Ijraset Journal For Research in Applied Science and Engineering Technology
Authors: Dr. Kirteebala Pawar, Sharvari Gujarathi , Ritik Gupta, Aasim Khan, Amit Tiwari
DOI Link: https://doi.org/10.22214/ijraset.2024.58371
Certificate: View Certificate
The term \"digital health technology\" describes the application of technology, including telemedicine, m-health, and e-health, to diagnose and enhance healthcare. Plenty of research and advancements in technology have been conducted to enhance and advance the field. Digital health technologies are frequently used in the pharmaceutical industry at different stages of medication design, data analysis for clinical trials, etc. Research and inquiries in the disciplines of biotechnology and bioengineering are increasingly concentrating on technology and healthcare. The study analyzes aspects of the digital ecosystem, digital health, and innovation pertinent to the healthcare industry. By fusing information technology and health services, digital health technology has completely transformed the healthcare sector.
I. INTRODUCTION
Digital health, often known as digital healthcare, is a broad, multidisciplinary idea that encompasses ideas from the point where technology and healthcare converge. By integrating software, hardware, and services, digital health brings digital transformation to the healthcare industry. Wearable technology, telemedicine, which electronic health records, mobile health apps, and personalized devices are numerous instances of digital health technology.
"Application of organized knowledge and skills in the form of devices, medicines, vaccines, procedures and systems developed to solve a health problem and improve quality of health" is how the World Health Organization, or WHO, describes digital health technology. Improvements in patient care, disease management, and operational effectiveness within healthcare systems have benefited from the integration of these technologies. With an emphasis on how digital health technology is influencing the future of healthcare, this seeks to explore the development, significance, difficulties, and prospects of this field.
II. TELEMEDICINE
The American Telemedicine Association defines telemedicine as the "natural evolution of healthcare in the digital world" (1). According to the World Health Organization, "the delivery of healthcare, where distance is a critical factor, by all medical professionals using information and communications technology for the exchange of valid information for the diagnosis, treatment, and prevention of disease and injuries, research and evaluation, and for the ongoing training of health care providers, all in the best interest of advancing the health of individuals and communities" is commonly referred to as telemedicine (2). The practice of using communication networks to treat and diagnose patients virtually from any location in the world is known as telemedicine. Telemedicine is being used by more individuals as payers become aware of the reduced cost of care, doctors become aware of its benefits, and patients (3)
A. The Evolution of Telemedicine
In remote locations with limited access to healthcare, telemedicine gained popularity as a means for people to consult specialists remotely. The U.S. Department of Health and Human Services, NASA, the Public Health Department, and the Department of Defense all devoted time and resources to telemedicine research in the 1960s and 1970s. The collaboration between NASA and the Indian Health Services was one of these government initiatives that was the most successful. Under the Space Technology Applied to Rural Papago Advanced Health Care (STARPAHC) project, medical care was made available to astronauts in orbit as well as Native Americans living on the Papago Reservation in Arizona. Electrocardiographs, X-ray pictures, and other medical data were transferred to and from the Public Health Service hospital via microwave technology. Clinicians from the University of Nebraska were the first to employ video communication for medical purposes.
B. Historical Outlook
The benefit of telemedicine is its long-distance medical data transfer capability. Electrocardiogram transmission over telephone lines was the first documented use of telemedicine in a published paper during the first decade of the twentieth century (1).
The Apollo Hospital in the Andhra Pradesh village of Aragonda in the Chittoor District created the country's first telemedicine program. Through telemedicine, it was connected to Apollo Hospital in Chennai. A few notable instances of the successful use of telemedicine services in India are mammography services at Sri Ganga Ram Hospital in Delhi, oncology at Regional Cancer Center in Trivandrum, and surgical services at Sanjay Gandhi Postgraduate Institute of Medical Sciences in Lucknow (4).
C. Advantages
D. Drawbacks
E. Application
III. E-HEALTH
In the health care sector, where demand for services grows due to an aging population and an influx of new ailments, digitization has proven especially difficult. Therefore, funding for novel therapies is required to ensure that everyone has equitable access to the healthcare system (6,7,8). E-health refers to medical treatments like mobile health and telehealth that use electronic devices to deliver healthcare information, resources, and services (9). Electronic health records (EHRs) or online prescriptions is known as e-health.
