Authors :
Seyed Masoud Ghoreishi Mokri; Newsha Valadbeygi; Khafaji Mohammed Balyasimovich
Volume/Issue :
Volume 9 - 2024, Issue 4 - April
Google Scholar :
https://tinyurl.com/yc58epx8
Scribd :
https://tinyurl.com/2mkpyafv
DOI :
https://doi.org/10.38124/ijisrt/IJISRT24APR2410
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Determination and treatment arranging play
a significant part within the field of gastric surgery to
guarantee compelling treatment results. The essential
objective of this inquiry about was to create a novel fake
insights system for making choices concerning surgical
or non-surgical mediations and to survey the extraction
and execution assessment of this show. The think-about
test comprised 200 patients, with 103 cases reserved for
surgical treatment and 97 cases for non-surgical
treatment. The counterfeit neural organize utilized in
this consider comprised 12 input layers, 6 target layers,
and 13 covered-up layers. By utilizing this show, the
victory rate of deciding the requirement for surgical or
non-surgical intercessions, as well as the particular sort
of surgery required, was computed. The ultimate victory
rate of discovery was decided by comparing the genuine
location results with those produced by the
manufactured insights demonstrated. The show
displayed a victory rate of 99.998% for diagnosing the
requirement for surgical or non-surgical mediations and
a 100% exactness rate for deciding the particular sort of
surgery required. This examination underscores the
potential of counterfeit insights models utilizing neural
systems in diagnosing cases requiring gastric surgery.
Keywords :
Gastric Surgery, Neural Network, Matlab, Accuracy, Diagnosis, CNN Neural Network.
Determination and treatment arranging play
a significant part within the field of gastric surgery to
guarantee compelling treatment results. The essential
objective of this inquiry about was to create a novel fake
insights system for making choices concerning surgical
or non-surgical mediations and to survey the extraction
and execution assessment of this show. The think-about
test comprised 200 patients, with 103 cases reserved for
surgical treatment and 97 cases for non-surgical
treatment. The counterfeit neural organize utilized in
this consider comprised 12 input layers, 6 target layers,
and 13 covered-up layers. By utilizing this show, the
victory rate of deciding the requirement for surgical or
non-surgical intercessions, as well as the particular sort
of surgery required, was computed. The ultimate victory
rate of discovery was decided by comparing the genuine
location results with those produced by the
manufactured insights demonstrated. The show
displayed a victory rate of 99.998% for diagnosing the
requirement for surgical or non-surgical mediations and
a 100% exactness rate for deciding the particular sort of
surgery required. This examination underscores the
potential of counterfeit insights models utilizing neural
systems in diagnosing cases requiring gastric surgery.
Keywords :
Gastric Surgery, Neural Network, Matlab, Accuracy, Diagnosis, CNN Neural Network.
