Bingtian Dong, Hua Zhang, Yayang Duan, Senbang Yao, Yongjian Chen, Chaoxue Zhang
Development of a machine learning-based model to predict prognosis of alpha-fetoprotein-positive hepatocellular carcinoma
Journal of translational medicine
preliminary study aimed clinically assess precision novel optical jaw tracking system jts registering mandibular movements mms protrusion mediotrusion twenty healthy participants underwent recordings using cyclops jts itaka way med functional mms protrusion laterotrusion two trained clinicians subject performed five registrations different times according standardized pattern within onemonth period angulations protrusive mediotrusive functional paths within first 2 mm maximal intercuspal position mip calculated trace using data software angle measurements descriptive statistics used assess repeatability recordings participant mm additionally inferential statistics carried standard deviation values obtained 005 overall precision patients 707337 protrusion angle 524224 right laterotrusion 514306 left laterotrusion angles protrusion angle ranged 308 1357 right left laterotrusion ranged 182 942 158 1059 respectively statistically significant differences observed different functional mm types gender p 005 recordings functional mms mediotrusion protrusion using cyclops jts showed consistent repeatability regardless gender functional mm type results revealed nonnegligible variations may due patients abilities precisely reproduce jaw movements operators ability consistently connect kinesiograph capturing functional mms digitally importing data dental cad software essential virtual waxing prosthetic rehabilitations design functionalized adapted occlusion establishing repeatability mm recordings jts crucial step better understanding novel jts market process could facilitate interpretation cusp angles aid cad dynamic technical modeling enhance clinical data communication clinicians technicians modern workflow