A nation's ability to implement e-health is contingent upon a number of elements, such as user acceptance and the kinds of systems, infrastructure, and management that are being used (10,11). The expression "mobile health," or "m health," encompasses the use of mobile devices by patients to manage or monitor treatment or challenges or other health-related issues, use apps to verify information, and electronically demand services (12).
E-health strategies, that involve the creation of norms, laws, or regulations, must be executed in an integrated manner in order to effectively regulate the use of information technologies in healthcare. This is true regardless of the domain—telehealth, mobile health, or specific domains like e-health (learning in health) or electronic medical records. (13, 14). The three major parts of an e-health strategy are policies, equipment and processes, and knowledge management. (15).
Review:
A. History of eHealth
In the past, medical professionals kept paper records detailing the medical history and current condition of their patients. However, the development of electronic tracking systems has been driven by the rise in health care costs and technical improvement. Therefore, the term "digital health," also known as "eHealth," came into being to refer to the application of information and communication technologies (ICT) in the healthcare industry. The field of eHealth is a developing area at the intersection of public health, business, and medical informatics, and it describes the health services and information that are enhanced or distributed via the internet and related technologies.
B. Application
C. Advantages
D. Its drawbacks are
IV. GENOMICS
The study of genes and how they affect heredity is known as genetics. Examples of single-gene illnesses that fall under the category of "Genetics" are PKU (phenyl ketonuria) and cysticercosis. (17) Because complex diseases like cancer, diabetes, asthma, and heart disease are more often caused by a combination of hereditary and environmental factors, scientists studying genomics research these conditions. (18) Gaining knowledge of the connections between these variables at the population level may open up fresh possibilities for intervention and prevention.(19).
2. Why is genetics and genomics important to our health?
Health and illness are influenced by both genomes and genetics. Understanding why some people become ill from specific illnesses, environmental variables, and behaviors while others do not is made easier with the use of genomics. The secret to these variations lies in genomics. (20) Humans share 99.9% of their genetic makeup with each other. Variations in the remaining 0.1% provide crucial hints on the origins of illnesses. Our ability to prevent and improve health is being enhanced by our growing understanding of the ways that genes and the environment interact.
3. Why Is Genetic And Genomic Important To Our Family's Health
For illnesses that have a genetic or genomic origin, family history is a valuable tailored tool that captures many of the gene/environment interactions. (22) The foundation for understanding genetic and genomic circumstances in family and individual disease prevention can be found in the family history. (23)
4. Impact Of Gene Regulation On Health And Disease
Their particular area of study is how regulation has evolved over the course of millions of years of human evolution. In order to achieve this, they fused two techniques from genome research: population genetics and the search for single nucleotide polymorphisms (SNPS), which can indicate the proper expression of genes. Using this approach, researchers can find genetic variants that can lead to human disease in addition to studying gene regulation (24). Sections of the genetic molecule DNA called genes are what carry the instructions for making proteins, which are the fundamental units and molecular machinery of life (25). 3,2 billion nucleotides are found in one molecule of DNA. However, the nucleotide sequence varies from person to person in the human race. Adenine (A) nucleotides, for instance, can be found in one person but cytosine (C) nucleotides can be found in another at the same location (26). It is estimated by researchers that there are eleven million single nucleotide variations, or SNPs, in the human genome. Finding these SNPs and learning more about how they affect health and illness is their goal. Mutation is the key to human variety (27). Lastly, if a mutation disrupts a vital bodily function, it may directly cause illness (28).
5. Genetics, Genomics and Patient Management
In addition to praising the value of genomics, the 2002 World Health Organization study on genomics and global health also raised concerns about a potential "genomic divide," which would make it more difficult for developing nations to benefit from genomic research and exacerbate existing disparities in health around the world. (29). By linking genotypes to phenotypes, detecting predisposing genetic variation (disease susceptibility) early, improving diagnostic techniques, improving disease prevention and treatment, and avoiding drug side effects, personalized medicine has the potential to revolutionize the health care industry. (30)
V. IMAGING IN HEALTHCARE
The term "medical imaging" describes the methods and procedures used to produce images of the human body (or portions of it) for a range of clinical applications, including diagnosis and treatment, as well as medical scientific applications including the examination of normal anatomy and function. It falls under the larger category of biological imaging, which also includes microscopy, radiography, endoscopy, thermography, and medical photography.
While not intended to create images per se, measurement and recording methods like magnetoencephalography (MEG) and electroencephalography (EEG) might be considered medical imaging since they generate data that can be displayed as maps.
