New Era In Healthcare Research Articles

Personalized Medicine: The Dawn of a New Era in Healthcare

The landscape of healthcare is transforming with the advent of personalized medicine, an approach that alters medical treatment to each individual's specific characteristics. This paradigm shift is driven by advancements in genomics, molecular biology, and bioinformatics, which have developed a deeper understanding of the genetic and molecular basis of diseases. This new healthcare model is based on precision and individualization, aiming to provide customized healthcare with medical decisions and treatments by considering variability in genes, environment and lifestyle of an individual patient and offer accurate diagnosis, better treatments and prevention plans. The accomplishment of the Human Genome Project in 2003 was a significant advancement in genomics that provided blueprints of the human genome [1]. Rapid progress in genomic sequencing technologies makes it feasible and cost effective. Advanced sequencing techniques including next-generation sequencing allow a detailed analysis of genetic makeup to locate mutations and genetic predispositions for better treatment decisions. Cancer is caused by genetic heterogeneity and has benefited greatly from genomic insights. Molecular profiling of tumor cells allows the identification of specific genetic mutations involved in cancer pathogenesis. Targeted therapies can then be designed to inhibit these specific molecular pathways, leading to more effective and less toxic treatments compared to traditional chemotherapy. For example, in breast cancer the identification of Human epidermal growth factor receptor 2 (HER2) mutations has led to the development of HER2-targeted therapies to improve treatment [2]. Besides oncology, personalized medicine is making progress in other fields. In cardiology, genetic testing allows identification of patients who are at risk of getting inherited cardiovascular diseases. In pharmacology, pharmacogenomics, the study of correlation between genes and immune response of an individual to drugs helps in designing most effective drugs with the least side effects for each patient. In infectious diseases, genomic sequencing of pathogenic microbes can lead to development of appropriate antimicrobial drugs to prevent outbreaks. Despite its progress, the implementation of personalized medicine is facing several challenges. The utilization of genomic data in clinical workflows demands significant changes to healthcare setting and training with concerns about data privacy, equal access to diverse populations and the ethical implications of genetic information. Currently, the universal unavailability of sophisticated bioinformatics tools to interpret complex genomic data is also a challenge. Researchers and policymakers must work in to set guidelines and standards for safe use of personalized medicine. Therefore, personalized medicine is a promising tool, which has revolutionized diagnosis, treatment, and prevention in traditional medicine. Using genomics and molecular biology, we can develop a more precise, predictive, and personalized approach to medicine. This exciting frontier must be navigated with the ultimate goal of improving patient outcomes.

AI and Cloud Computing in Healthcare: Transforming Patient Care with AWS and Java

A new era in healthcare is being ushered in by the convergence of artificial intelligence (AI) and cloud computing, which will significantly improve patient care through improved diagnosis, individualized treatment planning, and effective patient management. This article explores the potent combination of Java and Amazon Web Services (AWS) and how these technologies may be used to develop cutting-edge AI-driven healthcare solutions that optimize healthcare operations and dramatically enhance patient outcomes. Together with Java's robust and flexible programming environment, healthcare providers can leverage AWS's scalable infrastructure and advanced machine learning capabilities to create and implement sophisticated AI models that analyze massive amounts of medical data at a speed and accuracy never seen before. These developments are making it possible to make more accurate diagnoses, customized treatment plans, and proactive patient monitoring, which can result in better clinical judgment and possibly life-saving measures. But even as we consider the enormous positive effects these technologies have on society, we also have to face the ethical problems they raise, such as issues with data privacy, potential biases in algorithms, and unequal access to cutting-edge medical treatments.

AI and Cloud Computing in Healthcare: Transforming Patient Care with AWS and Java

A new era in healthcare is being ushered in by the convergence of artificial intelligence (AI) and cloud computing, which will significantly improve patient care through improved diagnosis, individualized treatment planning, and effective patient management. This article explores the potent combination of Java and Amazon Web Services (AWS) and how these technologies may be used to develop cutting-edge AI-driven healthcare solutions that optimize healthcare operations and dramatically enhance patient outcomes. Together with Java's robust and flexible programming environment, healthcare providers can leverage AWS's scalable infrastructure and advanced machine learning capabilities to create and implement sophisticated AI models that analyze massive amounts of medical data at a speed and accuracy never seen before. These developments are making it possible to make more accurate diagnoses, customized treatment plans, and proactive patient monitoring, which can result in better clinical judgment and possibly life-saving measures. But even as we consider the enormous positive effects these technologies have on society, we also have to face the ethical problems they raise, such as issues with data privacy, potential biases in algorithms, and unequal access to cutting-edge medical treatments. The goal of this thorough investigation is to present a fair assessment of the revolutionary potential of artificial intelligence (AI) and cloud computing in the healthcare industry, while also discussing the wider ramifications and obligations associated with incorporating these formidable technologies into our healthcare systems.

