In light of a pending national standard requiring breast density notification in mammography reports, an emerging artificial intelligence (AI) tool may help reduce subjectivity and variability in breast density assessments. The Food and Drug Administration (FDA) has granted 510(k) clearance for Saige-Density (DeepHealth/RadNet), an adjunctive AI software that provides automated categorization of breast density based on the American College of Radiology's Breast Imaging Reporting and Data System (BI-RADS) classification. DeepHealth said a retrospective, multicenter study showed a 91.5 percent alignment between Saige-Density assessment and consensus assessment of breast density by five specialists in breast imaging. The Saige-Density AI algorithm was trained on a racially diverse database of over 166,000 images from 30,000 mammography exams across the United States, according to DeepHealth. "Achieving FDA clearance for another important tool in the breast cancer screening process in such a short time frame highlights our aggressive commitment to bringing state-of-the art AI innovation to the breast screening mammography market," noted Gregory Sorenson, M.D., the CEO and co-founder of DeepHealth.

Is there enough scrutiny of artificial intelligence (AI) software prior to clearance by the Food and Drug Administration (FDA) for adjunctive use in breast cancer screening? Despite the FDA clearance in recent years of several AI products to help identify suspicious breast lesions and facilitate mammography triage, researchers suggested in a recent review, published in JAMA Internal Medicine, that questions remain about data sources, clinical outcome measures and external validation. Here are a few takeaways from their review of the research leading to FDA clearance for nine AI-related products for breast cancer screening between January 1, 2017 and December 31, 2021. All of the clearances for the AI products were based on retrospective analysis of previously existing databases. Only six of the nine products had multicenter studies to support their use and research for four of the AI products lacked information about external validation, according to the review.

Since 1995, the FDA has authorized more than 500 AI/ML-enabled medical devices via 510(k) clearance, granted De Novo request, or approved PMA. This week the FDA published an updated list with 178 new devices that were authorized through July 2022. According to the FDA, their list is based on publicly available information and is not a comprehensive resource of FDA approved AI/ML-enabled medical devices. In today's DeepTech newsletter I'm sharing a high level analysis of the 521 devices on the list, charts to visualize the data, and a summary of milestones. Note: According to the FDA their list is based on publicly available information and is not a comprehensive resource of approved AI/ML-enabled medical devices.

Dr. Ronny Shalev is CEO and founder of Dyad Medical Inc. a company that develops FDA-cleared software which automatically analyzes the content of cardiac and cardiovascular images using artificial intelligence. He has spent much of the past 25 years in executive positions, including VP of Sales and Marketing at Orbotech (NASDAQ: ORBK), where he managed teams of more than 100 people worldwide and Director of the World-wide Program Management at Marvell Semiconductor (NASDAQ: MRVL). He has a significant amount of experience as an entrepreneur and is dedicated to using his skills to help physicians make accurate decisions to improve patient outcomes. He holds a Ph.D. in electrical engineering and computer science from Case Western Reserve University. What initially attracted you to computer science and machine learning?

Offering the potential of enhanced resolution with accelerated scan times for magnetic resonance imaging (MRI), SmartSpeed (Philips), an emerging artificial intelligence (AI)-enabled software, has garnered FDA 510(k) clearance. In comparison to other MRI modalities, Philips said the addition of SmartSpeed to the company's Compressed SENSE MR acceleration engine offers a threefold reduction in MRI scanning time and increases image resolution up to 65 percent. "Philips' AI-based SmartSpeed reconstruction is the new benchmark among acceleration techniques for us. It improves on the company's existing Compressed SENSE (MR acceleration engine) in all aspects and allows a reduction in scan times with excellent image quality and diagnostic confidence," noted Grischa Bratke, MD, who is affiliated with the Department of Radiology at the University Hospital of Cologne in Germany. Philips noted that application of the AI reconstruction algorithm with SmartSpeed at the front end of the MR signal facilitates a high signal-to-noise ratio that enhances image quality and enables small lesion detection.

This week Aidoc announced that they have raised $110 million in their Series D expansion round. This round of funding was co-led by TCV and Alpha Intelligence Capital with participation from CDIB Capital. Funding raised in this round will go toward expansion of Aidoc's first of its kind AI Care Platform. The platform offers health systems a singular platform solution designed to help doctors manage the entire patient lifecycle--from diagnostic aid, to consultation, to suggested treatment paths, to patient follow-up tools. In clinical studies, this platform has proven to reduce turnaround time, shorten patient length of stay and improve patient outcomes.

This partnership will help health systems address the increasing volume of medical images and the worldwide radiologist labor shortage. Integration of Boneview into Aidoc's AI platform will give many more clinicians access to a tool to help them identify fractures in limbs, pelvis, thoracic and lumbar spine, and rib cage. Aidoc's end-to-end AI platform already includes numerous third-party AI vendors including Imbio, Riverain, Subtle, Icometrix and ScreenPoint. Over 152 million X-rays are performed every year in the US. Although there are about 37,000 radiologists in the US, they are not evenly distributed.

RapidAI's newly cleared artificial intelligence tool automatically analyzes CT pulmonary angiograms to detect signs of pulmonary embolism, …

An emerging artificial intelligence (AI) software that reportedly reduces false negative rates for fractures by 29 percent has received FDA clearance. BoneView AI (Gleamer) detects fractures on X-rays, highlights regions of interest and submits them to radiologists for confirmation, according to the French company Gleamer. The company said the algorithm was designed to aid a variety of physicians who read X-rays in clinical practice. Noting that traumatic injuries account for one-third of visits to emergency rooms (ERs), Gleamer noted that errors with fracture interpretation, which are common during evening hours, can represent up to 24 percent of harmful diagnostic errors in the ER. The company said these errors may result from fatigue and non-expert reading of X-rays.

A check up by Khosla Ventures determined that Docbot Inc. was healthy enough for the prominent biotech investor to take the lead in a $4 million series A round. The new funds bring the artificial intelligence company to a total of $8.5 million in capital raised to date. Other participants included Bold Capital Partners, Collaborative Fund and Boutique Venture Partners. Docbot's platform, Ultivision AI, uses artificial intelligence to enhance detection of gastrointestinal (GI) disease. The Irvine, Calif.-based company is targeting identification and classification of polyps, Barrett's esophagus, and ulcerative colitis to start.