Within the clinical setting, radiology or "clinical imaging" is typically used interchangeably with medical imaging. The application and interpretation of medical imaging research is often.
The preservation of radiography and the medical subdiscipline pertinent to the illness or field of study in medicine (psychiatry, neuroscience, cardiology, psychology, etc.). Numerous methods created for medical imaging have further uses in science and business. Before computed tomography (CT) for X-ray imaging, which led to computer-aided tomography (CAT), and isotope emission tomography, which led to PET and single Positron Emission Computed Tomography (SPECT) scans, there was little significance in biomedical work. After that, magnetic resonance imaging (MRI) dominated the other modalities in many ways as the most informative medical imaging methodology (31).
A number of methods have been developed to allow 3D images to be produced for doctors to use with CT, MRI, and ultrasound scanning software. In the past, CT and MRI scans gave 2D static output on film. Several scans were then done to construct a 3D model, which a doctor could edit, to make 3D images.
Overview:
Biological imaging, which has been around since the 19th century, includes medical imaging. Here is a quick rundown of medical imaging. Although more intriguing, MRIs, ultrasounds, and X-rays continued to rule the 21st century.
Both macroscopic and microscopic biological structures are being studied using tools, particularly imaging (thermal imaging, electrical impedance tomography, scanning probe techniques etc).
In the future, getting functional and metabolic data in addition to structural (image) data will be more important. To some extent, magnetic resonance spectroscopy (32) and radioactive tracers (such PET) can be used for this.
VI. TECHNIQUES AND APPLICATIONS
The development of image, visualization, and graphics workstation technologies has sparked a variety of new medical imaging procedures and methods. The use of wavelet transformations in medical imaging, image segmentation, and virtual medical imaging subsystems are among the most crucial ones.
Medical image creation and capture techniques:
A. Wavelet Transform Technology Application
The wavelet transform has multi-resolution and multi-scale properties. All that occurs in scaling is "stretching" and "compressing." We confine ourselves to utilize discrete wavelet transform (DWT) and binary scaling (33).
B. Segmentation of medical images (using LEGION method)
Segmenting binary and grey-level images has shown to be a successful use of LEGION, a computational paradigm for image analysis that Terman and Wang (41, 42) described as biologically plausible.⇒Medical image repository and image categorization:
Data Access Layer (DAL)-based generic storage component is referred to as a "Medical Image Repository" (43).
COTS product is defined by the evaluation process for COTS software products as
Explains additional requirements that are generally included in any COTS-like component in addition to the ones that were previously mentioned. Among these requirements are:
Interoperability: It defines Information Objects, which are abstractions of
real information entities such as CT Image, MR Image etc.
Diversity in requirements: A generic medical image repository must
satisfy the following criteria:
Support for multiple modalities.
Different information models.
Versatility
Usability
Effectiveness
Dependability
Portability
2. In the online CISMeF health catalogue, the content-based automatic medical envision classification techniques are highlighted in ref. (44). The recommended feature representation/transformation technique is similar to Vector Quantification (VQ), in which the prototype blocks' indexes are used to label pixel blocks (44).
3. Web-based interactive applications of high-resolution 3D medical image data:
The amount of medical image data that needs to be shared on the Internet for computerized visualization and analysis is steadily increasing. These data sizes, which can range from several hundred megabytes to several dozen gigabytes (45), put a significant strain on networks and storage systems and provide numerous difficulties for developers of Web-based interactive applications. Web-based interactive applications are restricted to low- or medium-resolution image data due to limitations in Internet speed, which are frequently insufficient for dependable use in clinical diagnostics.
A software package (standalone system) called MACOSTAT has been created by Gustafson et al. for the building and browsing of 3D brain atlases (46).
◊ Data storage structure:
VII. M-HEALTH
A. Patient Follow-Up And Medication Adherence
Among the review's findings (n = 19), actions to enhance patient lifestyle and medication adherence, as well as therapy follow-up, were the most prevalent. Six studies reported on the outcomes of pilot projects aimed at informing birth outcomes (48), reporting side effects from medications, monitoring TB patients (49), observing behavioral changes in diabetic patients (50), and identifying pregnant women in need of antenatal care and referral services (51). RCT studies were also frequently conducted on this subject (n =8), with findings on patient adherence, ART monitoring, and competent de-livery attendance reported (52, 53). These projects made use of phone calls, SMS, and multimedia communications (MMS).
