Sentence examples for classification aimed to from inspiring English sources

Future studies need to improve both diagnostic methods and tools and adequate classification aimed to determine a correct prognosis and an appropriate therapy for gingival overgrowth.

The final stage of development of the classification aimed to define a restricted set of 'surgical problems' by examining which problems had been referred to surgeons in the BEACH study.

The great heterogeneity of diagnostic data and results in our systematic review is due to the lack in literature of complete RCTs on the efficacy of systemic antibiotic therapy of GO, mainly due to the absence of precise diagnostic methods and tools and of an adequate classification aimed to determine a correct prognosis and an appropriate therapy for GO.

In literature there are few RCTs on the efficacy of systemic antibiotic therapy of GO and it is mainly due to the absence of precise diagnostic tools and of an adequate classification aimed to determine a correct prognosis and an appropriate therapy for GO.

Clustering differs from classification in that classification aims to assign data instances to predefined classes, while clustering aims to group-related data instances together without labeling them.

This study concluded that the GEOIC approach on land type classification is significant and appears potential for land type classification aiming to land assessment and planning.

Findings are structured according to Köppen Geiger climate classification, aiming to investigate the prevalence of research conducted in different climate zones.

Ecological land classification aims to efficiently manage natural resources, and is often used as an effective approach for solving environmental problems.

This classification aims to encompass these challenges; however, it may underestimate non-anatomical issues.

7– 9 The UICC TNM classification aims to reflect the outcome of patients with perihilar cholangiocarcinoma.

We conclude our work in Section 7. Classification aims to build an efficient and effective model for predicting class labels of unknown data.