Tag Archives: Machine learning

November 2023—It was a mystery, wrapped less in an enigma than a few layers of bafflement, surprise, and mild irritation. Call it the Case of the Split Lung Specimens. The first hint something was amiss came when Alain Borczuk, MD, vice chair of anatomic pathology and co-director of thoracic pathology, Northwell Health, noticed that he and his colleagues were receiving more insufficient bronchoscopy specimens than usual. “When I say ‘increasing’—we don’t get that many bronchoscopies. It’s not like colon polyps,” says Dr. Borczuk, who is also director of oncologic pathology, Northwell Health Cancer Institute. Normally they would get a handful a week, some of them straightforward cancer cases, although these additional cases were tied to noncancerous conditions. And then the plot thickened even further, with missing pieces—literally. Though no guideline clearly states what constitutes an adequate specimen, Dr. Borczuk says, the samples he and his colleagues were seeing fell markedly short.

February 2023—As this year’s guide to anatomic pathology computer systems was taking shape, CAP TODAY publisher Bob McGonnagle met online with representatives of five companies and with John Sinard, MD, PhD, of Yale University School of Medicine. They talked about the cloud, CPT codes, training of pathology informaticians, and artificial intelligence, for which the time frame in pathology is far longer than it’s been portrayed, in Dr. Sinard’s view. “It will start to impact the careers of some of our trainees, but it’s probably a 10- to 20-year time frame before it plays a major role,” he said. The view of Joe Nollar of Xifin: “Speculation that AI will someday replace pathologists is completely overblown,” though it will help to triage cases and mitigate risk. Their full conversation, which took place Dec. 20, 2022, follows.  

December 2022—In September, when CAP TODAY publisher Bob McGonnagle met with pathologists and representatives of companies to talk about laboratory information systems (“Lab information systems—where the needs are greatest,” https://bit.ly/LIS_112022), they talked also about artificial intelligence—innovations, clinical impact, how much interest there is. That part of their conversation follows.

September 2022—Do you want to play a role in solving a problem or improving a process in your laboratory via machine learning or artificial intelligence but don’t know where to begin? If so, take some time to learn, listen, share, and, perhaps, have a cup of coffee, says Scott Doyle, PhD, biomedical engineer at the State University of New York at Buffalo.

February 2022—In a survey of the international pathology community on the integration of artificial intelligence into diagnostic pathology practice, 80 percent of the 487 respondents predicted integration within the next five or 10 years.

December 2021—A cost-effective liquid biopsy focused on analyzing genomewide fragmentation profiles in cell-free DNA has been shown in proof-of-concept studies to detect early-stage lung and other cancers.

February 2020—At Massachusetts General Hospital, machine learning is being used in the laboratories to build next-level clinical decision support, and in the latest phase, it’s undergoing trial for use in predicting laboratory results. “I think this is the new paradigm for cost-effective laboratory medicine. This is an important way we’re going to change how we do business,” says Anand Dighe, MD, PhD, who spoke about machine learning techniques for labs during a CAP19 presentation last fall and in a recent interview with CAP TODAY.