Additional discoveries comprised two mixed-methods studies, one for supporting patients with breast cancer during their oncological treatment (55), and an additional to monitor adherence to treatment and care provided by caregivers of HIV-infected children. The cross-sectional study examined the feasibility of using mobile phones to remind patients regarding their medications and appointments in an anti- Retroviral treatment (ART) health facility.
The review investigated the effectiveness of SMS on patient adherence to ART.
B. Advantages
C. Disadvantages
Data Privacy: The health applications constantly gather and examine the user's medical information. The risk that a hacker will reveal personal information and share it with unaffiliated parties is a serious worry.
VIII. HEALTH PROMOTION STRATEGY
A. Methods Search strategy
Three excellent practices served as the basis for the review: the Center for Reviews and Dissemination's 1996 Undertaking Systematic Reviews of Research on Effectiveness, the EPI-Center's 1996 Review Guidelines on Data Collection. The study dealt with older adults either fully or partially. The goal of the intervention was to either completely or partially prevent or lessen social isolation and/or loneliness. The study detailed treatments that promoted health and gave older adults more control over their health. The research collected data on outcome measures in Trevan, either in conjunction with or apart from process measures.
B. Introduction studies
"The process that enables people to increase control over their health and improve their overall health" is what the Ottawa Charter defines as health promotion. This can be accomplished through promoting change at the individual, family, and community levels as well as through education and skill development. Well-being is included in the duty for health promotion, which goes beyond the health sector. Rather of concentrating just on those who are most vulnerable to certain diseases, health promotion initiatives aim to prevent illness and promote overall well-being.
C. Strategies for health promotion
Developing strategies for health promotion requires careful consideration of three important factors: ecology, holism, and caring. Men and women must therefore emerge as equal partners in every stage of planning, carrying out, and evaluating health promotion initiatives. This is a fundamental principle that everybody involved must follow. The strategies listed below can be used to promote health:
Health-related communication
Health instruction
Policy formulation
Systems evolve
Changes in the environment
D. Advantages
The nation, states, families, communities, and individuals all benefit from improved health due to health promotion. -Health promotion makes everyone's quality of life better. -Healthy living promotes fewer preventable deaths
E. Disadvantages
Social media marketing's shortcomings include its time, resource, and personnel requirements; cause marketing, on the other hand, has advantages for both businesses and nonprofits.
IX. PERSONALIZED MEDICINE & PATIENT’S ENGAGEMENT
The use of novel, high-throughput, data-intensive biomedical assays, like proteomics, DNA sequencing, imaging protocols, and wireless monitoring devices, has uncovered a great deal of inter-individual variation in the mechanisms and contributing factors to disease processes as well as the effects of those processes.
A number of excellent reviews on personalized medicine have been written, including a growing number of textbooks on the subject meant for medical students and clinicians. It should be noted that although many use the term ‘personalized’ medicine interchangeably with the terms ‘individualized’ and ‘precision’ medicine (as we do here), many have argued that there are some important, though often subtle, distinctions between them. (59, 60)
Personalized medications come with a lot of difficulties, particularly when it comes to getting regulatory organizations to approve them for regular usage. Furthermore, there exist numerous concerns linked to the widespread adoption of customized medications by various healthcare stakeholders, including physicians, executives in the field, insurance providers, and patients themselves. The proof that personalized medicine strategies simply work better than traditional medicine strategies is at the center of almost all these challenges. This is because many tailored or personalized therapies, like autologous CAR-T cell transplant therapies for specific cancer types (61) and mutation-specific medications like ivacaftor to treat cystic fibrosis (62,63), can be highly expensive (64).
A. Patient’s Engagement
Through patient engagement, treatment plans can take into account the opinions and preferences of the patients, making them more responsive and tailored.
By encouraging active participation, patient engagement can result in better adherence to treatment plans, better outcome, and fewer adverse events.
Active patient involvement can build trust, improve the patient-provider relationship, and raise patient satisfaction. Patient participation helps to ensure the long-term viability of global health systems by encouraging informed treatment decisions and effective resource utilization.
Patient participation promotes wise choices regarding treatment and efficient use of available resources, which contributes to the sustainable development of international health systems.
