Advanced clinical and medical applications with the employment of Artificial Intelligence (AI) algorithms can facilitate with accurate and timely diagnosis and prognosis. While AI algorithms care capable of analyzing medical images, patient records and genetic data to some extent, personalized treatment and precision medicine with the use of AI can provide the development of customized treatment solutions through the analysis of individual patient data, which can bring about more tailored therapies, well-adjusted dosage, regimens and efficacy. In addition to these key points, operational efficiency is enabled through the streamlining of AI in terms of administrative missions like scheduling and other tasks that have to do with healthcare services. Predictive analysis is evident through the mathematical models which are capable of providing prediction about the outbreaks of diseases and patients’ progresses and follow-ups. Thus, preventative measures can be taken in a timely manner. Considering the medication and its related processes, AI, in medical and clinical applications, may accelerate the process of drug discoveries by predicting the way different compounds interact with the target aspects, which in turn reduces the burden, time, cost and workload.
Clinical and medical problems are important challenges of mankind involving life, well-being and human health. As the progress of human society is evolving, so is the field of medicine with modern medicine facing the requirement of not only treating diseases but also preventing them at various scales. [Migliori, G.B., et al.(2022)], [Liu, Y., et al. (2023)].
It is possible to model and analyze many medical problems, which paves the way towards the nature and laws governing medical problems with the ultimate aim of improving precision and efficiency of medical research, maintaining and enhancing life quality and providing a scientific foundation for medical practice. Through the building of mathematical models, researchers can be facilitated in terms of understanding the intrinsic mechanisms of biological systems, optimizing diagnosis as well as treatment plans, predicting and / or preventing the occurrence and spreading.
Given these considerations and aims, the integration of advanced models in clinical and medical applications can serve improving of accuracy in diagnosis by reducing human error, enhancing patients’ outcomes, reducing related costs through the optimization of operations and acceleration of process mentioned above. Besides these, an important point to achieve is improved patient care and maintaining the life quality of the patients through the timely support to patients, which will in turn improve their decision-making processes and management of the patients. Another important benefit is related to scalability since it is possible that AI systems can handle large volumes of data by providing consistent and reliable results to render solutions scalability for healthcare systems. Last but not least, early detection through AI and mathematical models can ensure timely detection as regards diseases to be able to intervene promptly for a better prognosis in medical and clinical applications.
Regarding advanced clinical and medical applications with the employment of AI, the following realms can be put forth:
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