by Tomás Freyer | May 9, 2023 | Artificial Intelligence
Predictive analytics tools are AI applications that have the potential to transform the healthcare industry, among others. By analyzing vast amounts of patient data, AI algorithms can predict the likelihood of developing certain diseases and identify which treatments are most likely to be effective for a particular patient, por example. In this blog post, we will explore how developing predictive analytics with AI can improve the goals of the healthcare industry.
Its contributions can be highly positive in these areas:
- Early Detection of Diseases: One of the main goals of the healthcare industry is to detect diseases early, when they are most treatable. Predictive analytics can help achieve this goal by analyzing patient data to identify those at risk of developing a disease. This allows doctors to intervene early with preventative measures or early treatments, increasing the chances of successful outcomes.
- Improved Patient Outcomes: The healthcare industry is focused on improving patient outcomes, and predictive analytics can help achieve this by identifying which treatments are most likely to be effective for a particular patient. By analyzing patient data, AI can predict how a patient is likely to respond to a particular treatment, allowing doctors to tailor their approach and improve the chances of success.
- Reduced Healthcare Costs: Another goal of the healthcare industry is to reduce healthcare costs. Predictive analytics can help achieve this by reducing the need for expensive and unnecessary treatments. By analyzing patient data, AI can predict which treatments are most likely to be effective for a particular patient, reducing the need for trial and error and potentially saving money on ineffective treatments.
- Personalized Medicine: The healthcare industry is increasingly focused on personalized medicine, and predictive analytics is a key part of achieving this objective. By analyzing patient data, AI can create personalized treatment plans based on a patient’s unique characteristics, such as genetics and environmental factors. This can lead to more effective treatments with fewer side effects.
- Improved Population Health: The healthcare industry is also focused on improving population health, and predictive analytics can help achieve this goal by identifying trends and patterns in patient data. By analyzing large datasets, AI can identify risk factors for certain diseases and help healthcare providers develop targeted interventions to improve the health of populations.
- Training: You could build your own training platform using OpenAI. Through the “Information Search” function you can get online data about drug types and typical information contained in a drug package insert and then you can design personalized exams. Using the “Text Analysis” function you can compare the text of the information obtained versus the text of the answer entered by the trainee and according to the % of accuracy obtained give a score to his answer.
In conclusion, the development of predictive analytics tools with AI can help improve the goals of the healthcare sector by enabling an infinite range of possibilities and solutions to industry needs. As with any AI application, it is important to ensure that predictive analytics is developed and used in an ethical and transparent manner, with the interests of patients at the Forefront.
When looking for a software development vendor working with an OpenAI-powered model, it is of high importance to verify that they have a strong commitment to ethical and patient-friendly practices in the development of AI applications for the healthcare sector. At Huenei we have a strong privacy and data protection policy that ensures that patient data is protected and used in a transparent and ethical manner, ensuring the best results and a highly satisfactory user experience.
by Tomás Freyer | May 6, 2023 | Artificial Intelligence
How can you make a Chat GPT integration with OpenAI models into a software development successfully?
Technology advances by leaps and bounds and provides us with more solutions and possibilities to explore in the world of development, which can take us to unimagined places. The need to be constantly at the forefront of this range of possibilities, leads us to be in training and learning 24/7, which allows us to incorporate new expertise to, for example, integrate OpenAI models within projects with cutting-edge technology, such as a Chat GPT integration.
In this blog post we want to share with you how together with one of our large clients we have managed to implement a concrete business case where we made a Chat GPT integration into a custom software solution.
The objective of the application is to provide a dynamic and flexible training platform for the sales force of a renowned pharmaceutical laboratory, with the ability to obtain online information without the need to perform previous data uploads, saving costs and time.
The software solution, beyond including standard user, group and profile administration functionalities, contains modules related to training management: roles, suggested exams per role, exam form and results tracking per exam, per role and per group.
The important innovation we achieved is the integration with Chat GPT combining two of its main functionalities: Information Search and Text Analysis.
After a series of concept tests carried out by our team of Prompt Engineers together with business specialists on the client’s side to refine the parameters that allow us to obtain information in an accurate, reliable and fair way in terms of the amount of bytes sent and received to optimize costs, we concluded the following:
- We use “Information Search” to obtain online information related to drug types, typical information contained in a drug package insert.
- We use “Text Analysis” to compare the text of the information obtained versus the text of the answer entered by the user and according to the % of accuracy obtained we give a score to his answer.
The sum of your scores will give you a final result that is recorded and will be part of your training record through integration with your LMS (Learn Management System).
The results are amazing with a tremendous positive impact for the client in terms of cost and time due to the high degree of automation of the process for training your sales force.
by Tomás Freyer | May 6, 2023 | Artificial Intelligence
Organizations are constantly seeking ways to boost productivity, streamline processes, and improve customer experience; Generative AI is helping them achieve that thanks to OpenAI benefits.
Generative AI can be particularly useful in business software applications in several ways. Let’s go through some OpenAI benefits:
- Data Analysis: Generative AI can be used to analyze large amounts of data and identify patterns and trends. This can help businesses make better decisions and optimize their operations. For example, generative AI can be used to analyze customer data to identify buying patterns and preferences, which can help businesses tailor their marketing strategies to specific customer groups.
- Personalization: Generative AI can be used to personalize the user experience in applications by generating customized content for each user. For example, a news application can generate personalized news articles for each user based on their reading habits and interests.
- Training: Generative AI can be used to create customized content training in many subjects for different departments of your organization. (Sales force, technical training, etc.)
- Predictive Maintenance: Generative AI can be used to predict equipment failures and maintenance needs by analyzing data from sensors and other sources. This can help businesses avoid costly downtime and reduce maintenance costs by performing maintenance only when needed.
- Regionalization: Generative AI can be used to regionalize your app to different languages and expand its global reach.
Generative AI can help businesses streamline operations, reduce costs, and make better decisions by leveraging the power of data analysis and machine learning. However, businesses must exercise quality control over the generated content to ensure its accuracy and consistency.
In conclusion, Generative AI is proving to be a game-changer for businesses looking to improve their operations and customer experience. OpenAI benefits organizations by providing them with advanced data analysis, personalization, training, predictive maintenance, and regionalization capabilities. By leveraging these benefits, businesses can increase productivity, reduce costs, and make better decisions. However, it is crucial for businesses to ensure the accuracy and consistency of the results through quality control measures. With OpenAI model-powered development services, businesses can create customized models that deliver real results and take their operations to new heights.
As a provider of OpenAI model-powered development services we can help you create custom models that deliver real results and take your business to new heights.