Research on Healthcare using AI
Overview
Research on Healthcare is a direct value-addition to the life of mankind. Artificial Intelligence has a lot of things to do in the healthcare field.
Research on Healthcare
Research on Healthcare
Sunena Rose M V
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Research on Healthcare is a direct value-addition to the life of mankind. It can improve the quality of healthcare by providing relevant, high-quality, and safe real-world data. Quality of care can be enhanced by utilizing research to develop and implement evidence-based solutions tailored to individual patient’s needs, which can also be related to technological advancements like Artificial Intelligence and the digitalization of the industry.
Artificial intelligence in medicine uses machine learning models to search medical data and uncover insights to help improve health outcomes and patient experiences. AI algorithms and other applications powered by AI are being used to support medical professionals in clinical settings and ongoing research. Currently, the most common roles for AI in medical settings are clinical decision support and imaging analysis. Clinical decision support tools help providers make decisions about treatments, medications, mental health, and other patient needs by providing them with quick access to information or research that's relevant to their patients. In medical imaging, AI tools are being used to analyze CT scans, x-rays, MRIs, and other images for lesions or other findings that a human radiologist might miss. The research and results of these tests are still being gathered, and the overall standards for the use of AI in medicine are still being defined. Yet opportunities for AI to benefit clinicians, researchers, and the patients they serve are steadily increasing. At this point, there is little doubt that AI will become a core part of the digital health systems that shape and support modern medicine. There are numerous ways AI can positively impact the practice of medicine, whether it's through speeding up the pace of research or helping clinicians make better decisions.
Machine learning models could be used to observe the vital signs of patients receiving critical care and alert clinicians if certain risk factors increase. While medical devices like heart monitors can track vital signs, AI can collect the data from those devices and look for more complex conditions. Precision medicine could become easier to support with virtual AI assistance. Because AI models can learn and retain preferences, AI has the potential to provide customized real-time recommendations to patients around the clock. Rather than having to repeat information with a new person each time, a healthcare system could offer patients around-the-clock access to an AI-powered virtual assistant that could answer questions based on the patient's medical history, preferences, and personal needs.
Integrating medical AI into clinician workflows can give providers valuable context while making care decisions. A trained machine learning algorithm can help reduce research time by giving clinicians valuable search results with evidence-based insights about treatments and procedures while the patient is still in the room with them.
References
https://www.healthanalytics.com/expertise/benefits-of-research-in-healthcare/
https://builtin.com/artificial-intelligence/artificial-intelligence-healthcare
Secinaro, S., Calandra, D., Secinaro, A. et al. The role of artificial intelligence in healthcare: a structured literature review. BMC Med Inform Decis Mak 21, 125 (2021). https://doi.org/10.1186/s12911-021-01488-9
S. Gaikwad, "Study on Artificial Intelligence in Healthcare," 2021 7th International Conference on Advanced Computing and Communication Systems (ICACCS), Coimbatore, India, 2021, pp. 1165-1169, doi: 10.1109/ICACCS51430.2021.9441741.