The increase in the knowledge regarding diseases and human health has been critical as science opens more opportunities to overcome medical and non-medical factors affecting health. Over the past several decades, human society has valued technological advances in healthcare and the promise to enhance health and disease management. While there are many advances in healthcare from many scientific fronts, the most recent technological advancements in healthcare include telemedicine, cloud computing and artificial intelligence.
According to the Centre for Disease Control and Prevention (CDC), telemedicine is the practice of using telecommunication technology and electronic information to get the health care needed without physical visits to a health practitioner or the medical facility. It is the perfect analogy for remote access to healthcare. One only needs an electronic device such as a smartphone that connects to the internet to access healthcare remotely (Fix, 188). With telemedicine technology, one can discuss medical issues, symptoms and more with healthcare givers in real-time using video conferencing, textual channels or other online audio portals. Some examples are remote medical evaluations and diagnosis, video consultation with specialists and digital transmission of medical imaging.
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Cloud computing has also played a significant role in the immense evolution of collecting, storing, and accessing healthcare data. The industry has come a long way in optimizing its data management activities from orthodox storage to healthcare data digitization. For an organization that has traditionally lagged behind its generations, the healthcare sector is on top when cloud computing implementation is concerned. The West Monroe Partner’s report shows that 35% of healthcare corporations gaged over 50% of cloud infrastructure or data (Symvoulidis et al., 11). Healthcare is hence confirmed to be the utmost along with cloud adoption as opposed to other organizations. The extensive cloud computing adoption in the healthcare industry goes far beyond data storage on cloud infrastructure. Healthcare specialists are now leveraging this technology to reduce the costs related to healthcare delivery, optimize workflows, gain efficiencies, and offer personalization in care plans to improve outcomes.
In addition, artificial intelligence in healthcare (AI) is the principal term used to define software and machine-learning algorithms, or artificial intelligence to mimic human cognizance in the presentation, analysis and comprehension of complex healthcare and medical data. The health-related AI applications main aim is to analyze the relationship between treatment and prevention techniques and patient results (Yu et al., 98). AI programs are applied in developing a protocol, diagnosis procedure, tailored medicine, drug advance and patient nursing. AI algorithms can also scrutinize vast data quantity through electronic health records for disease diagnosis and prevention.
In conclusion, more efficient and rational development in the invention procedure will need new types and stronger alliances in an evaluative study among different participants: new technology developers, those who enhance and employ evaluation tools, and those who use resulting data for administrative authorization, clinical options or repayment. Likewise, it will necessitate a readiness to discuss and research the regularly integral worth of various evaluative strategies for further developing formative direction.
Fix, Oren K., and Marina Serper. “Telemedicine and telehepatology during the COVID‐19 pandemic.” Clinical liver disease 15.5 (2020): 187-190.
Symvoulidis, Chrysostomos, et al. “Healthcare Provision in the Cloud: An EHR Object Store-based Cloud Used for Emergency.” HEALTH INF. 2021. Yu, Kun-Hsing, Andrew L. Beam, and Isaac S. Kohane. “Artificial intelligence in