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Review | Open Access

Revolutionizing healthcare and medicine: The impact of modern technologies for a healthier future—A comprehensive review

Aswin Thacharodi1, Prabhakar Singh2, Ramu Meenatchi3, Z. H. Tawfeeq Ahmed2, Rejith R. S. Kumar2, Neha V2, Sanjana Kavish2, Mohsin Maqbool4, Saqib Hassan2,5 ()
Department of Research and Development, Dr. Thacharodi's Laboratories, Puducherry, India
Department of Biotechnology, School of Bio and Chemical Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamilnadu, India
Department of Biotechnology, SRM Institute of Science and Technology, Faculty of Science and Humanities, Kattankulathur, Chengalpattu, Tamilnadu, India
Sidney Kimmel Cancer Center, Jefferson Health Thomas Jefferson University, Philadelphia, Pennsylvania, USA
Future Leaders Mentoring Fellow, American Society for Microbiology, Washington, USA

Aswin Thacharodi, Prabhakar Singh, and Ramu Meenatchi contributed equally to this study.

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The way medical professionals diagnose, treat, and manage diseases has changed dramatically due to several innovative technologies that have emerged in recent years. Thanks to sophisticated algorithms that examine enormous volumes of patient data to find patterns and predict outcomes, artificial intelligence (AI) and machine learning (ML) have become increasingly potent instruments that enable more precise diagnoses. Telemedicine has increased access to healthcare, particularly in rural regions, by facilitating remote monitoring and consultations. Furthermore, wearable technology and IoMT have enabled people to track their health parameters in real‐time, offering insightful information to patients and healthcare professionals. Moreover, personalized therapies have become possible thanks to genomics and personalized medicine developments, which use a patient's genetic information to create exact medications. Together, these technologies have improved healthcare delivery systems’ efficiency and patient‐centeredness while raising the standard of care.

Abstract

The increasing integration of new technologies is driving a fundamental revolution in the healthcare sector. Developments in artificial intelligence (AI), machine learning, and big data analytics have completely transformed the diagnosis, treatment, and care of patients. AI‐powered solutions are enhancing the efficiency and accuracy of healthcare delivery by demonstrating exceptional skills in personalized medicine, early disease detection, and predictive analytics. Furthermore, telemedicine and remote patient monitoring systems have overcome geographical constraints, offering easy and accessible healthcare services, particularly in underserved areas. Wearable technology, the Internet of Medical Things, and sensor technologies have empowered individuals to take an active role in tracking and managing their health. These devices facilitate real‐time data collection, enabling preventive and personalized care. Additionally, the development of 3D printing technology has revolutionized the medical field by enabling the production of customized prosthetics, implants, and anatomical models, significantly impacting surgical planning and treatment strategies. Accepting these advancements holds the potential to create a more patient‐centered, efficient healthcare system that emphasizes individualized care, preventive care, and better overall health outcomes. This review's novelty lies in exploring how these technologies are radically transforming the healthcare industry, paving the way for a more personalized and effective healthcare for all. It highlights the capacity of modern technology to revolutionize healthcare delivery by addressing long‐standing challenges and improving health outcomes. Although the approval and use of digital technology and advanced data analysis face scientific and regulatory obstacles, they have the potential for transforming translational research. as these technologies continue to evolve, they are poised to significantly alter the healthcare environment, offering a more sustainable, efficient, and accessible healthcare ecosystem for future generations. Innovation across multiple fronts will shape the future of advanced healthcare technology, revolutionizing the provision of healthcare, enhancing patient outcomes, and equipping both patients and healthcare professionals with the tools to make better decisions and receive personalized treatment. As these technologies continue to develop and become integrated into standard healthcare practices, the future of healthcare will probably be more accessible, effective, and efficient than ever before.

Keywords

Artificial Intelligencehealthcaremachine learningmulti‐omicsprecision medicine

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Health Care Science
Volume 3 Issue 5,
October 2024
Pages 329-349
DOI: 10.1002/hcs2.115
Cite this article:
Thacharodi A, Singh P, Meenatchi R, et al. Revolutionizing healthcare and medicine: The impact of modern technologies for a healthier future—A comprehensive review. Health Care Science, 2024, 3(5): 329-349. https://doi.org/10.1002/hcs2.115
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Comparative analysis of the recent publications related to use of the modern technologies in healthcare.

