Vocal Biomarkers in Healthcare

Declaration of Topic

The development of technologies alters every domain of human life, including healthcare. Artificial intelligence (AI) will be used increasingly in the healthcare industry as a result of the developments in this sector. Payers, healthcare organizations, and businesses involved in the life sciences are already utilizing a variety of artificial intelligence technologies (Fagherazzi et al., 2021). Although there are numerous situations where artificial intelligence can do healthcare activities better than humans, factors related to the introduction of large-scale automation must be considered (Mucke et al., 2022). The ability of vocal biomarkers to transform diagnoses is astounding. AI-based speech analysis offers up new horizons in medicine since some illnesses, such as those that affect the heart, lungs, vocal cords, or brain, can alter a person’s voice (Fagherazzi et al., 2021). COVID screening can make use of biomarkers for diagnosis and remote monitoring. This technology has the potential to influence the development of society.

Contextual Information

Vocal biomarkers now in use come in a variety of forms. A vocal biomarker is a signature, feature, or combination of features of the audio signal of the voice that is connected to the clinical outcome (Maor et al., 2020). It can be used to track patients, make a diagnosis, gauge the severity or stages of a disease, or prescribe drugs for growth (Mucke et al., 2022). Moreover, it must have all the characteristics of a conventional biomarker that is employed, qualified, and subject to analytical validation. Vocal biomarkers can aid in the earlier detection of some diseases than the standard screening approach, which in some cases is crucial for a patient (Maor et al., 2020). In an ideal situation, there would be no need to visit the doctor, wait for pricey tests to be completed, and then wait days for the results.

The following are the main issues that this study focuses on. The theoretical and practical development of technology must first be traced. This will make it possible to analyze its advantages and disadvantages in-depth, as well as its true potential. Second, the technology’s potential implications will be evaluated and analyzed. A SWOT analysis will be necessary for this situation, making it the ideal framework. Finally, in order to evaluate the impact of technology on the evolution of society, the social consequences and theoretical adoption hurdles will be examined. Although it is obvious that such an AI-based medical module might completely transform the healthcare industry, nothing is known about it. Therefore, both healthcare professionals and anybody interested in the technological advancement of healthcare in particular and its possible effects on society are included in the intended audience.

Literature Review

Analysis of voice and speech for medical diagnosis and therapy evaluations appears to have gained popularity recently. This has the potential to spread widely and be a respected addition to the therapeutic literature. The work thus complements a growing collection of related literature. For instance, the paper by Fagherazzi et al. (2021) builds on the analysis of the biomarkers theoretical research and its potential implementation in clinical practice. Another example, an article by Maor et al. (2020), aims at researching the technology in its applicability to heart failure cases and other coronary diseases. Mucke et al. (2022) employed the technology in the research in the field of rheumatoid arthritis. This study expands on earlier studies that identified advancements in vocal biomarker technology that might encourage adoption.

References

Fagherazzi, G., Fischer, A., Ismael, M., & Despotovic, V. (2021). Voice for health: The use of vocal biomarkers from research to clinical practice. Digital Biomarkers, 5(1), 78-88. Web.

Maor, E., Perry, D., Mevorach, D., Taiblum, N., Luz, Y., Mazin, I. & Shalev, V. (2020). A vocal biomarker is associated with hospitalization and mortality among heart failure patients. Journal of the American Heart Association, 9(7), e013359. Web.

Mucke, J., Krusche, M., & Burmester, G. R. (2022). A broad look into the future of rheumatoid arthritis. Therapeutic Advances in Musculoskeletal Disease, 14(1), 1759720X221076211. Web.

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StudyCorgi. "Vocal Biomarkers in Healthcare." August 31, 2023. https://studycorgi.com/vocal-biomarkers-in-healthcare/.

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StudyCorgi. 2023. "Vocal Biomarkers in Healthcare." August 31, 2023. https://studycorgi.com/vocal-biomarkers-in-healthcare/.

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