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-based mammo screening protocol reduces radiologist workload by 62%

Researchers reported that the artificial intelligence system was able to interpret more than 114,000 screening mammograms using a reading protocol with high sensitivity and specificity.

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Explainable AI model accurately auto-labels chest X-rays from open access datasets

A model that can achieve accuracy in line with that of radiologists when labeling open-access datasets could be a key factor to overcoming limitations of artificial intelligence implementation, researchers explained in Nature Communications.

Algorithm performs at expert level when distinguishing between benign and malignant ovarian tumors

Experts involved with the study suggested that these findings could be beneficial in the future of ovarian tumor assessment by providing clinical decision making support.

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Lack of diverse datasets in AI research puts patients at risk, experts suggest

Homogenous datasets can create unintended research bias that hinders the clinical efficacy of AI applications, experts recently explained in PLOS Digital Health.

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Australian tech company opens new US office, eyes FDA approval for AI CAD solution

The company's flagship offering uses AI to evaluate 3D images of a patient's heart for signs of atherosclerotic plaque.

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Artificial intelligence startup Viz.ai reaches unicorn status with $100M investment

Now valued at $1.2B, the San Francisco startup was co-founded by a neurosurgeon and offers a suite of solutions for diagnosing diseases from medical images. 

AI model able to ID early signs of type 2 diabetes on imaging results

The authors hope their findings could lead to earlier diagnoses and improvements in patient care. 

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AI predicts COVID prognosis at near-expert level using CT scoring system

A deep convolutional neural network was able to predict hospital stay, ICU admission and intubation when scoring chest CT images of hospitalized COVID patients.

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