Intelligent Healthcare on Hydrocephalus Management using Artificial Neural Network Algorithm
Anisah Mardiah Binti Suhaimy1, Toni Anwar2

1Anisah Mardiah binti Suhaimy*, CIS Department, University Technology PETRONAS, Tronoh, Malaysia.
2Toni Anwar, Assoc. Prof. CIS Department, University Technology PETRONAS, Tronoh, Malaysia.
Manuscript received on September 10, 2019. | Revised Manuscript received on October 20, 2019. | Manuscript published on October 30, 2019. | PP: 6108-6115 | Volume-9 Issue-1, October 2019 | Retrieval Number: A1977109119/2019©BEIESP | DOI: 10.35940/ijeat.A1977.109119
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Abstract: Shunt efficiency plays an important role in hydrocephalus management. Artificial intelligence has been used far and wide in managing healthcare treatment such example is the use of artificial neural network for increasing shunt device efficiency as through the research done has find that there are gap in current practice. This research focus in improving artificial neural network algorithm to create a more efficient hydrocephalus shunt device that could detect any shunt malfunctions before used clinically on patient. The improved algorithm would also help to ensure a more efficient shunt management, in terms of after shunt insertion; predicting shunt infection to decrease the length of hospitals stays and mortality rate for patients especially for children. The method proposed is by improving the current algorithm that are currently being used by the shunt device to increase its efficiency and also enable advance data collection for more accurate prediction.
Keywords: Artificial Neural Network Algorithm, Hydrocephalus in children, Shunt-device efficiency.