{"id":196335,"date":"2023-03-22T07:16:06","date_gmt":"2023-03-22T11:16:06","guid":{"rendered":"https:\/\/today.uconn.edu\/?p=196335"},"modified":"2023-03-16T10:58:05","modified_gmt":"2023-03-16T14:58:05","slug":"using-ai-algorithms-to-streamline-orthodontic-care","status":"publish","type":"post","link":"https:\/\/today.uconn.edu\/2023\/03\/using-ai-algorithms-to-streamline-orthodontic-care\/","title":{"rendered":"Using AI Algorithms to Streamline Orthodontic Care"},"content":{"rendered":"

Dr. Madhur Upadhyay and his collaborators have invented an artificial intelligence <\/span>tool<\/span><\/a> to assist clinicians in determining next steps for patients\u2019 orthodontic care.\u00a0<\/span>\u00a0<\/span><\/p>\n

\u201cIf you get two orthodontists in a room, they will disagree on 50% of the patients they are diagnosing, to varying degrees,\u201d says Upadhyay, an associate professor of orthodontics at UConn\u2019s School of Dental Medicine. \u201cEverybody\u2019s reading the same literature, but they are perhaps interpreting it in different ways. Artificial intelligence can do this job very nicely \u2013 assimilating the literature and then interpreting it in ways that are perhaps more accurate than how most of us will interpret it.\u201d<\/span>\u00a0<\/span><\/p>\n

The algorithm<\/a>, further optimized by assistant professor at Marquette University School of Dental Medicine Dr. Shivam Mehta and data scientist and AI developer Gaurav Sinha, draws on a deep network of medical literature and expert decisions to indicate whether it agrees or disagrees with an orthodontist\u2019s analysis. Positive results, where the algorithm is in agreement with the doctor\u2019s diagnosis, provide more peace of mind to clinicians and patients. Negative results prompt the clinicians to take another look and determine the source of the discrepancy between the algorithm\u2019s projected diagnosis and their own.<\/span>\u00a0<\/span><\/p>\n

While any former braces-wearer can attest that the process of shifting teeth can be unpleasant, the diagnostic acumen required from orthodontists may be less obvious from the patient\u2019s chair. But determining the best placement for a patient\u2019s teeth — and the best course of action to guide them there — is a precise science, one that Upadhyay is excited to augment with the capabilities of AI.\u00a0<\/span>\u00a0<\/span><\/p>\n

Inaccurate diagnoses can result in jaw pain, bone loss, gum recession, and other dental issues that are difficult to correlate with past orthodontia when they develop years down the line. Including the \u201csecond voice\u201d of AI, he says, will ensure better patient outcomes in the long term.<\/span>\u00a0<\/span><\/p>\n

A successful orthodontic diagnosis considers \u201caesthetics, function, and structure,\u201d says Upadhyay, who is a practicing clinician in addition to teaching at UConn. All these domains are interconnected, he notes, so an inaccurate diagnosis can be catastrophic: \u201cSuppose you took teeth out in a patient that did not need teeth to be taken out. Or suppose a patient required taking teeth out but you did not take teeth out. That can compromise the structural integrity of the teeth, the bone, and the surrounding structures.\u201d<\/span>\u00a0<\/span><\/p>\n

In addition to improving patient outcomes, Upadhyay\u2019s algorithm will free up valuable time for providers, allowing them to diagnose more patients without compromising accuracy. \u201cWe understood that time is the key if you want to make it into a business model,\u201d Upadhyay says about the commercialization process.\u00a0<\/span>\u00a0<\/span><\/p>\n

As the idea for the algorithm was being developed<\/span>,<\/span> Upadhyay reached out to UConn\u2019s Technology Commercialization Services (<\/span>TCS<\/span><\/a>) for patentability and commercialization. TCS worked with Upadhyay to protect the intellectual property associated with the technology and introduced him to various entrepreneurship support services, like Accelerate UConn. The technology maturation was further supported by UConn\u2019s TCS through a Proof-of-Concept START grant.<\/span>\u00a0<\/span><\/p>\n

Eventually, he says, his team has an eye toward developing AI algorithms to assist with all steps of the diagnosis process, from taking measurements to interpreting data.<\/span>\u00a0<\/span><\/p>\n

\u201cA significant amount of human power is wasted in doing mundane jobs like cropping figures, resizing figures, drawing some lines on them to interpret them — which are pretty basic things,\u201d he says. \u201cA system should be automatically able to do it.\u201d\u00a0<\/span>\u00a0<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

Brace yourself for the future of AI-assisted diagnosis<\/p>\n","protected":false},"author":175,"featured_media":196351,"comment_status":"closed","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_crdt_document":"","wds_primary_category":0,"wds_primary_series":0,"wds_primary_attribution":0,"footnotes":""},"categories":[2076,2166,2364,2235],"tags":[],"magazine-issues":[],"coauthors":[2413],"class_list":["post-196335","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-research","category-sdm","category-technology-commercialization","category-today-homepage"],"pp_statuses_selecting_workflow":false,"pp_workflow_action":"current","pp_status_selection":"publish","acf":[],"publishpress_future_action":{"enabled":false,"date":"2026-05-22 16:14:02","action":"change-status","newStatus":"draft","terms":[],"taxonomy":"category","extraData":[]},"publishpress_future_workflow_manual_trigger":{"enabledWorkflows":[]},"_links":{"self":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/196335","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/users\/175"}],"replies":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/comments?post=196335"}],"version-history":[{"count":1,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/196335\/revisions"}],"predecessor-version":[{"id":196336,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/posts\/196335\/revisions\/196336"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media\/196351"}],"wp:attachment":[{"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/media?parent=196335"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/categories?post=196335"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/tags?post=196335"},{"taxonomy":"magazine-issue","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/magazine-issues?post=196335"},{"taxonomy":"author","embeddable":true,"href":"https:\/\/today.uconn.edu\/wp-rest\/wp\/v2\/coauthors?post=196335"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}