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HEALTH PSYCHOLOGY IN INTEGRATIVE HEALTH CARE
The 8th International Conference of Indian Academy of Health Psychology (ICIAHP 2023) gathered leading experts, researchers, and professionals to exchange insights and explore innovations in mental and physical well-being. Featuring workshops on trauma release, hypnotherapy basics, mindfulness-based CBT, and suicide prevention, ICIAHP offered a diverse learning experience. Distinguished speakers from national and international universities attended the conference. The conference catered to health psychology professionals, researchers, educators, and scholars. ICIAHP 2023 stood out for its comprehensive program, renowned speakers, and ample networking, providing a platform for holistic learning and collaboration. 2024 selection and editorial matter, Dr. Sundeep Katevarapu, Dr. Anand Pratap Singh, Dr. Priyanka Tiwari, Ms. Akriti Varshney, Ms. Priya Lanka, Ms. Aankur Pradhan, Dr. Neeraj Panwar, Dr. Kumud Sapru Wangnue; individual chapters, the contributors. -
Healthcare and wearables in smart cyber-physical systems
[No abstract available] -
Healthcare cloud services in image processing
Technology has been fundamental in defining, advancing, and reinventing medicalpractises, equipment, and drugs during the last century. Although cloud computing is quite a newer concept, it is now one of the most often discussed issues in academic and therapeutic contexts. Many academics and healthcare persons are focused in providing vast, conveniently obtainable, and reconstruct assets like virtual frameworks, platforms, and implementations having lesser business expenditures. As they need enough assets to operate, store, share, and utilise huge quantity of healthcare data, specialists in the field of medicine are transferring their operations in the cloud. Major issues about the application of cutting-edge cloud computing in medical imaging are covered in this chapter. The research also takes into account the ethical and security concerns related to cloud computing. 2023, IGI Global. All rights reserved. -
Healthcare Metaverse
Discussions regarding metaverse technologies are happening all over the place, from universities to business tycoons. A lot of people are thinking about how to make their apps work better in the metaverse. To better serve their patients, more and more healthcare firms are embracing the metaverse. In this research, healthcare metaverses are examined. We show how to improve healthcare services in the metaverse and increase patient use cases by using safer approaches to managing chronic diseases, mental health, and fitness. With the advent of digital twins, artificial intelligence (AI), immersive technologies, the Internet of Things (IoT), and blockchain (BC), new possibilities in healthcare are emerging in the metaverse. These innovations have the potential to change the way people perceive healthcare, save costs, and enhance patient outcomes. Healthcare may be revolutionized by using AI and BC technology to sift through massive amounts of data and develop individualized treatment regimens. But IoT devices gather vital data for patient therapy instantly. The healthcare system and people's lives throughout the globe may both benefit from these concepts coming together. The recommendations made in this article should be adhered to ensure that digital procedures continue to benefit customers. 2026 Scrivener Publishing LLC. -
Healthcare performance optimization
Healthcare systems worldwide are in huge pressure to enhance their performances for the rising demands to manage quality care, costs, and resource utilization efficiently. This research focuses on exploring Healthcare Performance Optimization. Specifically, it deals with efficiency in operations, patients, and resources. Strategic alignment is achieved through appropriate use of Key Performance Indicators (KPIs) in healthcare institutions. It's, therefore, an emerging approach integrating DEA and ML that helps address inefficiencies, predict outcomes, and create an opportunity for continuous improvement in the delivery of healthcare. The CCR and BCC-DEA models help determine technical and pure technical efficiency among healthcare providers. Simultaneously, Moreover, this research also focuses on sustainable healthcare and its role in the fight against climate change, resource depletion, and health disparities. Sustainable practices ensure that health care is accessible equitably while conserving resources and environmental integrity. 2025 by IGI Global Scientific Publishing. All rights reserved. -
Healthy healthcare systems in India: A prognosis
India has been an emerging economy which has retained its second position in the global healthcare market that has been tackling its economic gaps, shifting demographics, thereby, facing a wide gap between the demand and supply of healthcare products and services due to technology and increasing cost. Affordable treatment facilities for the economically low strata is still a dream. The government scheme of "Swachh Bharat Abhiyan" and "Ayushman Bharat Yojna" are the steps to uplift the backward community and make all the facilities available to them at the lowest possible cost directly and indirectly. Hence, the objective of this research was to unfold the three pillars of Healthy Healthcare which revolves around healthcare systems in India, Healthcare Employees' wellbeing and resultant patient outcomes. This research also tried studying various interventions that can be taken to improve the present scenario of affordable and quality service to the needy people. Springer Nature Switzerland AG 2020. -
