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Artificial intelligence in healthcare is transforming disease treatment - Discover the key steps to implement AI models and optimize your healthcare system.
Artificial intelligence in healthcare has come to revolutionize disease treatment and improve efficiency in healthcare systems. Addressing chronic diseases requires significant resources and high operational costs, which, if not managed properly, can create an unsustainable burden for both the system and the patient. In this context, artificial intelligence (AI) is a crucial tool that not only optimizes resource management but also improves diagnostic accuracy, personalizes treatments, and reduces response times in patient care.The approach taken by companies like Arkangel Ai, a leader in implementing AI in healthcare across 18 countries and impacting 68 million people, demonstrates the transformation that AI can achieve. Through predictive and non-predictive models, AI addresses significant challenges: treatment adherence, cost reduction, and improved diagnostic times.However, for these models to work effectively, a clear and careful methodology is essential. This article outlines the essential steps in implementing AI models in healthcare, providing a guide to maximize the potential of this disruptive technology.
Chronic diseases account for more than 40% of healthcare costs, and with an aging global population, this percentage continues to increase. These conditions require constant monitoring and effective management to avoid complications and prolonged hospitalizations. Detecting and treating these conditions early not only improves patients' lives but also enables hospitals, insurers, and government agencies to manage their resources more effectively. This is where artificial intelligence plays a decisive role in optimizing the diagnosis, prognosis, and treatment of these diseases.However, implementing AI in the healthcare sector is no simple task. It requires detailed planning, selecting the right model, validating results, and adhering to ethical and privacy standards. Below, we explain each key step in this implementation process.
Before selecting any artificial intelligence model, the first step is to clearly define the problem to be solved. In the healthcare industry, objectives can vary widely: from improving treatment adherence, reducing operational costs, to increasing diagnostic accuracy. Identifying this objective is crucial, as it will guide the development and selection of the AI model.According to Arkangel Ai’s experience, a common mistake in this phase is that many organizations have a general understanding of the problem but lack insight into the specific causes that originate it. For instance, if a hospital faces challenges in increasing access to treatments, it's essential to ask why this limitation occurs and what data is needed to understand the context. This thorough analysis can take hours to weeks and is the foundation for successful AI implementation aligned with business objectives.
Once the problem is identified, the next step is to collect and organize the data to train the model. Information in healthcare is often fragmented across multiple systems and formats, making it difficult to analyze. However, AI technology can process and structure large volumes of data, providing a solid foundation for decision-making.Arkangel Ai notes that data disorganization is not a barrier. AI can help organize this information and start generating results quickly, even within weeks, with the right tools and approach. Data collection is one of the most critical phases of the project, as it determines the accuracy and effectiveness of the AI model.
With data ready, the next step is to select the artificial intelligence model best suited to the identified problem. There are two main types of models in healthcare: predictive and non-predictive, each with specific characteristics and applications.
With the model selected, the next step is to test and validate the results in a controlled environment. This stage is critical to ensuring the model functions correctly and meets the required safety and privacy standards in the healthcare sector. Arkangel Ai adheres to ISO 27001 standards to ensure that all data and models are protected in line with current regulations.Testing typically lasts one to two months and allows developers to identify improvement areas and adjust model parameters to maximize accuracy. Additionally, this process offers the opportunity to test the real impact of AI in clinical practice before full deployment.
Once validated, the model is deployed within the organization’s system, enabling AI to start generating value immediately. This implementation process takes approximately 15 days, allowing the model to integrate effectively with existing systems.However, artificial intelligence is not static. During the first six months after implementation, Arkangel Ai continuously monitors model performance and retrains the system with real data. This constant adjustment allows the model to improve over time and maintain effectiveness in a constantly changing environment.This monitoring also helps assess key performance indicators (KPIs), such as cost reduction, optimized care times, and patient health impact. Thanks to this methodology, the AI models implemented by Arkangel Ai have helped healthcare institutions make faster, more accurate, and cost-effective decisions.
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Artificial intelligence in healthcare has become an invaluable ally in improving disease treatment, especially for chronic conditions. By implementing AI models, healthcare organizations can optimize resources, reduce costs, and provide patients with more personalized and precise care. The methodology of companies like Arkangel Ai, which already impacts millions of people in 18 countries, demonstrates that this technology is not only effective but also scalable and capable of meeting the strictest security and privacy standards.AI is revolutionizing the healthcare sector, and those who don’t integrate it into their processes risk falling behind. Careful and strategic implementation of this technology maximizes its benefits, improves patients' quality of life, and builds a more efficient and sustainable healthcare system.If your organization seeks to incorporate artificial intelligence into its operations, Arkangel Ai’s experience shows how to leverage this technology at every stage, from planning to continuous monitoring.
