AI in Cardiology II
Researchers from Mayo Clinic and AliveCor Inc. have been using artificial intelligence (AI) to develop a mobile device that can identify certain patients at risk of sudden cardiac death. This research has yielded a breakthrough in determining the health of the electrical recharging system in a patient’s heart. The researchers determined that a smartphone-enabled mobile […]
AI in Cardiology I
As a Cardiologist with expertise in AI, I definitely see a whole lot of areas where AI can improve the practice of cardiology. But my excitement is less about AI adding more accuracy to the reading of the variety of the imaging studies performed in the assessment of the cardiac patients, and more about adding […]
AI in Ophthalmology II
Moore’s Field Eye Hospital partnered with Google’s DeepMind to develop OCT algorithms for the eye. They can diagnose most retinal disease: diabetic retinopathy, AMD, glaucoma, and fifty more with a combination of high-quality photos of the eye and deep learning algorithm. Smart phone attachments can enable remote OCT or fundoscopic photo, coupled with an algorithm […]
AI in Ophthalmology I
As with dermatology, ophthalmology is another specialty where the examination of the eye, including the fundus is a huge part of the screening and diagnosis for a variety of eye conditions. As such, if there is a way to create high-quality digital pictures of the fundus (which there is!) then AI algorithms can be used […]
AI in Dermatology
Consistent with radiology and pathology, dermatology is another specialty where a lot of the diagnosis comes down to a visual inspection of the skin and doing pattern recognition. This is good fit for AI to assist. Assist is the right term since the diagnosis will need to take other factors into consideration such as patient […]
AI Shows Improved Accuracy In Diagnosis in Pathology
In 2021, the FDA granted its first clearance for a cancer diagnosis AI program to Paige, a New York-based company launched in 2018 with data and digital pathology tech from Memorial Sloan Kettering Cancer Center. The product, Paige Prostate, analyzes slides of biopsied prostate tissue to spot the hallmarks of malignant cells. The software highlights […]
AI in Pathology II
Four factors came together to make digital pathology a must-have instead of a nice-to-have. First, COVID-19 sent pathologists home and challenged them to figure out new remote workflows. Second, cloud storage got cheaper and more robust, allowing for the sharing of massive images. Third, the development of advanced artificial intelligence has enabled pathologists to gain […]
AI in Pathology I
If a radiology scan suggests a mass that can be concerning for something serious (of even if not,) what comes next is taking tissue from that mass and examining it. When a cancer is suspected by a radiologist, a biopsy is taken, and that lump of tissue is sent to a pathology lab. There, a […]
AI in Radiology Imaging Acquisition
Whilst X-rays accounted for most of the scans performed, it is estimated that they accounted for less than 20% of total radiologist reading time, due to faster reading times per scan. The net effect of the changing complexion of scan types forecast over the next five years is, not only are diagnostic procedures increasing, but […]
AI in Radiology IV
A series of studies have described the use of deep learning algorithms to detect abnormalities in radiology, yielding promising results. ‘qXR’, Qure.ai’s chest X-ray interpretation tool, is able to automatically detect and localize up to 29 abnormalities, including those indicative of possible lung cancer. There are several features of chest radiographs (such as sharply circumscribed […]