Patient participation is essential in the ever changing healthcare environment of today. Treatment quality is enhanced by active patient participation, particularly when it comes to chronic illnesses. Acknowledging its influence on health-related behaviors and results, the medical community is searching for innovative approaches to involve people.
In order to guarantee that patients are informed about their treatment, recuperation, medication choices, and other significant parts of their medical care, patient engagement refers to the active participation and collaboration between healthcare providers and patients (65,66). It is becoming more widely acknowledged as a vital component of safe, person-centered services and as an essential part of health care.
B. Health & Medical Platforms
Online healthcare consultation has become an essential part of healthcare system. Online medical platforms provide patients with a channel that allows them to make an appointment, learn about a physician, understand their severity of illness, and ask for advice on the Internet without having to leave home (67,68).
Researchers concentrate on various forms of data within the virtual health community to examine the ways in which variables influence patients' consultation practices. Physician information includes self-reported data, their internet persona, and more. Furthermore, the online medical community co-created the customer value.
A portion of the problems facing the physician-patient interaction in China today can be attributed to the asymmetry of knowledge between the two parties (69, 70). A doctor's personal webpage can serve as a resource for patients to learn about illnesses and doctors, enabling them to select a doctor based on comprehensive information (71). This helps to mitigate information asymmetry and influences patients' consultative behavior (72). System-generated and patient-generated information for physician homepages have been separated in the literature. For instance, contribution values, etc., are considered system-produced information, but thank-you messages are data generated following a patient consultation and are categorized as patient-provided information. (73)
[1] Telemedicine in India: Where do we stand? Chellaiyan VG, Nirupama AY, Taneja N. J Family Med Prim Care. 2019;8:1872–1876. [2] Utilization of telemedicine in rhinology practice during COVID-19 pandemic. Alshareef M, Alsaleh S, Albarn H, et al. Am J Otolaryngology. 2021; 42:102929. [3] Telemedicine and health policy: a systematic review. Kruse CS, Williams K, Bohls J, Shamsi W. Health Policy Technol. 2021;10:209–229. [4] Telemedicine in India: a tool for transforming health care in the era of COVID-19 pandemic. Agarwal N, Jain P, Pathak R, Gupta R. J Educ Health Promot. 2020; 9:190. [5] Warshaw EM, Hillman YJ, Greer NL, Hagel EM, MacDonald R, Rutks IR, et al. Teledermatology for diagnosis and management of skin conditions: A systematic review. J Am Acad Dermatol. 2011; 64:759–72 [6] Dhingra D., Dabas A. Global strategy on digital health. Indian Pediatric. 2020; 27:356–358. Doi: 10.1007/s13312-020-1789-7. [PubMed] [Cross Ref] [Google Scholar] [7] Negash S., Musa P., Vogel D., Sahay S. Healthcare information technology for development: Improvements in people’s lives through innovations in the uses of technologies. Inf. Technol. Dev. 2018; 24:189–197. Doi: 10.1080/02681102.2018.1422477. [Cross Ref] [Google Scholar] [8] Ross J., Stevenson F., Lau R., Murray E. Factors that influence the implementation of e-health: A systematic review of systematic reviews (an update) Implement at. Sci. 2016; 11:146. Doi: 10.1186/s13012-016-0510-7. [PMC free article] [PubMed] [Cross Ref] [Google Scholar] [9] Mauco K.L., Scott R.E., Mars M. Validation of an e-health readiness assessment framework for developing countries. BMC Health Serv. Res. 2020; 20:575. Doi: 10.1186/s12913-020-05448-3. [PMC free article] [PubMed] [Cross Ref] [Google Scholar] [10] Van Houwelingen C., Moerman A., Ettema R., Kort H., Cate O.T. Competencies required for nursing telehealth activities: A Delphi-study. Nurse Educ. Today. 