Title of the articleAimFindings/ResultsConclusionsReferences
Multimodal Healthcare AI: Identifying and Designing Clinically Relevant Vision Language Applications for RadiologyTo explore the application of vision‐language models (VLMs) in radiology to enhance clinical workflows. VLMs can assist in generating draft reports from images, facilitating augmented report reviews, and highlighting patient imaging historiesClinicians prefer tool‐based interactions over chatbots for clinical decision support due to time constraints and trust issues, emphasizing AI\'s role as an information resource rather than a decision agentDirecting new AI towards specific, practical tasks can ensure effective integration into workflows and the development of useful mental models for AI usage. Researchers discovered that AI serves as an effective tool for extracting and processing information, supporting human interpretation[6]
Securing the Future of IoT Healthcare Systems: A Meta‐Synthesis of Mandatory Security RequirementsTo identify the necessary security requirements for the implementation of H‐IoT systems using a meta‐synthesis approach14 security requirements were determined, focusing on quantitative and technical propertiesAddressing these security requirements is crucial to safeguarding H‐IoT systems and ensuring resilience in healthcare information security[7]
Role of Emerging Technologies In Future Iot-Driven Healthcare 4.0 Technologies: A Survey, Current Challenges and Future DirectionsTo gain a comprehensive understanding of various emerging technologies and offer insights for future H‐IoT systemsBlock chain, edge computing, and machine learning, can greatly improve performance metrics like accuracy and response time while meeting QoS requirementsInteroperability, scalability, affordability, and privacy[8]
The Role of Artificial Intelligence in Healthcare: A Structured Literature ReviewTo examine the current state of AI research in healthcare, with an emphasis on diagnostics, predictive medicine, and health services managementUsing bibliometric analysis, the study finds five primary clusters related to AI in healthcare while highlighting the advantages of AI enhances diagnosis precision and decision‐makingSignificant challenges exist in ethics, data governance, and health workforce competencies[9]
Explainable Artificial Intelligence for Predictive Modelling in HealthcareTo explore how explainable AI (XAI) can enhance the trust and applicability in healthcare predictive modellingTransparency concerns and professional trust are vital; XAI can address these concernsSuccessful adoption of AI requires both technology advancement and stakeholders involvement[10]
Enabling Artificial Intelligence of Things (AIoT) Healthcare Architectures and Listing Security IssuesTo assess and disseminate information on AIoT medical innovations in healthcareIoT applications in healthcare are still in their early stages, with limited utilization causing challenges in various subfieldsInterdisciplinary integration and security concerns need to be addressed[11]
Recent Advancements in Emerging Technologies for Healthcare Management Systems: A SurveyTo evaluate the application of Smart Sensor, IoT, AI, Blockchain in healthcare management systemsIoT‐assisted wearable sensor systems, AI, and Blockchain, as well as the critical concerns that must be addressed to enhance the application of these emerging technologies in the healthcare management systemProvides a detailed review of these technologies in healthcare management systems[12]
Advancements and Future Prospects of Wearable Sensing Technology for Healthcare ApplicationsTo discuss the relevance and future development of wearable devices in the customized healthcareThe difficulty of delivering effective real‐time medical services has been demonstrated to be overcome by wearable sensors and related healthcare systemsFew privacy concerns include sensor reading accuracy, and compatibility with medical ecosystems; it may take time for these wearables to be widely adopted[13]
The Cost‐Effectiveness of Digital Health Interventions: A Systematic Review of the LiteratureTo summarize the evidence on the cost‐effectiveness of digital health interventions and assess whether the studies meet established quality criteriaResults regarding the cost‐effectiveness of digital interventions indicated a typically positive impact in terms of costs and health outcomes, supported by an increasing body of research. However, it is still challenging to compare different interventions because of the variability in study techniquesFurther research based on a standardized approach is needed to methodically analyze incremental cost‐effectiveness ratios, costs, and health benefits[14]
Application of Internet of Things and Sensors in HealthcareTo discuss different applications, technologies, and challenges related to the healthcare systemThe IoT provides services that allow a patient to instantly communicate health‐related data in real‐time with a particular physician and healthcare system. Nonetheless, there are a number of IoT‐related issues that need to be resolved to enhance the healthcare systemBy eliminating the insufficiencies in IoT apps and technologies, a more innovative IoT healthcare system can be accomplished with more facilities to the healthcare system in a cost‐effective manner[15]
The Impact of Telemedicine and Remote Patient Monitoring on Healthcare Delivery: A Comprehensive EvaluationTo evaluate the impact of new technologies on healthcare delivery, focusing on patient outcomes, economic parameters, and overall satisfactionPrimary outcomes revealed significant improvements in patient health. The healthcare costs were found to decrease. Secondary results demonstrated increased patient satisfaction with communication and increase in convenience of services. Accessibility to healthcare services improved, reducing geographic barriersThe study offers strong evidence of the beneficial effects of remote patient monitoring and telemedicine on the provision of healthcare, highlighting the transformational potential of these technologies[16]
Robots in Healthcare: A Scoping ReviewTo establish the types of robots being used in healthcareAdvances in technology have made it possible for robots to perform a wider range of intricate tasks in the healthcare sector. According to this review, there are ten primary roles that robots have fulfilled in various healthcare settings. The two main responsibilities were mobility and rehabilitation and surgeryThe COVID‐19 demonstrates the changing demands of healthcare, and robots may be able to help with this adaptation[17]
The Use of Big Data Analytics in healthcareTo analyze the possibilities of using Big Data Analytics in healthcareThe use of Big Data Analytics bring benefits medical facilitiesResults of the study confirm that medical facilities are moving towards data‐based healthcare, together with its benefits[18]
Artificial Intelligence Ethics in Precision Oncology: Balancing Advancements in Technology With Patient Privacy and AutonomyTo provide an overview of earlier research on the application of AI in precision oncology and the ethical concerns raised by this technology is providedThe application of AI to precision oncology holds the potential to completely transform cancer care, ethical concerns should be taken care ofAI in precision oncology could lead to better cancer outcomes. However, the development and application of AI in precision oncology must be based on ethical considerations pertaining to patient privacy, autonomy, and bias prevention[19]
3D Bioprinting for Next‐Generation Personalized MedicineTo introduce the principles and techniques of bioprinting, focusing on predominant methods including extrusion printing and digital light processingBioprinting has emerged as a promising technology in personalized medicine, with rapid progress and promising preliminary results3D bioprinting has the potential to revolutionize the design of next‐generation personalized medicine with additional technological advancement and biological validation[20]