SUBMIP: Smart Human Body Health Prediction Application System Based on Medical Image Processing

This paper focuses on the improvement of a cloud-based application that predicts the health conditions of the patient daily. patients can check their health status and records are generated and saved in the cloud and can access them by using mobile and web applications. A new era in healthcare has begun with the introduction of technology, promising creative approaches to tracking and forecasting health conditions and status. This study introduces and investigates the “Smart Human Body Health Prediction Application System,” a vast digital platform that combines wearable sensors, and artificial intelligence, to provide real-time health insights and predictive analysis so that the patient can easily know their health and can consult the doctors. The Smart Human Body Health Prediction Application System, which combines wearable sensors, using ML algorithm to train the data sets, and predictive analytics, is explored in detail in this paper. We talk about how these elements work together to give users a proactive and unique approach to the health care field.

Integrating multisensory information fusion and interaction technologies in smart healthcare systems

<p>The advent of intelligent medical systems has heralded a new era in healthcare, promising enhanced diagnostic accuracy, treatment efficacy, and personalized patient care. Central to these advancements is the application of multisensory information fusion and interaction technology, which integrates diverse data types—from imaging to auditory signals and electronic health records—to facilitate comprehensive patient assessments. This study examines the efficacy of such multisensory integration within an intelligent medical system framework, focusing on its impact on diagnostic accuracy and treatment effectiveness. A hypothetical dataset encompassing various sensory inputs for a cohort of patients was analyzed, revealing a significant improvement in diagnostic precision (average accuracy of 92.3%) and treatment outcomes, with a majority of interventions rated as highly effective. These findings underscore the potential of multisensory data fusion in revolutionizing medical diagnostics and treatment planning. Despite the promising results, limitations such as sample size and data quality were acknowledged, pointing towards the necessity for further research. This study not only corroborates the value of multisensory information fusion in enhancing healthcare delivery but also highlights the pathway for future advancements in intelligent medical systems. The article’s novelty lies in its approach to integrating multisensory data with AI technologies, leading to a more nuanced understanding of patient health. This method transcends traditional diagnostic techniques, allowing for a multifaceted analysis of medical conditions. It emphasizes the potential of this technology to detect diseases earlier and more accurately, tailor treatments to individual patient needs, and improve overall healthcare efficiency.</p>

Tailoring Tomorrow's Healthcare for Young Lives: Precision Medicine in Pediatrics and Advanced Neonatal Care

Precision medicine has emerged as a groundbreaking approach to healthcare, tailoring medical treatment to the individual characteristics of each patient. While its applications have been widely discussed in the context of adult medicine, its role in pediatrics and advanced neonatal care is equally promising. It is ushering in a new era in healthcare, with particular promise in the fields of pediatrics and advanced neonatal care. This article explores the transformative potential of precision medicine in optimizing treatment strategies for pediatric patients and infants in neonatal intensive care units (NICUs). By focusing on genetic, environmental, and lifestyle factors, precision medicine offers targeted therapies, early interventions, and improved outcomes. This paper reviews recent advancements, ethical considerations, and challenges associated with implementing precision medicine in pediatric and neonatal healthcare. The integration of genomic data, advanced diagnostic tools, and personalized treatment plans exemplifies the future of healthcare, promising enhanced quality of life for young patients. This article explores the current landscape of precision medicine in pediatrics, with a specific focus on neonatal care, highlighting its potential benefits, challenges, and prospects.

Revolutionizing Healthcare: Disease Prediction Through Machine Learning Algorithms

