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Data-Driven Healthcare:The Role of Computational Methods in Medical Innovation

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Computer Modeling in engineering & Sciences 2025年第1期142卷 1-48页

作者： Hariharasakthisudhan Ponnarengan Sivakumar Rajendran Vikas Khalkar Gunapriya Devarajan Logesh Kamaraj department of Mechanical engineering Dr.Mahalingam College of Engineering and TechnologyPollachiCoimbatoreTamil Nadu642003India department of Mechanical engineering JKKN College of Engineering and TechnologyKumarapalayamNamakkalTamil Nadu637209India department of Mechanical engineering Gharda Institute of TechnologyLavelMaharashtra415708India department of Electrical and electronics engineering Sri Eshwar College of EngineeringCoimbatoreTamilnadu641202India department of Mechanical engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyChennai600062India

The purpose of this review is to explore the intersection of computational engineering and biomedical science,highlighting the transformative potential this convergence holds for innovation in healthcare and medical *** review covers key topics such as computational modelling,bioinformatics,machine learning in medical diagnostics,and the integration of wearable technology for real-time health *** findings indicate that computational models have significantly enhanced the understanding of complex biological systems,while machine learning algorithms have improved the accuracy of disease prediction and *** synergy between bioinformatics and computational techniques has led to breakthroughs in personalized medicine,enabling more precise treatment ***,the integration of wearable devices with advanced computational methods has opened new avenues for continuous health monitoring and early disease *** review emphasizes the need for interdisciplinary collaboration to further advance this *** research should focus on developing more robust and scalable computational models,enhancing data integration techniques,and addressing ethical considerations related to data privacy and *** fostering innovation at the intersection of these disciplines,the potential to revolutionize healthcare delivery and outcomes becomes increasingly attainable.

关键词： Computational models biomedical engineering bioinformatics machine learning wearable technology

Three-Stage Transfer Learning with AlexNet50 for MRI Image Multi-Class Classification with Optimal Learning Rate

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Computer Modeling in engineering & Sciences 2025年第1期142卷 155-183页

作者： Suganya Athisayamani A.Robert Singh Gyanendra Prasad Joshi Woong Cho School of Computing Sastra Deemed to be UniversityThanjavur613401India department of Computational Intelligence SRM Institute of Science and TechnologyKattankulathur603203India department of AI and Software engineering Kangwon National UniversitySamcheok25913Republic of Korea department of electronics Information and Communication EngineeringKangwon National UniversitySamcheok25913Republic of Korea

In radiology,magnetic resonance imaging(MRI)is an essential diagnostic tool that provides detailed images of a patient’s anatomical and physiological *** is particularly effective for detecting soft tissue ***,radiologists manually interpret these images,which can be labor-intensive and time-consuming due to the vast amount of *** address this challenge,machine learning,and deep learning approaches can be utilized to improve the accuracy and efficiency of anomaly detection in MRI *** manuscript presents the use of the Deep AlexNet50 model for MRI classification with discriminative learning *** are three stages for learning;in the first stage,the whole dataset is used to learn the *** the second stage,some layers of AlexNet50 are frozen with an augmented dataset,and in the third stage,AlexNet50 with an augmented dataset with the augmented *** method used three publicly available MRI classification datasets:Harvard whole brain atlas(HWBA-dataset),the School of Biomedical engineering of Southern Medical University(SMU-dataset),and The National Institute of Neuroscience and Hospitals brain MRI dataset(NINS-dataset)for *** hyperparameter optimizers like Adam,stochastic gradient descent(SGD),Root mean square propagation(RMS prop),Adamax,and AdamW have been used to compare the performance of the learning ***-dataset registers maximum classification *** evaluated the performance of the proposed classification model using several quantitative metrics,achieving an average accuracy of 98%.

关键词： MRI tumors classification AlexNet50 transfer learning hyperparameter tuning optimizer

Analysis of OSA Syndrome from PPG Signal Using CART-PSO Classifier with Time Domain and Frequency Domain Features

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Computer Modeling in engineering & Sciences 2019年第2期118卷 351-375页

作者： N.Kins Burk Sunil R.Ganesan B.Sankaragomathi department of Biomedical engineering Sethu Institute of TechnologyVirudhunagarIndia department of electronics and instrumentation engineering Saveetha Engineering CollegeChennaiIndia department of electronics and instrumentation engineering National Engineering CollegeKovilpattiIndia.