Multi‐omics databases for research in precision medicine.

ConsortiumLatest release StatusOmics assaysReferences
Type: Cancer
COSMIC v9928‐Nov‐23Genomics, Transcriptomics, Epigenomicshttps://cancer.sanger.ac.uk/cosmic
Genomic Data Commons Data Portal 39.004‐Nov‐23Genomics, Transcriptomics, Epigenomicshttps://portal.gdc.cancer.gov/
NCI Proteomic Data Commons V1.6.816‐Nov‐23RNA‐seq, miRNAs, global proteomehttps://pdc.cancer.gov/pdc/
Therapeutically Applicable Research to Generate Effective Treatments (TARGET)2016Genomic, transcriptomic, and Epigenomic datahttps://www.cancer.gov/ccg/research/genome-sequencing/target/using-target-data
TIMER2.02020EpigenomicsTranscriptomicsProteomicsImmunomicshttp://timer.cistrome.org/
Gene Expression Profiling Interactive Analysis (GEPIA)2021GenomicsEpigenomicsTranscriptomicsProteomicsImmunomicshttp://gepia.cancer-pku.cn/
Molecular Taxonomy of Breast Cancer International Consortium (METABRIC)−GenomicsTranscriptomicsImmunomicshttps://www.mercuriolab.umassmed.edu/metabric
Human Cancer Models Initiative (HCMI)−Genomic, transcriptomic, and Epigenomic datahttps://portal.gdc.cancer.gov/projects/HCMI-CMDC
Type: Alzheimer\'s Disease
The Alzheimer\'s Disease Neuroimaging Initiative (ADNI)2004Genetic, magnetic resonance imaging, and positron emission tomography imaginghttps://adni.loni.usc.edu/
Type: Parkinson\'s Disease
Parkinson\'s Disease Biomarker Discovery (PDBD)2018Transcriptomics, epigenomics, whole genome sequencing, metabolomics, and proteomicshttps://pdbp.ninds.nih.gov/
Parkinson\'s Progression Markers Initiative (PPMI)2018Transcriptomics, epigenomics, whole genome sequencing, metabolomics, and proteomicshttps://www.ppmi-info.org/
Type: Neuropsychiatric disease
PsychENCODE2015Whole genome sequences, Transcriptomicshttps://psychencode.synapse.org/
NIMH Repository and Genomic resources−RNA and DNA sequencing, genotyping, epigeneticshttps://www.nimhgenetics.org/
Type: Human genetic variations
The International Genome Sample Resource (IGSR)2007Whole genome sequences, Targeted Exome sequencinghttps://www.internationalgenome.org/
UK Biobank2007Genotyping, Whole genome sequenceshttps://www.ukbiobank.ac.uk/
Functional Annotation of the Mammalian Genome (FANTOM)2000RNA‐seq, RADICL‐seq, Cap Analysis of Gene Expressionhttps://fantom.gsc.riken.jp/
The Genotype‐Tissue Expression (GTEx)2010Whole genome sequences, WES, and RNA‐Seqhttps://www.gtexportal.org/home/