A crucial field of medical research is disease prediction, which has the potential to improve early diagnosis and therapy that can have a major impact on the course of treatment. By dramatically raising the standard of patient care and the effectiveness of the healthcare system as a whole, disease prediction plays a critical role in contemporary healthcare. Early detection of illnesses or medical issues, even before symptoms appear, is a key component of this proactive approach to healthcare management. This enables prompt interventions, better treatment outcomes, and better resource allocation. In this study, we use four different machine learning techniques to predict diseases using large datasets. Our main goal is to evaluate the effectiveness of different algorithms and determine which one performs best at accurately predicting the condition. To guarantee data quality and significance, the study makes considerable use of feature selection, engineering, and data preparation. Across various illness datasets, four machine learning algorithms, K-Nearest Neighbors, XG Boost, Ada Boost with SVM and Logistic Regression, are thoroughly examined. Accuracy, precision, recall, F1-score, and receiver operating characteristic area under the curve (AUC-ROC) are just a few of the performance criteria used to rate these algorithms. The comparative study not only identifies the algorithm with the best predicted accuracy, but it also offers insightful information about the benefits and drawbacks of each strategy. This study has significant healthcare impacts. We provide medical professionals with an effective tool for early detection and intervention by determining the algorithm that performs best at disease prediction. Improved disease prediction accuracy can result in earlier and more efficient treatment, which may save lives and lower healthcare costs. Additionally, this research opens the door for the application of sophisticated machine learning methods to clinical practice, ushering in a new era in healthcare where data-driven predictions support clinical judgment. In conclusion, by utilizing the potential of machine learning algorithms for more precise and timely disease prediction, our research supports the continual evolution of healthcare.

ChatGPT in Diabetes Care: An Overview of the Evolution and Potential of Generative Artificial Intelligence Model Like ChatGPT in Augmenting Clinical and Patient Outcomes in the Management of Diabetes

Abstract The rapid evolution of artificial intelligence (AI) technologies has brought a new era in health care, offering innovative solutions for various medical disciplines, including diabetes care. This viewpoint article aimed to elucidate the transformative potential of Chat Generative Pre-trained Transformer (ChatGPT), a large language model (LLM), in augmenting diabetes care. We traverse through the historical evolution of AI, delineating its trajectory from conceptual origins to contemporary advancements. Central to our discussion is the exploration of ChatGPT’s capabilities in fostering enhanced patient engagement, personalized medical guidance, and streamlined health-care workflows. Through a comprehensive review, we underscore ChatGPT as a pivotal technology, focused to revolutionize traditional paradigms in diabetes management and patient care.

Digital therapeutics-a new era in health care

Digital therapeutics are evidence-based therapeutic interventions that utilize digital technologies to prevent, manage, or treat medical disorders. These interventions utilize digital technologies like mobile apps or online platforms to deliver evidence-based therapeutic interventions and treatments for various health conditions. Digital therapeutics undergo rigorous clinical validation and regulatory processes to ensure their safety and efficacy. Digital therapeutics offer several benefits in health care, including improved accessibility, personalized treatment, cost-effectiveness, continuous monitoring and feedback, enhanced patient engagement, scalability, and support for various health conditions. They have practical applications in areas such as psychiatry, drug development, substance abuse treatment, chronic insomnia, Parkinson’s disease, cardiac rehabilitation, and oncology care. Digital therapeutics can significantly improve the quality of life for individuals across different populations by providing tailored interventions for mental health disorders and addressing health conditions related to different age groups. However, challenges to the widespread adoption of digital therapeutics include resistance to change within health-care systems, interoperability issues, privacy concerns, and limited reimbursement policies. Collaboration among health-care providers, regulators, technology developers, and patients is necessary to address these challenges and ensure the safety and effectiveness of digital therapeutics.

THE IMPACT OF AI IN HEALTH CARE: DIAGNOSIS AND PATIENT CARE

An exciting new era in healthcare has begin with the introduction of Artificial Intelligence (AI), which holds the promise of resolving some of the industry’s most serious problems. The present review delves into the various aspects of artificial intelligence’s impact on healthcare, primarily emphasising its function in patient care and diagnosis. This review explores the development of AI technologies, their use in medical diagnostics, and their significant influence on patient care procedures, drawing on a wide range of research papers. The study addresses the benefits, drawbacks, and potential applications of AI-driven healthcare technologies. In addition, it discusses the necessity of a cordial collaboration between AI and medical professionals as well as the ethical and legal ramifications of AI in healthcare

Digital health in older adults for the prevention and management of cardiovascular diseases and frailty. A clinical consensus statement from the ESC Council for Cardiology Practice/Taskforce on Geriatric Cardiology, the ESC Digital Health Committee and the ESC Working Group on e-Cardiology.