Heart Disease Prediction Using Ensemble Voting Methods in Machine Learning
Heart disease is the leading cause of mortality globally according to the World Health Organization. Every year, it results in millions of mortalities and thus billions of dollars in economic damage throughout the world. Many lives can be saved if the disease is detected early and accurately. The typical methods to predict or diagnosis heart diseases require medical expertise. Such facilities and experts are relatively expensive and not very commonly available in under developed and developing countries. Recent times, much research is done on leveraging technology for the prediction as well as diagnosis of heart diseases. Machine Learning techniques have been extensively deployed as quick, inexpensive, and noninvasive ways for heart disease identification. In this work, we present a machine learning approach in detecting heart disease using a dataset that contains vital body parameters. We used seven different models and combined them with Soft-Voting and Hard-Voting ensemble approaches to improve accuracy in 7-model and various 5-model combinations. The ensemble combinations of 5 models achieved the highest test accuracy score of 94.2%. 2022 IEEE. -
Heart Disease PredictionA Computational Machine Learning Model Perspective
Relying on medical instruments to predict heart disease is either expensive or inefficient. It is important to detect cardiac diseases early to avoid complications and reduce the death rate. This research aims to compare various machine learning models using supervised learning techniques to find a better model that gives the highest accuracy for heart disease prediction. This research compares standalone and ensemble models for prediction analysis. Six standalone models are logistic regression, Naive Bayes, support vector machine, K-nearest neighbors, artificial neural network, and decision tree. The three ensemble models include random forest, AdaBoost, and XGBoost. Feature engineering is done with principal component analysis (PCA). The experimental process resulted in random forest giving better prediction analysis with 92% accuracy. Random forest can handle both regression and classification tasks. The predictions it generates are accurate and simple to comprehend. It is capable of effectively handling big datasets. Utilizing numerous trees avoids and inhibits overfitting. Instead of searching for the most prominent feature when splitting a node, it seeks out an optimal feature among a randomly selected feature set in order to minimize the variance. Due to all these reasons, it has performed better. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
HEART FAILURE DETECTION USING OPTIMIZATION ALGORITHMS
Heart failure (HF) remains a significant global health challenge, requiring early and precise detection to improve clinical outcomes and reduce mortality rates. Traditional diagnostic approaches often fail to capture the complexity of HF pathophysiology, necessitating advanced computational methods for accurate prediction. In this study, we propose a novel optimized Stacked Support Vector Machine (S-SVM) framework, integrating multiple SVM classifiers with diverse kernel functions to enhance predictive accuracy. A genetic algorithm (GA) is employed to fine-tune hyperparameters, ensuring model robustness and generalizability across patient populations. The model is rigorously evaluated on the UCI Heart Failure Clinical Records Dataset and the Framingham Heart Study Dataset, demonstrating superior performance in accuracy (95.7%), precision (0.90), recall (0.87), and AUC (0.96) compared to conventional machine learning techniques. The proposed system effectively balances computational efficiency with clinical interpretability, making it a promising tool for early-stage HF detection and risk stratification. This research advances the intersection of machine learning and cardiovascular diagnostics, offering a scalable and adaptive solution for real-world healthcare applications. Little Lion Scientific. -
Heat amd Mass Transfer Analyses of Nanofluid in a Multilayer Model
