An arrhythmia is a problem with the rate or rhythm of the heartbeat. During an arrhythmia, the heart can beat too fast, too slowly, or with an irregular rhythm. When a heart beats too fast, the condition is called tachycardia. When a heart beats too slowly, the condition is called bradycardia. The most common test used to diagnose an arrhythmia is an electrocardiogram (EKG or ECG). [Ref]

“Thanks to advances in wearable health technologies, it’s now possible for people to monitor their heart rhythms at home for days, weeks, or even months via wireless electrocardiogram (EKG) patches. In fact, my Apple Watch makes it possible to record a real-time EKG whenever I want.” says Dr Francis Collins, Director of NIH, USA.

A powerful computer “studied” more than 90,000 EKG recordings, from which it “learned” to recognize patterns, form rules, and apply them accurately to future EKG readings. The computer became so “smart” that it could classify 10 different types of irregular heart rhythms, including atrial fibrillation (AFib). In fact, after just seven months of training, the computer-devised algorithm was as good—and in some cases even better than—cardiology experts at making the correct diagnostic call [Ref].  The findings suggest that artificial intelligence can be used to improve the accuracy and efficiency of EKG readings. In fact, Hannun reports that iRhythm Technologies, maker of the Zio patch, has already incorporated the algorithm into the interpretation now being used to analyze data from real patients. [Ref]

Nearly all cervical cancers are caused by the human papillomavirus (HPV). Cervical cancer screening—first with Pap smears and now also using HPV testing—have greatly reduced deaths from cervical cancer. But this cancer still claims the lives of more than 4,000 U.S. women each year, with higher frequency among women who are black or older [Ref]. Around the world, more than a quarter-million women die of this preventable disease, mostly in poor and remote areas [Ref].

In work described in the Journal of the National Cancer Institute [Ref], researchers used a high-performance computer to analyze thousands of cervical photographs, obtained more than 20 years ago from volunteers in a cancer screening study. The computer learned to recognize specific patterns associated with pre-cancerous and cancerous changes of the cervix, and that information was used to develop an algorithm for reliably detecting such changes in the collection of images. How they exactly did this – First, the researchers got the computer to create a convolutional neural network. That’s a fancy way of saying that they trained it to read images, filter out the millions of non-essential bytes, and retain the few hundred bytes in the photo that make it uniquely identifiable. They fed 1.28 million color images covering hundreds of common objects into the computer to create layers of processing ability that, like the human visual system, can distinguish objects and their qualities. The AI-generated algorithm outperformed human expert reviewers and all standard screening tests in detecting pre-cancerous changes. [Ref]

In fact, the researchers are already field testing their AI-inspired approach on smartphones in the United States and abroad. If all goes well, this low-cost, mobile approach could provide a valuable new tool to help reduce the burden of cervical cancer among underserved populations. The day that cervical cancer no longer steals the lives of hundreds of thousands of women a year worldwide will be a joyful moment for cancer researchers, as well as a major victory for women’s health.

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