Digital health technology is receiving increasing attention in cardiology. The rise of accessibility of digital health tools including wearable technologies and smart phone applications used in medical practice has created a new era in healthcare. The coronavirus pandemic has provided a new impetus for changes in delivering medical assistance across the world. This Consensus document discusses the potential implementation of digital health technology in older adults, suggesting a practical approach to general cardiologists working in an ambulatory outpatient clinic, highlighting the potential benefit and challenges of digital health in older patients with, or at risk of, cardiovascular disease. Advancing age may lead to a progressive loss of independence, to frailty, and to increasing degrees of disability. In geriatric cardiology, digital health technology may serve as an additional tool both in cardiovascular prevention and treatment that may help by (i) supporting self-caring patients with cardiovascular disease to maintain their independence and improve the management of their cardiovascular disease and (ii) improving the prevention, detection, and management of frailty and supporting collaboration with caregivers. Digital health technology has the potential to be useful for every field of cardiology, but notably in an office-based setting with frequent contact with ambulatory older adults who may be pre-frail or frail but who are still able to live at home. Cardiologists and other healthcare professionals should increase their digital health skills and learn how best to apply and integrate new technologies into daily practice and how to engage older people and their caregivers in a tailored programme of care.

Novel Artificial Intelligence and Smart Emerging Medical Technology Revolutionize and Transform Nursing Profession in 2020

In 2020, novel artificial intelligent, immersive and connected technological advances have made their way into nursing care delivery settings globally as 2020 had been the year of rapid overwhelming changes. Novel artificial intelligence has the potential to transform healthcare to the forefront of a new era in healthcare driven by its ability to create an energetic improvement in the concept of patients' care. This innovative technology can significantly help drive efficiency and productivity and empower healthcare providers worldwide by providing real time data and clinical interpretation. Emerging medical technology continues to revolutionize healthcare and nursing profession has entered an exciting new frontier of state of the art widgets with high technology communication systems. Some of these new technologies made it possible for nurses to have the ability to utilize all the available big sources of data to make an overall strategy for developing quality care services to improve patients' outcomes through the field of health informatics, awesome inspiring advancements in medical science, telecommunications, and even robotics. The Nurses' workload is astronomical. They have to do countless things at the same time, besides running in and manually doing patient's bed, measuring blood glucose or drawing blood so, these new technologies will provide numerous benefits for nurses, such as freeing up time to provide better-targeted patient care.

Critical Analysis of Laparoscopic Diagnosis in Gynecology: New Era in Healthcare

INTRODUCTION AND OBJECTIVES: Laparoscopy is a diagnostic method that is currently becoming consolidated for therapeutic use. It consists of endoscopically viewing the abdominal cavity. The aim here was to evaluate the indications for diagnostic video laparoscopy and the intraoperative findings in an endoscopic gynecology section of Zulekha hospital, Sharjah UAE over the last few years. RESEARCH DESIGN: Retrospective descriptive study on all diagnostic video laparoscopy procedures of the last five years carried out in the endoscopic gynecology section of Zulekha hospital, Sharjah UAE over the last few years. RESEARCH METHODS: The medical records of 618 women who underwent diagnostic laparoscopy between 2015 and 2020 were analyzed. The clinical characteristics of these women, the indications for video laparoscopy and the intraoperative findings were evaluated. CLINICAL RESULTS: The women’s mean age was 32 ± 6.4 years. Most of the women had already undergone at least one previous operation (60%), which was most frequently a cesarean. The indications for performing video laparoscopy were infertility in 57%, chronic pelvic pain in 27% and others (intrauterine device, adnexal tumor, ectopic pregnancy or pelvic inflammatory disease) in 16%. The main laparoscopic findings were tubal alterations in the group with infertility (59.78%) and peritoneal alterations in the group with chronic pelvic pain (43.54%). CONCLUSION: The main indications for video laparoscopy in gynecology were infertility and chronic pelvic pain. However, in most procedures, no abnormalities justifying these complaints were found.

Toward Emerging Innovations in Electrochemical Biosensing Technology

With the progress of nanoscience and biotechnology, advanced electrochemical biosensors have been widely investigated for various application fields. Such electrochemical sensors are well suited to miniaturization and integration for portable devices and parallel processing chips. Therefore, advanced electrochemical biosensors can open a new era in health care, drug discovery, and environmental monitoring. This Special Issue serves the need to promote exploratory research and development on emerging electrochemical biosensor technologies while aiming to reflect on the current state of research in this emerging field.

Nursing Personnel in the Era of Personalized Healthcare in Clinical Practice.

Personalized, stratified, or precision medicine (PM) introduces a new era in healthcare that tries to identify and predict optimum treatment outcomes for a patient or a cohort. It also introduces new scientific terminologies regarding therapeutic approaches and the need of their adoption from healthcare providers. Till today, evidence-based practice (EBP) was focusing on population averages and their variances among cohorts for clinical values that are essential for optimizing healthcare outcome. It can be stated that EBP and PM are complementary approaches for a modern healthcare system. Healthcare providers through EBP often see the forest (population averages) but miss the trees (individual patients), whereas utilization of PM may not see the forest for the trees. Nursing personnel (NP) play an important role in modern healthcare since they are consulting, educating, and providing care to patients whose needs often needs to be individualized (personalized nursing care, PNC). Based on the clinical issues earlier addressed from clinical pharmacology, EBP, and now encompassed in PM, this review tries to describe the challenges that NP have to face in order to meet the requisites of the new era in healthcare. It presents the demands that should be met for upgrading the provided education and expertise of NP toward an updated role in a modern healthcare system.