The study offers an in-depth exploration into the dynamics and properties of multilayered nanofluids and hybrid nanofluid flow in newlinedifferent geometries. The in-vestigation ranges from sinusoidal channels with micropolar hybrid nanoliquids to concentric cylinders that exhibit electrokinetic effects and rotating disks. Also, the DarcyForchheimer model is introduced to assess non-Newtonian and Newtonian fluid interplay, emphasizing the role of asymmetric slip conditions which reduces the fluid flow. Moreover, the study on bioconvection obtained newlineby addition of gyrotac-tic microorganisms which enhances mass and heat transfer in multilayer Newtonian fluid channels. Studies explain the importance of interfacial regions in achieving optimal system temperature. The subsequent study examines the two-layer hybrid nanofluid (HNF) with magnetohydrodynamic properties between two newlineidentical ro-tating disks. The governing equations of the mathematical models are explained using PDE and solutions are attained using numerical and semi-analytical methods such as the DTM and Range Kutta method. Further, the obtained results have been explained with the help of tables and graphs. The study reveals that the immisci-bility of the base fluids forms an interfacial layer, revealing that the addition of two different fluids restricts the fluid motion nearer to the interfacial region, maintaining an optimum temperature in the system. Collectively, these findings pave the way for advanced applications in industries like solar, nuclear, biomedical, and electronic cooling, promising enhanced newlineperformance and efficiency. -
Heat and mass transfer analysis of Casson-based hybrid nanofluid flow in the presence of an aligned magnetic field: An application toward mechanical engineering
This examination explores the flow of a hybridized nanofluid (HyNf) containing silica and tin oxide nanoparticles mixed with engine oil (EO/SnO2-SiO2). The flowing occurs via a permeable material constrained by a semi-infinite flat plate. The study takes into account various factors such as convective heat and mass transference, chemical reactions, the Dufour effect, the Lorentz force, thermal radiative fluxing, and radiative absorbing. The research involves converting the managing formulas of the flowing model into a dimensionless form and applying the regular perturbation procedure to find solutions for the rate of fluid flow, temperature, and species diffusion. The surface frictional factor, Nusselt quantity, and Sherwood quantity reflect the shearing stress, rates of heat transference, and rates of mass transport at the plate, respectively. An analysis is conducted on the impact of several factors, including the suction variable, magnetic variable, radiation-absorbing factor, Casson parameter, and Dufour number, on the flow and related quantities. This analysis is based on an examination of graphs and tables. The findings suggest that the heat transference rate in the Casson hybridized nanofluid is better than that in the mono nanofluid. It is exposed that the temperature reduces at the plate having improved frequency of oscillation and also fluid velocity declines for improving values of aligned magnetized field (Formula presented.), but it shows the reverse phenomenon with Gr1 and Gc1. IMechE 2024. -
Heat and Mass Transfer Analysis of Newtonian and Non-Newtonian Nanofluids in The Presence of Motile Microorganisms
This dissertation deals with the analysis of heat and mass transfer in Newtonian and newlinenon-Newtonian nanoand#64258;uid in the presence of motile microorganisms. The major application of the and#64258;uids in heat and mass transfer process is its capability to conduct heat. Hence, the and#64258;uids act as a source that conducts heat and cools down the temperature of the appliance. Whereas, the capacity of heat conductance is low in case of regular and#64258;uids, hence the concept of nanoand#64258;uids was introduced whose thermal conductivity is more when compared to regular and#64258;uids. The high thermal conductivity of nanoparticles helps in conducting more heat and the property of and#64258;uid to and#64258;ow helps the nanoparticles to and#64258;ow all over the desired surface and conduct heat. During the process of nanoand#64258;uid and#64258;ow, the nanoparticles undergo random motion that is termed as Brownian motion and they also experience the thermophoretic force that causes the nanoparticles to move from hotter region to colder region. Further, the presence of nanoparticles would either result in sedimentation or formation a layer of nanoparticles over the surface. This layer of nanoparticles adhered to the surface creates corrosion. Hence, it is important to prevent the nanoparticles from forming its layer over the surface and also the sedimentation of nanoparticles must be avoided to have no blockages in the system. Hence in this regards, self propelled microorganisms newlineare allowed to swim in the nanoand#64258;uid which in turn constitutes bioconvection. Considering these assumptions, problems in this dissertation are modelled such that it deals with the analysis of bioconvection caused due to the swimming of microorganisms in the and#64258;ow newlineof nanoand#64258;uid. The mathematical models of the and#64258;ow, heat and mass transfer of Newtonian and non Newtonian nanoand#64258;uids are designed using the partial differential equations with various assumptions to achieve realistic results. -
Heat and mass transfer effects on non-newtonian fluid flow over an unsteady stretching surface with viscous dissipation and thermal radiation
