Forecasting of rehabilitation treatment in sufferers from lateral displacement of patella using artificial intelligence
In this research, the application of artificial intelligence methods for data analysis named hybrid artificial neural network (ANN) with teaching learning based optimization (TLBO) algorithm to predict of the rehabilitation treatment for females with lateral displacement of the patella (LDP) is demonstrated.
The prediction abilities offered using ANN-TLBO model was presented using available data from 48 female patients referred to physical medicine and rehabilitation clinics of Isfahan Ayatollah Kashani medical center and Al Zahra hospital, Iran. In this modeling, clinical characteristics [weight, height, body mass index (BMI), the degree of LDP, affected side and severity of pain] and demographic characteristic (age) were utilized as the input parameters, while the rehabilitation treatment was the output parameter.
Results and discussion
The results indicate a high level of efficient of ANN-TLBO model used with an accuracy level of more than 86%. Therefore, this model can be used successfully for the prediction of rehabilitation treatment for females with LDP.
KeywordsRehabilitation treatment Lateral displacement of patella Artificial neural network Teaching learning based optimization
The authors thank the authorities of physical medicine and rehabilitation clinics of Isfahan Ayatollah Kashani medical center and Al Zahra hospital, Iran for their cooperation.
Compliance with ethical standards
Conflict of interest
The authors declared no conflict of interests.
An institutional review board approved all procedures before testing.
Prior to participation; all subjects were informed of the nature of the study and gave their written consent to participate.
- 16.Juhn MS (1999) Patellofemoral pain syndrome: a review and guidelines for treatment. Am Fam Phys 60(7):2012–2022Google Scholar
- 24.Mohammadi Asl J, Kahrizi S, Ebrahimi E, Faghihzadeh S (2008) The effect of short-term usage of rigid neoprene knee sleeve and soft neoprene knee sleeve on knee joint position sense perception after reconstruction surgery of anterior cruciate ligament. World J Sport Sci 1(1):42–47Google Scholar
- 31.Shanthi D, Sahoo G, Saravanan N (2009) Designing an artificial neural network model for the prediction of thrombo-embolic stroke. Int J Biom Bioinform 3(1):10–18Google Scholar
- 35.Paulin F, Santhakumaran A (2011) Classification of breast cancer by comparing back propagation training algorithms. Int J Comput Sci Eng 3(1):327–332Google Scholar
- 36.Al Timemy AHA, Al Naima F (2010) Comparison of different neural network approaches for the prediction of kidney dysfunction. Int J Biol Life Sci 6:84–90Google Scholar
- 37.Monadjemi S, Moallem P (2008) Automatic diagnosis of particular diseases using a fuzzy-neural approach. Int Rev Comput Softw 3(4):406–411Google Scholar
- 48.Simpson PK (1991) Artificial neural systems: foundations, paradigms, applications, and implementations. Windcrest/McGraw-Hill, New YorkGoogle Scholar