Towards a Health 4.0 Framework for the Design of Wearables: Leveraging Human-Centered and Robust Design

With the introduction of Health 4.0 we face a new era in healthcare and notice the disruption of delivery, adoption and use through newly introduced technology. Wearables have become increasingly important in the medical sector and their remote application and widespread use are significant to the development of technology in healthcare today and the future. The implementation of wearables requires regulations and clinical approval when intended to use for health tracking and monitoring. Within this process designers play a crucial role. Design methodologies are the guideline to accomplish a successful path towards the creation of a new product. In this paper the authors explore and draw from established design methodologies to support the creation of a framework for design of wearables in a health 4.0 context. Identifying the positions of design practices and analyzing the correlations in the context of Health 4.0 is therefore presented within this paper.

Can Organizational Leaders Sustain Compassionate, Patient-Centered Care and Mitigate Burnout?

Organizational leaders are recognizing the urgent need to mitigate clinician burnout. They face difficult choices, knowing that burnout threatens the quality and safety of care and the sustainability of their organizations. Creating cultures and system improvements that support the workforce and diminish burnout are vital leadership skills. The motivation to heal draws many health professionals to their chosen work. Further, research suggests that compassion creates a sense of personal reward and professional satisfaction. Although many organizations stress compassion in mission and vision statements, their strategies to enhance well-being largely ignore compassion as a source of joy and connection to purpose.Passage of the HITECH (Health Information Technology for Economic and Clinical Health) Act in 2009 and the Affordable Care Act in 2010 ushered in a new era in healthcare. Little is known about how changes in the healthcare delivery system related to these legislative milestones have influenced health professionals' capacity to offer compassionate care. Further, advances such as artificial intelligence and virtual care modalities brought more attention to the elements that form the clinician-patient relationship.This study analyzed the views of U.S. healthcare providers on the status of compassionate healthcare compared with 2010. Postulating that compassion is inversely correlated with burnout, we studied this relationship and contributing factors. Our review of evidence-based initiatives suggests that leaders must define the organizational conditions and implement processes that support professionals' innate compassion and contribute to their well-being rather than address burnout later through remedial strategies.

Completing the MISSION: a Blueprint for Helping Veterans Make the Most of New Choices.

The June 6, 2019, implementation of the VA Maintaining Internal Systems and Strengthening Integrated Outside Networks (MISSION) Act commenced a new era in health care for Veterans in which the more than 9 million Veterans who use VA care can now choose community (i.e., non-VA) clinicians or facilities when certain new criteria are met. This expansion of Veterans' health care options could give many Veterans more freedom to decide which settings best meet their individual needs and expectations, and could also lead to unintended consequences for Veterans who do not have all of the information they need to make personalized decisions about VA and community care. In this Perspective article, we recommend initial steps that VA leaders and VA clinicians need to take, and community clinicians should be aware of, in order to ensure that Veterans' expanded health care options translate into improvements in their access and outcomes.

PharmActa: Empowering Patients to Avoid Clinical Significant Drug⁻Herb Interactions.

Herbal medicinal products (HMPs) are the subject of increasing interest regarding their benefits for health. However, a serious concern is the potential appearance of clinically significant drug–herb interactions in patients. This work provides an overview of drug–herb interactions and an evaluation of their clinical significance. We discuss how personalized health services and mobile health applications can utilize tools that provide essential information to patients to avoid drug–HMP interactions. There is a specific mention to PharmActa, a dedicated mobile app for personalized pharmaceutical care with information regarding drug–HMPs interactions. Several studies over the years have shown that for some HMPs, the potential to present clinically significant interactions is evident, especially for many of the top selling HMPs. Towards that, PharmActa presents how we can improve the way that information regarding potential drug–herb interactions can be disseminated to the public. The utilization of technologies focusing on medical information and context awareness introduce a new era in healthcare. The exploitation of eHealth tools and pervasive mobile monitoring technologies in the case of HMPs will allow the citizens to be informed and avoid potential drug–HMPs interactions enhancing the effectiveness and ensuring safety for HMPs.

Glimpses of keraleeya ayurveda samajam history

Glimpses of keraleeya ayurveda samajam history