2016; 39:50–62. Doi: 10.1016/j.nedt.2015.12.025. [PubMed] [Cross Ref] [Google Scholar] [11] Wolff-Piggott B., Coleman J., Rivett U. The clinic-level perspective on mHealth implementation: A South African case [12] ?wiklicki M., Schiavone F., Klich J., Pilch K. Antecedents of use of e-health services in Central Eastern Europe: A qualitative comparative analysis. BMC Health Serv. Res. 2020; 20:171. Doi: 10.1186/s12913-020-5034-9. [PMC free article] [PubMed] [Cross Ref] [Google Scholar] [13] D’Agostino M. Electronic health strategies in The Americas: Current situation and perspectives. Rev. Peru. Med. Exp. Salud Publication. 2015; 32:352–355. Doi: 10.17843/rpmesp.2015.322.1631. [PubMed] [Cross Ref] [Google Scholar] [14] Kho J., Gillespie N., Martin-Khan M. A systematic scoping review of change [15] Pan American Health Organization—PAHO. World Health Organization—WHO What Is eHealth? [(accessed on 1 April 2020)] [16] Whitehead L., Seaton P. The effectiveness of self-management mobile phone and tablet apps in long-term condition management: A systematic review. J. Med. Internet Res. 2016; 18: e4883. doi:10.2196/jmir.4883. [17] Gerard S, Hayes M and Rothstein MA. On the edge of tomorrow: Fitting genomics into public health policy. J. Law Med.Ethics 2002 Fall;30: 173-6 [18] Guttmacher AE and Collins FS.15Shawky and Nour El Din Genomic medicine--a primer. N. Engl. J. Med. 20027;347(19):1512-20 [19] Shelton AK, Fish AF, Cobb JP, Bach-man JA, Jenkins RL, Battistich V, et al. Surrogate consent for genomics research in intensive care. Am. J. Crit. Care 2009 18(5):418,426; quiz427. [20] Khoury MJ. Genetic epidemiology and the future of disease prevention and public health. Epidemiol.Rev. 1997;19(1):175-80. [21] Khoury MJ, Little J, Burke W. Human genome epidemiology: A scientific foundation for using genetic information to improve health and prevent dis-ease. 1st ed. USA: Oxford University Press; 2003 [22] Reilly PR. Is it in your genes? The intense of genes on common disorders and diseases that affect you and your family. 1st ed.: Cold Spring Harbor Laboratory Press; 2004. [23] Willard H, Chandrasekharan S. Genomics: Making a world of difference: Global Health at Duke; 2007. [24] Chen K, Rajewsky N. Finding genomic elements involved in human disease with a new approach. Berlin-Buch E M B A R G O E D: Max-Delbrück-Centrum für Molekulare Medizing (MDC);2006. [25] Lippman A. Led (astray) by genetic genetic map: the cartography of the human genome and healthcare’s sci Med 2007:36:1469-80. [26] .Myerowitz R. mutations and neutral polymorphisms. Hum Mutate. 2009, 10:120-208. [27] Genetics, genomics and patient management. 2009; Available: http://www.genome.gov/27527600. [28] Burke W, Khoury MJ, Stewart A and Zimmern RL. The path from genome-based research to population health:Development of an international public health genomics network. Genet.Med. 2006;8(7):451-8. [29] Webb, S.: The Physics of Medical Imaging Medical Science Series, New York (1988) [30] Zaidi, H.: Medical Imaging: Current Status and Future Perspective, Division of Nuclear Medicine, Geneva University Hospital [31] Tian, D.-Z., Ha, M.-H.: Applications of Wavelet Transform in Medical Image Processing, Faculty of Mathematics and Computer Science, Hebei university, Baoding 071002 [32] Bradie, B.: Wavelet packet-based compression of signal lead ECG J. IEEE Trans. BME 43(1),49–60 (1994) [33] Kaimei, Z., Shengchen, y.: Semi-lossless compression algorithm of ECG signal based onwavelet transform. Shandong Joumal of Biomedical Engineering 22(2), 8–10 (2003) [34] Kalayci, T., Ozadmar, 0.: Wavelet processing for automated neural network detection of EEGspikes Jl. IEEE Eng. in Med. and Biol. 2, 160–166 (1995) [35] Weidong, Z., Yingyuan, L.: EEG spikes detection