Prediction of Malaysian Talus Bone Morphology Using Artificial Intelligence

Book cover pp 29–37Cite as Part of the Abstract Talus fractures keep on presenting to a difficult and generally experienced gathering of injuries. This published report shows that not all the current bone implants are the ideal counterpart for the specific population. Along these lines, this investigation received a three-dimensional (3D) estimation way to deal with given exact information to the anatomical morphology of talus bone. Seventy-four Malaysian healthy subjects experienced computerized tomography (CT) arthrography. 3D computerized talar models were generated and three morphological boundaries predicted through Mimics and Solidworks software. Sagittal Talar radius (STRa), Throchlea Tali length (TTL), Talar Anterior width (TaAW) are the most part chosen. Information investigation was directed by determination of information test through Matlab programming. In this way, the information was obtained dependent on the artificial intelligence (AI) forecast of the talus bone morphometric. While, the AI strategy demonstrated a more noteworthy limit of forecast in regards to the low level of mistake and high correlative qualities since the average percentage errors of the predicted talus bone morphology parameters are around 10% which 11.3% for STRa, 12.95% for TaAW, and 9.45% for TTL. AI is an exceptionally exact prescient technique and can be utilized as helping instruments in developing bone implant specifically for Malaysian patient and for Asian patient in general