Obstructive Sleep Apnea(OSA)is a respiratory syndrome that occurs due to insufficient airflow through the respiratory or respiratory arrest while sleeping and sometimes due to the reduced oxygen *** aim of this paper is to analyze the respiratory signal of a person to detect the Normal Breathing Activity and the Sleep Apnea(SA)*** the proposed method,the time domain and frequency domain features of respiration signal obtained from the PPG device are *** features are applied to the Classification and Regression Tree(CART)-Particle Swarm Optimization(PSO)classifier which classifies the signal into normal breathing signal and sleep apnea *** proposed method is validated to measure the performance metrics like sensitivity,specificity,accuracy and F1 score by applying time domain and frequency domain features ***,the performance of the CART-PSO(CPSO)classification algorithm is evaluated through comparing its measures with existing classification ***,the effect of the PSO algorithm in the classifier is validated by varying the parameters of PSO.

关键词： Obstructive sleep apnea photoplethysmogram signal time domain features frequency domain features classification and regression tree classifier particle swarm optimization algorithm.

Hybrid Active Contour Mammographic Mass Segmentation and Classification

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Computer Systems Science & engineering 2022年第3期40卷 823-834页

作者： K.Yuvaraj U.S.Ragupathy department of electronics and instrumentation engineering Kongu Engineering College PerunduraiErode638060India

This research implements a novel segmentation of mammographic *** methods are proposed,namely,segmentation of mass based on iterative active contour,automatic region growing,and fully automatic mask selectionbased active contour *** the first method,iterative threshold is performed for manual cropped preprocessed image,and active contour is applied *** overcome manual cropping in the second method,an automatic seed selection followed by region growing is *** that the result is only a few images owing to over segmentation,the third method uses a fully automatic active *** of the segmentation techniques are compared with the manual markup by experts,specifically by taking the difference in their mean ***,the difference in the mean value of the third method is 1.0853,which indicates the closeness of the ***,the proposed method is compared with the existing fuzzy C means and level set *** automatic mass segmentation based on active contour technique results in segmentation with high *** using adaptive neuro fuzzy inference system,classification is done and results in a sensitivity of 94.73%,accuracy of 93.93%,and Mathew’s correlation coefficient(MCC)of 0.876.

关键词： Feature optimization hybrid active contour segmentation mass classification mass feature extraction medical image analysis

Recursive adaptive filter using current innovation for celestial navigation during the Mars approach phase

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Science China(Information Sciences) 2017年第3期60卷 168-182页

作者： Xiaolin NING Zhuo LI Weiren WU Yuqing YANG Jiancheng FANG Gang LIU School of instrumentation Science & Opto-electronics engineering Beihang University

Celestial navigation is a commonly used autonomous navigation technique for deep space navigation.A nonlinear filter such as the unscented Kalman filter(UKF) is typically applied in a celestial navigation system(CNS). However, on account of being subject to a number of factors, such as ephemeris errors and centroid determination, the measurement model error of a CNS cannot be accurately determined. The analysis conducted in this study also shows that the measurement model error is time-variant during the Mars approach *** implies that covariance matrix of the measurement error R is usually inaccurate, which may induce large estimation errors that even result in filter divergence. Some adaptive methods are able to address this ***, traditional adaptive filters, for scaling R, usually require a sequence of innovation and are affected by the statistic window size. A new recursive adaptive UKF(RAUKF) is proposed in this paper, which only uses current innovation to scale R. The navigation performance of the proposed RAUKF method is compared with some traditional adaptive filters through simulations. The results show that this method is better than traditional adaptive filters in a CNS during the Mars approach phase.

关键词： deep space adaptive UKF navigation Mars approach variant noise

New rapid transfer alignment method for SINS of airborne weapon systems

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Journal of Systems engineering and electronics 2014年第2期25卷 281-287页

作者： Yu Chen Yan Zhao School of instrumentation Science and Opto-electronics engineering Beihang University

Transfer alignment is an effective alignment method for the strapdown inertial navigation system （SINS） of airborne weapon systems. The traditional transfer alignment methods for large misalignment angles alignment use nonlinear transfer align- ment models and incorporate nonlinear filtering. A rapid transfer alignment method with linear models and linear filtering for ar- bitrary misalignment angles is presented. Through the attitude quaternion decomposition, the purpose of transfer alignment is converted to estimate a constant quaternion. Employing special manipulations on measurement equation, velocity and attitude linear measurement equations are derived. Then the linear trans- fer alignment model for arbitrary misalignment angles is built. An adaptive Kalman filter is developed to handle modeling errors of the measurement noise statistics. Simulation results show feasibili- ty and effectiveness of the proposed method, which provides an alternative rapid transfer alignment method for airborne weapons.

