Black.
Two reindeers with masks on a snowy night
Radiology

Coping With Covid: How AI helped fight Covid-19.

AI accelerated the search for a coronavirus vaccine, detected Covid-19 cases, and otherwise softened the pandemic’s blow. Machine learning researchers worldwide scrambled to harness the technology against the coronavirus.
Examples of contrastive learning
Radiology

Learning From Words and Pictures: A deep learning method for medical x-rays with text

It’s expensive to pay doctors to label medical images, and the relative scarcity of high-quality training examples can make it hard for neural networks to learn features that make for accurate diagnoses.
Doctor holding candy and kid dressed as a ghost on a wheighing scale
Radiology

Unfair Outcomes Destroy Trust: What could cause widespread backlash against AI?

Will AI that discriminates based on race, gender, or economic status undermine the public’s confidence in the technology? Seduced by the promise of cost savings and data-driven decision making, organizations will deploy biased systems that end up doing real-world damage.
Data related to a system that purportedly identified breast cancer
Radiology

Pushing for Reproducible Research: Experts criticize Google Health over AI transparency.

Controversy erupted over the need for transparency in research into AI for medicine. Google Health introduced a system that purportedly identified breast cancer more accurately than human radiologists.
Examples of CT scans with different contrasts
Radiology

More Data for Medical AI: AI recognizes medical scans without iodine dye.

Convolutional neural networks are good at recognizing disease symptoms in medical scans of patients who were injected with iodine-based dye, that makes their organs more visible. But some patients can’t take the dye. Now synthetic scans from a GAN are helping CNNs learn to analyze undyed images.
Data related to Covid-19 symptoms prediction
Radiology

Cats Cured of Covid: Why some deep learning models thought cats had Covid

Neural networks are famously bad at interpreting input that falls outside the training set’s distribution, so it’s not surprising that some models are certain that cat pictures show symptoms of Covid-19. A new approach won’t mistakenly condemn your feline to a quarantine.
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