Computer and Mathematical Modeling: Translational Research and Economics in Clinical Diagnostics

The computer and modeling approach has begun to be used extensively in clinical intelligence diagnosis, we have refined the necessary techniques related to intelligence medicine, and we have performed economics-directional analysis of models and structures of artificial intelligence in the translational medicine sense.At the same time, the development of clinical diagnostic techniques is also the result of constant innovation, and we propose the necessary strategy for a cross-disciplinary approach to clinical diagnostics and computer and mathematical modeling, with the authors reporting in conjunction with the results of the study

From the Perspective of Robotic Research and Development in Medicine: Analysis of Principles for the Application of Circulating Neural Networks and the Design of Economic Products in Biomedical Medicine

The circulatory neural network is an important component part of the artificial neural network and can be integrated into biomedical engineering for disease warning in current frontier research. In the current market economy, women's sexual pleasures can be designed using the circulatory neural network as a core biomedical engineering device. We performed technical analysis, expound the principles of neuroscience, and report and analyze them

Sharp high-probability sample complexities for policy evaluation with linear function approximation

This paper is concerned with the problem of policy evaluation with linear function approximation in discounted infinite horizon Markov decision processes. We investigate the sample complexities required to guarantee a predefined estimation error of the best linear coefficients for two widely-used policy evaluation algorithms: the temporal difference (TD) learning algorithm and the two-timescale linear TD with gradient correction (TDC) algorithm. In both the on-policy setting, where observations are generated from the target policy, and the off-policy setting, where samples are drawn from a behavior policy potentially different from the target policy, we establish the first sample complexity bound with high-probability convergence guarantee that attains the optimal dependence on the tolerance level. We also exhihit an explicit dependence on problem-related quantities, and show in the on-policy setting that our upper bound matches the minimax lower bound on crucial problem parameters, including the choice of the feature maps and the problem dimension.Comment: The first two authors contributed equall

Effects of Excitation Angle on Air-Puff-Stimulated Surface Acoustic Wave-Based Optical Coherence Elastography (SAW-OCE)

Increased stiffness of tissues has been recognised as a diagnostic feature of pathologies. Tissue stiffness characterisation usually involves the detection of tissue response from mechanical stimulation. Air-puff optical coherence elastography (OCE) can generate impulse surface acoustic waves (SAWs) on tissue surface without contact and evaluate the mechanical properties of tissue. This study endeavours to explore the optimal excitation angle for air-puff OCE, a parameter that lacks standardisation at present, by investigating the relationship between the frequency bandwidth and peak-to-peak signal-to-noise ratio (SNR) of SAWs for different excitation angles (relative to the normal surface) of air-puff on the sample, from 5° to 85°, with an interval of 5° applied on the phantom. Due to the unevenness of human hands, 20°, 45° and 70° angles were employed for human skin (10 healthy adults). The results show that a smaller excitation angle could produce higher wave frequency bandwidth; a 5° angle generated an SAW with 1747 Hz frequency bandwidth, while an 85° angle produced an SAW with 1205 Hz. Significant differences were not shown in peak-to-peak SNR comparison between 5° and 65° on the phantom, but between 65° and 85° at the excitation position, a reduction of 48.6% was observed. Furthermore, the group velocity of the SAWs was used to evaluate the bulk Young’s modulus of the human tissue. The outcomes could provide essential guidance for air-puff-based elastography studies in clinical applications and future tissue research.<br/