关键词： strapdown inertial navigation system (SINS) transferalignment Kalman filter quaternion.

Trinary magnitude comparator using SLM based Savart plate

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Optoelectronics Letters 2019年第6期15卷 415-419页

作者： Animesh Bhattacharya Shyandeep Das Arijit Sarkar Nabanita Bose Amal K Ghosh department of Applied electronics and instrumentation engineering Netaji Subhash Engineering College

The demand of present technology inviting the popularity of multivalued optical computation system to coup up with the latest scenario of ultrahigh processing speed and handling large amount of data The magnitude comparator is the heart of the arithmetic and logic unit(ALU)in any logical processing and computing *** this paper,a trinary magnitude comparator circuit has been proposed and implemented with modified trinary number(MTN)*** tree architecture(OTA)of the proposed circuit has been realized reasonably using Savart plate and spatial light modulators(SLM).A simulation algorithm has also been developed and implemented to prove the authenticity of the proposed circuit through the simulation.

关键词： comparator system. magnitude

Sliding mode control of reaction flywheel-based brushless DC motor with buck converter

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Chinese Journal of Aeronautics 2013年第4期26卷 967-975页

作者： Liu Gang Zhang Cong School of instrumentation Science and Opto-electronics engineering Beihang University

Reaction flywheel is a significant actuator for satellites＇ attitude control. To improve output torque and rotational speed accuracy for reaction flywheel, this paper reviews the modeling and control approaches of DC-DC converters and presents an application of the variable structure system theory with associated sliding regimes. Firstly, the topology of reaction flywheel is constructed. The small signal linearization process for a buck converter is illustrated. Then, based on the state averaging models and reaching qualification expressed by the Lee derivative, the general results of the sliding mode control （SMC） are analyzed. The analytical equivalent control laws for reaction flywheel are deduced detailedly by selecting various sliding surfaces at electromotion, energy consumption braking, reverse connection braking stages. Finally, numerical and experimental examples are presented for illustrative purposes. The results demonstrate that favorable agreement is established between the simulations and experiments. The proposed control strategy achieves preferable rotational speed regulation, strong rejection of modest disturbances, and high-precision output torque and rotational speed tracking abilities.

关键词： DC-DC converter Flywheels State averaging model Sliding mode control Sliding surface Topology

FDTD technique based crosstalk analysis of bundled SWCNT interconnects

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Journal of Semiconductors 2015年第5期36卷 90-98页

作者： Yograj Singh Duksh Brajesh Kumar Kaushik Rajendra P.Agarwal department of electronics and instrumentation engineering Mahatma Jyotiba Phule Rohilkhand University department of electronics and Communication engineering Indian Institute of Technology Shobhit University

The equivalent electrical circuit model of a bundled single-walled carbon nanotube based distributed RLC interconnects is employed for the crosstalk analysis. The accurate time domain analysis and crosstalk effect in the VLSI interconnect has emerged as an essential design criteria. This paper presents a brief description of the numerical method based finite difference time domain （FDTD） technique that is intended for estimation of voltages and currents on coupled transmission lines. For the FDTD implementation, the stability of the proposed model is strictly restricted by the Courant condition. This method is used for the estimation of crosstalk induced propagation delay and peak voltage in lossy RLC interconnects. Both functional and dynamic crosstalk effects are analyzed in the coupled transmission line. The effect of line resistance on crosstalk induced delay, and peak voltage under dynamic and functional crosstalk is also evaluated. The FDTD analysis and the SPICE simulations are carried out at 32 nm technology node for the global interconnects. It is observed that the analytical results obtained using the FDTD technique are in good agreement with the SPICE simulation results. The crosstalk induced delay, propagation delay, and peak voltage obtained using the FDTD technique shows average errors of 4.9%, 3.4% and 0.46%, respectively, in comparison to SPICE.

关键词： FDTD SWCNT bundle interconnects crosstalk delay peak voltage coupled transmission lines