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2.
Public Health ; 164: 1-6, 2018 Nov.
Article in English | MEDLINE | ID: mdl-30149185

ABSTRACT

OBJECTIVE: Artificial neural networks (ANNs) and classification and regression trees (CARTs) have been previously used for the prediction of cancer in several fields. In our study, we aim to investigate the diagnostic accuracy of three different methodologies (i.e. logistic regression, ANNs and CARTs) for the prediction of endometrial cancer in postmenopausal women with vaginal bleeding or endometrial thickness ≥5 mm, as determined by ultrasound examination. STUDY DESIGN: We conducted a retrospective case-control study based on data from analysis of pathology reports of curettage specimens in postmenopausal women. METHODS: Classical regression analysis was performed in addition to ANN and CART analysis using the IBM SPSS and Matlab statistical packages. RESULTS: Overall, 178 women were enrolled. Among them, 106 women were diagnosed with carcinoma, whereas the remaining 72 women had normal histology in the final specimen. ANN analysis seems to perform better with a sensitivity of 86.8%, specificity of 83.3%, and overall accuracy (OA) of 85.4%. CART analysis did not perform well with a sensitivity of 78.3%, specificity of 76.4%, and OA of 77.5%. Regression analysis had a poorer predictive accuracy with a sensitivity of 76.4%, a specificity of 66.7%, and an OA of 72.5%. CONCLUSION: Artificial intelligence is a powerful mathematical tool that may significantly promote public health. It may be used as a non-invasive screening tool to guide clinicians involved in primary care decision making when endometrial pathology is suspected.


Subject(s)
Decision Trees , Endometrial Neoplasms/diagnosis , Neural Networks, Computer , Postmenopause , Regression Analysis , Aged , Case-Control Studies , Female , Humans , Middle Aged , Predictive Value of Tests , Reproducibility of Results , Retrospective Studies
3.
J BUON ; 17(4): 684-90, 2012.
Article in English | MEDLINE | ID: mdl-23335525

ABSTRACT

PURPOSE: The transforming growth factor bgr; (TGF-ß)/ Smad pathway is implicated in the development of interstitial cells of Cajal. The aim of this study was to examine the role of this pathway in human gastrointestinal stromal tumors (GISTs). METHODS: The expression of TGF-ß receptor II (TßRII), phosphorylated Smad2 (p-Smad2), SnoN, p21(WAF17sol;CIP1) and p27(KIP1) was examined by immunohistochemistry in 30 hu-man GISTs in relation to prognostic factors. RESULTS: TßRII was expressed in 76.9% of the cases. All cases were positive for p-Smad2 and SnoN, with significantly higher expression levels in small intestinal compared to gastric GISTs. Downregulation of p21(WAF1/CIP1) and p27(KIP1) was found in 78.6% and 46.4% of the cases respectively, while cytoplasmic expression of p27(KIP1) was also noted in 50% of GISTs. CONCLUSIONS: TGF-ß/Smad pathway may contribute to GIST pathogenesis. SnoN overexpression and low levels of p21(WAF1)/CIP1 and p27(KIP1) may be of importance in GISTs.


Subject(s)
Gastrointestinal Neoplasms/chemistry , Gastrointestinal Stromal Tumors/chemistry , Intracellular Signaling Peptides and Proteins/analysis , Proto-Oncogene Proteins/analysis , Adult , Aged , Aged, 80 and over , Carcinoembryonic Antigen/blood , Cyclin-Dependent Kinase Inhibitor p21/analysis , Cyclin-Dependent Kinase Inhibitor p27/analysis , Female , Gastrointestinal Neoplasms/etiology , Gastrointestinal Stromal Tumors/etiology , Humans , Immunohistochemistry , Intracellular Signaling Peptides and Proteins/physiology , Male , Middle Aged , Protein Serine-Threonine Kinases/analysis , Proto-Oncogene Proteins/physiology , Receptor, Transforming Growth Factor-beta Type II , Receptors, Transforming Growth Factor beta/analysis , Smad2 Protein/analysis
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