and denoising methods based on wavelet transform. Chinese Journal of Medical Physics 18(4), 208–210 (2001) [36] Meyer, E.G., Averbuch, A.Z., Stmmberg, J.O.: Fast adptive wavelet packet image compression. IEEE Trans. On Image processing 9(5), 792–800 (2000) [37] Xiong, Z., Ramchandran, K., Orchard, M.T.: Waveletpacket image coding using space-frequency quantization. IEEE Trans. On Image processing 7(6), 892–898 (1998) [38] Tolba, A.S.: Wavelet packet compression of Medical images. Digital Signal Processing 12, 441–470 (2002) [39] Terman, D., Wang, D.L.: Global competition and local cooperation in a network of neuraloscillators. Physics D 81, 148–176 (1995) [40] Wang, D.L., Terman, D.: Locally excitatory globally inhibitory oscillator networks. IEEETrans. Neural Networks 6, 283–286 (1995) [41] Wang, D.L., Terman, D.: Image segmentation based on oscillatory correlation. Neural Comput. 9, 805–836 (1997) (for errata see Neural Comput. 9, 1623–1626 (1997) [42] Chandrashekar, N., Gautam, S.M., Shivakumar, K.R., Srinivas, K.S., Vijayananda, J.: COTS-Like Generic Medical Image Repository [43] Florea, E., Barbu, E., Rogozan, A., Bensrhair, A.: VBuzuloiu LITIS Laboratory, INSA deRouen 1060 Av. de l’Universite. St. Etienne du Rouvray, France LAPI Laboratory PolitehnicaUniversity Bucharest 1-3 Iuliu Maniu Blvd, Bucharest, Romania, Medical image catagorization using a texture based symbolic description [44] Udupa, J.K., Herman, G.T.: 3D Imaging in Medicine. CRC Press, Boca Raton (1999); Proceedings of the 19th IEEE Symposium on Computer-Based Medical Systems (CBMS 2006) 0-7695-2517-1/06 $20.00 © 2006 IEEE [45] Gustafson, C., Tretiak, O., Bertrand, L., Nissanov, J.: Design and implementation of software for assembly and browsing of 3D brain atlases. Computer Methods and Programs in Biomedicine 74(1), 53–61 (2004) [46] Aguirre, A., Cabrera, S.D., Lucero, A., Vidal Jr., E., Gerdau, K.: Compression of Three-Dimensional Medical Image Data based on JPEG 2000. In: Proceedings of the 17th IEEE Symposium on Computer-Based Medical Systems, pp. 116–121 (2004) [47] Andreatta P, Debpuur D, Danquah A, Perosky J: Using cell phones to collect postpartum hemorrhage outcome data in rural Ghana. Int J Gynaecol Obstet 2011, 113(2):148–151. [48] Adedeji AA, Sanusi B, Tella A, Akinsanya M, Ojo O, Akinwunmi MO, Tikare OA, Ogunwande IA, Ogundahunsi OA, Ayilara OO: Exposure to anti-malarial drugs and monitoring of adverse drug reactions using toll-free mobile phone calls in private retail sector in Sagamu, Nigeria: implications for pharmacovigilance. Malar J 2011, 10:230. [49] Wakadha H, Chandir S, Were EV, Rubin A, Obor D, Levine OS, Gibson DG, Odhiambo F, Laserson KF, Feikin DR: The feasibility of using mobile-phone based SMS reminders and conditional cash transfers to improve timely immunization in rural Kenya. Vaccine 2013, 31(6):987–993. [50] Hoffman JA, Cunningham JR, Suleh AJ, Sundsmo A, Dekker D, Vago F, Munly K, Igonya EK, Hunt-Glassman J: Mobile direct observation treatment for tuberculosis patients: a technical feasibility pilot using mobile phones in Nairobi, Kenya. Am J Prev Med 2010, 39(1):78–80. [51] Mbuagbaw L, Thabane L, Ongolo-Zogo P, Lester RT, Mills EJ, Smieja M, Dolovich L, Kouanfack C: The Cameroon Mobile Phone SMS (CAMPS) trial: a randomized trial of text messaging versus usual care for adherence to antiretroviral therapy. PLoS One 2012, 7(12):e46909. [52] Pop-Eleches C, Thirumurthy H, Habyarimana JP, Zivin JG, Goldstein MP, de Walque D, MacKeen L, Haberer J, Kimaiyo S, Sidle J: Mobile phone technologies improve adherence to antiretroviral treatment in a resource-limited setting: a randomized controlled trial of text message reminders. AIDS 2011, 25(6):825–834[only 20 and 21 are taken] [53] Horvath T, Azman H, Kennedy GE, Rutherford GW: Mobile phone text messaging for promoting adherence to antiretroviral therapy in patients with HIV infection. Cochrane Database Syst Rev 2012, 