This paper analyzes the flow, heat and mass transfer characteristics of non-Newtonian Casson fluid towards an unsteady permeable stretching surface. An external transverse magnetic field is applied normal to the sheet. The effects of viscous dissipation and thermal radiation are considered in energy equation. Rosseland approximation is used to model the radiative heat transfer. With the aid of similarity transformations, the unsteady boundary layer equations are transformed into a set of non-linear ordinary differential equations. Numerical solutions of resulting non-linear differential equations are solved by using efficient fourth-fifth order Runge-Kutta Feldberg method. The obtained numerical results are compared and found to be in good agreement with previously published results. Behavior of emerging parameters on velocity, temperature and concentration profiles are discussed and presented graphically. Further, variation of the reduced skin friction coefficient, Nusselt and Sherwood number against physical parameters in graphical and tabular form are presented and discussed in detail. It is found that the effects of thermal radiation and viscous dissipation are favorable for thickening the thermal boundary layer. 2018 Pushpa Publishing House, Allahabad, India. -
Heat and mass transfer of AgH2O nano-thin film flowing over a porous medium: A modified Buongiorno's model
Due to their numerous applications, such as fibre and wire coating, polymer preparation, etc., thin films have recently come into focus in the analysis of heat and mass transport. As a result, the current article's main objective is to investigate how heat and mass are transferred when an AgH2O (sliverwater) thin film flows past a stretching sheet that is subject to thermal and velocity slips. The research takes into account other variables including porosity, thermal radiation, thermophoresis, and Brownian motion, among others, to ensure that the outcomes are consistent with real-world conditions. Along with these parameters, the impact of the nanoparticle volume fraction is also analysed by incorporating the modified model of the existing Buongiorno model. The resulting mathematical model is transformed into ordinary differential equations with the help of appropriate similarity transformation. The system of equations thus obtained is solved by employing the RKF-45 technique and the outcomes are expressed in terms of graphs and tables. The major outcomes indicate that the increase in the mixed convection parameter causes enhancement in the temperature profile while a reduction in the velocity profile. The thermophoresis is found to increase both the temperature and concentration profiles of the thin film. Whereas, the greater values of the volume fraction of the nanoparticles enhance the temperature and diminishes the velocity. 2023 The Physical Society of the Republic of China (Taiwan) -
Heat and mass transfer of triple diffusive convection in boussinesq-stokes suspension using ginzburg-landau model
The nonlinear stability of triple diffusive convection in Boussinesq-Stokes suspension is analysed by using Ginzburg-Landau model. Using the Bernoulli equation obtained from Ginzburg-Landau model, Nusselt number and Sherwood numbers of different solutes are studied to quantify the heat and mass transfer. It is found that the effect of couple stress parameter is to stabilize the system. 2017 Pushpa Publishing House, Allahabad, India. -
Heat and mass transfer of triple diffusive convection in viscoelastic liquids under internal heat source modulations
The influence of sinusoidal (trigonometric cosine [TC]) and nonsinusoidal waveforms (square, sawtooth, and triangular) of internal heat source modulation on triple diffusive convection in viscoelastic liquids is investigated. An Oldroyd-B type model is taken into account for viscoelastic liquids. Nonlinear analysis is carried out using a truncated representation of the Fourier series. To analyze the heat and mass transfer over a triply diffusive liquid layer, expressions for average Nusselt and average Sherwood numbers are derived using 8-mode generalized Lorenz equations. The transient behavior of Nusselt and Sherwood numbers is analyzed on different parameters of the problem. From the results, it is found that the internal heat source enhances the heat transfer and diminishes the mass transfer while the heat sink diminishes the heat transfer and enhances the mass transfer. The results for respective waveforms are obtained for each parameter and it is found that the maximum heat and mass transfer occurs due to TC waveform. The limiting cases of viscoelastic liquids (Newtonian, Oldroyd-B, Maxwell, and RivlinEricksen) have been tabulated and corresponding results for each of the waveforms onheat and mass transfer have been shown. 2021 Wiley Periodicals LLC -
Heat and Mass Transport in Casson Nanofluid Flow over a 3-D Riga Plate with Cattaneo-Christov Double Flux: A Computational Modeling through Analytical Method
This work examines the non-Newtonian Cassonnanofluids three-dimensional flow and heat and mass transmission properties over a Riga plate. The Buongiorno nanofluid model, which is included in the present model, includes thermo-migration and random movement of nanoparticles. It also took into account the CattaneoChristov double flux processes in the mass and heat equations. The non-Newtonian Casson fluid model and the boundary layer approximation are included in the modeling of nonlinear partial differential systems. The homotopy technique was used to analytically solve the systems governing equations. To examine the impact of dimensionless parameters on velocities, concentrations, temperatures, local Nusselt number, skin friction, and local Sherwood number, a parametric analysis was carried out. The velocity profile is augmented in this study as the size of the modified Hartmann number increases. The greater thermal radiative enhances the heat transport rate. When the mass relaxation parameter is used, the mass flux values start to decrease. 2023 by the authors. -
