With its growing impact on society, artificial intelligence (AI) has brought significant changes to various sectors, and healthcare is no exception. According to the World Health Organization (WHO), AI holds immense potential to improve the quality of services provided by operators, doctors, nurses, and more. From patient triage to personalized treatments, this technology enhances the efficiency of healthcare systems, enables early diagnoses, detects patterns in lab results, and much more.
In this article, you’ll find:
- The role of artificial intelligence in healthcare.
- The main benefits of AI in the medical field.
- Challenges in adopting the technology.
- Practical examples of its application.
- The future of AI in medical care.
Let's go?
Understanding artificial intelligence in healthcare
Before exploring how artificial intelligence operates in healthcare, let’s first understand the concept of this technology. Simply put, artificial intelligence refers to systems capable of simulating human reasoning. Computers analyze data, learn patterns, and make decisions automatically. The term "AI" was coined in 1956 during a conference at Dartmouth College in the United States, where researchers set out to study how machines could mimic human intelligence.
In the context of healthcare, this ability to "think" and "learn" allows AI to be applied across various areas, such as clinical support, hospital management, and patient monitoring. With advanced algorithms, AI makes medical care more accessible and secure, benefiting patients, service providers, and healthcare operators. It also accelerates drug discovery, contributes to the development of personalized therapies, and boosts scientific research.
How artificial intelligence improves efficiency and accuracy in healthcare
AI has already driven advancements in the healthcare sector. According to a study by the National Association of Private Hospitals (Anahp) and the Brazilian Association of Health Startups (ABSS), 62.5% of institutions use artificial intelligence in some capacity. Of the 45 hospitals participating in the study, more than half adopted the technology to focus on improvements and problem-solving, with 51% reporting practical results.
The technology also enhances medical records and documentation while supporting clinical decision-making. Here are some additional examples:
- Enhancing the clinical journey: by predicting needs, coordinating care, and identifying areas for improvement, AI makes the clinical journey more efficient and patient-centered.
- Resource optimization: AI improves resource allocation, appointment scheduling, and supply chain management, resulting in leaner and more qualified operations.
- Fraud detection: pattern analysis identifies irregularities with precision, saving costs and increasing trust among patients and professionals.
- Epidemic outbreak prediction and control: AI processes population data and trends to predict disease spread and assist in formulating public health policies.
- Administrative task automation: hospitals and clinics can streamline procedure authorizations and appointment scheduling.
By identifying hard-to-diagnose diseases and reducing medical error rates, AI outperforms traditional methods. A Stanford University study revealed that an AI system detected breast cancer with a 94.6% accuracy rate, surpassing the 88% average achieved by radiologists.
Challenges in adopting artificial intelligence in healthcare
Despite the clear benefits of AI, its adoption faces obstacles, particularly regarding data privacy. As AI systems access large volumes of sensitive information, ensuring compliance with laws like the General Data Protection Law (GDPL) requires implementing advanced security measures to protect against unauthorized access and misuse.
In this context, biometrics plays a crucial role. By authenticating users through fingerprint or facial recognition, biometric technology ensures that only authorized individuals can access collected data. This type of authentication also reduces fraud risks and provides traceability of actions within the system essential requirements for the ethical and effective use of AI in healthcare.
According to the 2024 Digital Identity and Fraud Report, online security is one of the population's top priorities, reflected in greater trust in companies that adopt robust digital protection technologies. The report also reveals that 67% of respondents consider biometrics the most secure method.
Biometric solutions are increasingly integrated into the healthcare ecosystem to strengthen system security. One example is BioPass ID, a comprehensive platform for identity verification and authentication. With biometric verification features, BioPass ID precisely controls who accesses healthcare institution information, ensuring full traceability of system actions and compliance with GDPL requirements. Additionally, the technology can be integrated into telemedicine platforms and hospital systems, ensuring proper authentication of professionals and patients.
Biometrics and artificial intelligence applied to healthcare
Another advantage of integrating biometrics and AI is the reduction of errors in medical systems. By using biometric solutions, healthcare institutions can:
- Protect medical records by preventing unauthorized access to data.
- Safeguard hospital pharmacies by verifying the identities of patients and staff.
- Secure clinics and offices by ensuring the authenticity of professionals and patients.
- Reduce prescription fraud by preventing substitution or falsification of medical prescriptions.
- Optimize patient care by improving the efficiency of identity verification processes.
In the coming years, the integration of artificial intelligence and biometrics is expected to expand into new applications, offering innovative solutions for managing and securing patient and provider data.
Artificial intelligence in healthcare and the future of medical care
This article explored the impacts of artificial intelligence on the healthcare sector. Benefits such as enhancing the clinical journey, optimizing resources, and enabling early disease detection stand out. However, challenges related to data privacy and information security remain constant concerns for institutions.
As a solution, biometric authentication technologies, such as facial recognition and fingerprint scanning, provide an additional layer of protection for medical services. Biometrics reduce fraud risks, facilitate action traceability within systems, and ensure that only authorized individuals can access sensitive information.
The combination of AI and biometrics strengthens digital security in the healthcare sector, enabling technological advancements to occur ethically, efficiently, and in compliance with GDPL regulations.
Interested in finding out more? Learn how to reduce healthcare costs with artificial intelligence.