3:CD009756 [54] Odigie VI, Yusufu LM, Dawotola DA, Ejagwulu F, Abur P, Mai A, Ukwenya Y, Garba ES, Rotibi BB, Odigie EC: The mobile phone as a tool in improving cancer care in Nigeria. Psychooncology 2012, 21(3):332–335 [55] White, H., McConnell, E., Clip, E., Branch, L. G., Sloane, R., Pieper, C. and Box, T. L.2002. A randomized controlled trial of the psychosocial impact of providing Internet training and access to older adults. Aging and Mental Health, 6, 3, 213–21. [56] Mullins, L. C. and McNicholas, N. 1986. Loneliness among the elderly: issues and con- siderations for professionals in aging. Gerontology and Geriatrics Education, 7, 1, 55–65.Nutbeam, D. 1998. Comprehensive strategies for health promotion for older people: past lessons and future opportunities. Australian Journal on Ageing, 7, 3, 120–7. [57] Burbank, P. M. 1986. Psychosocial theories of aging: a critical evaluation. Advances inNursing Science, 9, 1, 73–86 [58] CDC. 2016 Available from: https://blogs.cdc.gov/genomics/2016/04/21/shift/ [59] NIH. 2018 Available from:https://ghr.nlm.nih.gov/primer/precisionmedicine/precisionvspersonalized. [60] Shah GL, Majhail N, Khera N, Giralt S. Value-Based Care in Hematopoietic Cell Transplantation and Cellular Therapy: Challenges and Opportunities. Curr Hematol Malig Rep. 2018 doi: 10.1007/s11899-018-0444-z. [PMC free article] [PubMed] [CrossRef] [Google Scholar] [61] Davis PB, Yasothan U, Kirkpatrick P. Ivacaftor. Nat Rev Drug Discov. 2012;11(5):349–50. doi: 10.1038/nrd3723. [PubMed] [CrossRef] [Google Scholar] [62] Gulland A. Cystic fibrosis drug is not cost effective, says NICE. BMJ. 2016;353:i3409. doi: 10.1136/bmj.i3409. [63] Check Hayden E. Promising gene therapies pose million-dollar conundrum. Nature. 2016;534(7607):305–6. doi: 10.1038/534305a. [64] Barello S, Graffigna G, Vegni E. Patient engagement as an emerging challenge for healthcare services: mapping the literature. Nursing research and practice. 2012; Oct 31: 2012 [65] Krist, A. H., Tong, S. T., Aycock, R. A., and Longo, D. R. Engaging patients in decision-making and behavior change to promote prevention. Information Services & Use. 2017; 37(2): 105-122 [66] Ouyang P., Wang J.-J., Chang A.-C.J. Patients need emotional support: Managing physician disclosure information to attract more patients. Int. J. Med. Inform. 2022;158:104674. doi: 10.1016/j.ijmedinf.2021.104674. [PubMed] [CrossRef] [Google Scholar] [67] Ouyang P., Wang J.-J. Physician’s online image and patient’s choice in the online health community. Internet Res. 2022 doi: 10.1108/INTR-04-2021-0251. [68] Guo S., Guo X., Fang Y., Vogel D. How doctors gain social and economic returns in online health-care communities: A professional capital perspective. J. Manag. Inf. Syst. 2017;34:487–519. doi: 10.1080/07421222.2017.1334480. [CrossRef] [Google Scholar] [69] Wang J.Y., Probst J.C., Stoskopf C.H., Sanders J.M., McTigue J.F. Information asymmetry and performance tilting in hospitals: A national empirical study. Health Econ. 2011;20:1487–1506. doi: 10.1002/hec.1689. [70] Huang Z., Duan C., Yang Y. Online Selection of a Physician by Patients: The Impression Formation Perspective. Medicine. 2022 doi: 10.21203/rs.3.rs-1394279/v1 [71] Rider T., Malik M., Chevassut T. Haematology patients and the internet–The use of on-line health information and the impact on the patient–doctor relationship. Patient Educ. Couns. 2014;97:223–238 doi: 10.1016/j.pec.2014.06.018. [72] Yang H., Guo X., Wu T., Ju X. Exploring the effects of patient-generated and system-generated information on patients’ online search, evaluation and decision. Electron. Commer. Res. Appl. 2015;14:192–203.doi: 10.1016/j.elerap.2015.04.001
Copyright © 2024 Dr. Kirteebala Pawar, Sharvari Gujarathi , Ritik Gupta, Aasim Khan, Amit Tiwari. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Paper Id : IJRASET58371
Publish Date : 2024-02-09
ISSN : 2321-9653
Publisher Name : IJRASET
DOI Link : Click Here