Expression of anti - Apoptotic survivin in odontogenic keratocyst, adenomatoid odontogenic tumor and ameloblastoma. [PDF]
Latha HA+5 more
europepmc +1 more source
Calcifying odontogenic cyst coexists with adenomatoid odontogenic tumor and peripheral cemento-osseous reactive proliferation. [PDF]
Tseng CH, Wang WC, Chen YF, Chen YK.
europepmc +1 more source
Adenomatoid Odontogenic Tumor Mimicking a Dentigerous Cyst in Maxilla. [PDF]
Pawar SR+3 more
europepmc +1 more source
Syndromic multiple adenomatoid odontogenic tumors [PDF]
Kentaro Kikuchi+3 more
openaire +2 more sources
Adenomatoid odontogenic tumor with clear cell changes
Adenomatoid odontogenic tumor (AOT) has a limited biological profile and been an attention-grabbing tumor for a century for its origin. Though described earlier, it was widely accepted after Harbitz from Norway reported about this uncommon benign tumor in 1915. There has been a long debate as whether this tumor is a hamartoma or a neoplasm.
Yashwant Ingale+3 more
openaire +4 more sources
Management of Adenomatoid Odontogenic Tumor in a Pediatric Patient with Preservation of an Associated Impacted Tooth: A Combined Surgical and Orthodontic Approach. [PDF]
Taneja S, Jain A.
europepmc +1 more source
Confidence intervals for tree-structured varying coefficients [PDF]
The tree-structured varying coefficient model (TSVC) is a flexible regression approach that allows the effects of covariates to vary with the values of the effect modifiers. Relevant effect modifiers are identified inherently using recursive partitioning techniques.
arxiv
A Large Follicular Adenomatoid Odontogenic Tumor Occupying the Maxillary Sinus: A Case Report. [PDF]
Maharjan L, Gurung U, Pradhan B.
europepmc +1 more source
Deep Learning in Medical Image Classification from MRI-based Brain Tumor Images [PDF]
Brain tumors are among the deadliest diseases in the world. Magnetic Resonance Imaging (MRI) is one of the most effective ways to detect brain tumors. Accurate detection of brain tumors based on MRI scans is critical, as it can potentially save many lives and facilitate better decision-making at the early stages of the disease.
arxiv
Estimating the age of renal tumors [PDF]
We present a Bayesian method for estimating the age of a renal tumor given its size. We use a model of tumor growth based on published data from observations of untreated tumors. We find, for example, that the median age of a 5 cm tumor is 20 years, with interquartile range 16-23 and 90% confidence interval 11-30 years.
arxiv