Neural network based medical decision making using wearable technology

摘要

The process of making suitable decision as well as the ability to independently manage medical conditions for patient is very important for medical students (residents and fellows). A shared decision-making using artificial neural network (NN) is used in this study to optimize decision process. This method will also help medical resident to achieve competence and increase their performance. NN is probably the best model to simulate human brain decision making process. In this study, each input neuron used in the network will represent a decision output of a real physician biological neural network. Numerical values assigned to each neuron in the input layer represent measurable decisions made by each subject matter participants (resident students, fellows and physicians). The output layer represents an aided real time decision which incorporates all processed input values. Several hidden neural layers are also used to process and measure all the data in the network. In traditional schools, high learning performance is usually achieved by reducing the number of students or increasing the number of teachers in class. This proposed method will mimic or create a virtual class where the teachers will outnumber students. Wearable Technology (WT), namely “Google Glass” is used in this process to transmit live video stream via Wi-Fi which could be received by participant's tablet, smart phone or personal computer. This proposed “learning by sharing decision” model may prove effective to medical student outcomes.