Artificial intelligence (AI) has established itself as a disruptive force in the healthcare industry. In this article, DocWire News has compiled the most recent breakthroughs and headlines regarding how AI is impacting the future of healthcare.
Google Creates AI that Detects Lung Cancer Better than Doctors
Google researchers have recently worked with Northwestern Medicine to create an AI system that detects lung cancer more accurately than human radiologists. A deep-learning algorithm was used to train this system, which interprets computed tomography (CT) scans to predict one’s likelihood of having the disease. Daniel Tse, product manager at Google Brain, is the corresponding author of the study, which appeared on May 20 in the journal Nature Medicine.
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Discovering Causes of Autism in Uncharted DNA
Using AI, a research team has recently uncovered novel genetic mutations associated with autism in noncoding regions of DNA. The scientists leveraged deep learning to analyze these ‘junk’ regions of the genome that may not affect what certain genes produce, but rather how much of it they make. The work was published on May 27 in Nature Genetics.
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How do Doctors Feel About AI Taking Their Jobs?
With artificial intelligence-based systems proving their worth in various research trials, their potential impact in healthcare is profound particularly in areas such as pathology and radiology. Less than two weeks ago, news broke of Google’s AI system that detected lung cancers with higher accuracy than human doctors. The FDA has already approved IDx-DR, an AI-tool that analyzes images of the eye to diagnose disease and University of Michigan researchers have recently created a similar AI-software for smartphones.
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Researchers Use Machine Learning and Wearable Sensor to Detect Heart Disease
Researchers have recently developed an artificial intelligence classifier that can detect a specific cardiovascular disease using a wearable wrist biosensor. The condition, hypertrophic cardiomyopathy, can cause serious complications and is commonly unrecognized in the clinical setting. By proposing a diagnostic approach using a machine learning and a wearable sensor, these researchers have potentially developed a noninvasive and widely available tool to identify the disease. Their work was published in npj Digital Medicine on June 24.
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Medical Industry Takes an Important Step Towards Embracing AI
IDx, a privately held AI diagnostics company, announced yesterday that the American Medical Association’s (AMA) Current Procedural Terminology (CPT) Editorial Panel has accepted a new category 1 CPT® code for automated point-of-care retinal imaging. This new code, submitted by the American Academy of Ophthalmology (AAO) with the support of IDx, facilitates correct billing of IDx-DR, an FDA-cleared autonomous AI system that detects diabetic retinopathy, a leading cause of blindness.
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Using Machine Learning AI to Detect Schizophrenia
Recent innovations in artificial intelligence technology have allowed researchers to better detect psychosis in patients. In this article, we discuss two machine learning systems that use speech recognition and functional magnetic resonance imaging (fMRI) to detect the condition.
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