Heat Convection in a Viscoelastic Nanofluid Flow: A Memory DescriptiveModel
Modeling of physical phenomena with fractional differential equations is as old as modeling with ordinary differential equations. There are two stages in modeling of a memory process. One of them is short with persistent impact and other is usually governed by fractional mathematical model. It is established that fractional models fit the experimental data for the memory phenomena in better way when compared with the ordinary models, particularly in mechanics, psychology and in biology. Fractional model of viscoelastic nanofluid flow through permeable medium is studied in this communication. Convection parameters in the flow domain are used to account for buoyancy forces. The governing flow equations are computed using a numerical algorithm that combines finite difference and finite element techniques. The governing models friction coefficient, Sherwood numbers, and Nusselt numbers are calculated. Change in noninteger numbers behave similarly in concentration, temperature, and velocity fields, according to simulations. It is also noted that heat flux, ?1 and mass flux, ?2 numbers have contradictory effects on friction coefficient. Various flow patterns, particularly in the polymer industry and electrospinning for nanofiber manufacture, can be addressed in a similar manner 2023 L&H Scientific Publishing, LLC. All rights reserved -
Heat transfer and entropy generation analysis of non-Newtonian fluid flow through vertical microchannel with convective boundary condition
The entropy generation and heat transfer characteristics of magnetohydro-dynamic (MHD) third-grade fluid flow through a vertical porous microchannel with a convective boundary condition are analyzed. Entropy generation due to flow of MHD non-Newtonian third-grade fluid within a microchannel and temperature-dependent viscosity is studied using the entropy generation rate and Vogels model. The equations describing flow and heat transport along with boundary conditions are first made di-mensionless using proper non-dimensional transformations and then solved numerically via the finite element method (FEM). An appropriate comparison is made with the pre-viously published results in the literature as a limiting case of the considered problem. The comparison confirms excellent agreement. The effects of the Grashof number, the Hartmann number, the Biot number, the exponential space-and thermal-dependent heat source (ESHS/THS) parameters, and the viscous dissipation parameter on the temperature and velocity are studied and presented graphically. The entropy generation and the Bejan number are also calculated. From the comprehensive parametric study, it is recognized that the production of entropy can be improved with convective heating and viscous dissipation aspects. It is also found that the ESHS aspect dominates the THS aspect. Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature 2019. -
Heat transfer enhancement due to nanoparticles, magnetic field, thermal and exponential space-dependent heat source aspects in nanoliquid flow past a stretchable spinning disk
This study explores the heat transfer characteristics of nanoliquid flowing over a rotating disk in the presence of the applied magnetic field and convective boundary condition. The nanoliquid is flowing due to the rotation of the disk with uniform stretching of a disk along the radial direction. Effects of ESHS (exponential space-related heat source) and THS (thermal-related heat source) are the focal concern of this article. The effective thermal conductivity of ethylene glycol (EG)-based graphene oxide (GO) nanoliquid is estimated by using Nans model whereas effective dynamic viscosity is calculated through Brinkman model. The partial differential system which governed the problem is transformed by using Von-Karman stretching transformations to the ordinary differential system. The subsequent two-point ODBVP (ordinary differential boundary value problem) is treated numerically. The consequence of effective parameters of the problem on different flow fields is illustrated graphically. The numerical values of shear stress and heat transfer rate (Nusselt number) are also calculated. Further, the slope of the data points is determined to quantify the outcome. Validation of the present results is made by direct comparison with the available results and an excellent agreement is found. It is found that the rate of heat transfer increased with nanoparticle volume fraction at the rate 0.4153 and the friction factor increased by increasing nanoparticle volume fraction at the rate 3.0681. The fluctuation rate of Nusselt number due to the variation of the ESHS parameter is almost three times more than that of THS parameter. 2020, Akadiai Kiad Budapest, Hungary.