Exploration of Artificial Intelligence Assisted Health Risk Prediction

Abstract

AI Assisted Health Risk Prediction uses personalized knowledge and information gathered from the responses it creates to solve both simple and difficult problems. Amazing improvements in computing power and AI technologies may revolutionize the process of creating new medications. Due to increasing R&D costs and decreased efficiency, the pharmaceutical industry is currently experiencing difficulties with medication development. The key causes of the high attrition rates in drug approval will be covered in this overview, along with potential methods "The procedure involves gathering data, establishing rules for its utilization, reaching approximate or definitive conclusions, and self-correction. The development of AI can be seen as having two contrasting effects: on one hand, many individuals are concerned about job security, while on the other hand, each advancement is celebrated as a significant stride for civilization. Numerous industries, such as education and business process automation, employ AI. The idea of integrating AI into the drug development process has shifted from hype to optimism. The potential applications of AI in this field are vast." to drug development pipeline, drug development techniques and procedures, pharmaceutical R&D are discussed in this paper.Artificial intelligence (AI)-assisted health risk prediction refers to the use of AIalgorithms and techniques to analyze health data and predict the risk of developing certain health conditions or diseases. The weighted product method is a multi-criteria decision-making process is there are many alternatives, and based on several criteria we must determine the best alternative.RPM1, RPM2, RPM3, RPM4, RPM5.Usefulness, Social factors, Ease of use, Quality of technological service, Compatibility"While no pharmaceuticals have been created using AI methods to date, according to the developments discussed in this study, it is anticipated that it will take another 2-3 years before a drug is developed. It is interesting to note that specialists firmly believe AI will fundamentally alter the pharmaceutical sector and the process of medication development.""However, domain expertise is crucial for training algorithms, which is essential for efficient AI-assisted drug development. While domain expertise allows individuals to process vast datasets, AI algorithms can be trained, algorithms can be defined, and the examined data can be improved to facilitate a faster and more accurate drug development process.""This creates an ideal environment for collaboration between AI and medicinal chemists. Despite the potential of AI to accelerate medication discovery, real studies still need to be conducted. Furthermore, AI can also assist in areas such as gene therapy and other therapies that are not yet widely available in healthcare.". AI opens up the prospect of merging gene therapy, pharmacology, and regenerative medicine.