In the healthcare sector, we have investigated and studied methods to treat diseases after they manifest, with the aim of creating a drug or treatment to do so.
However, when AI is used in healthcare, we can use machine prediction power to identify diseases even before they manifest.
The shift in perspective from treating diseases once they have manifested to using AI to prevent diseases before they occur is the future of health.
Benefit 1: Improving efficiency and accuracy of the diagnostic process
- Predictive analytics
Fact: Every year, people receive incorrect diagnoses, which can result in further errors because, even if you switch healthcare providers, your previous medical records—which can be unreliable—are used by doctors.
AI in healthcare, for example, benefits the diagnostic process, improving the effectiveness of the entire course of treatment. Machines (AI) consider a lot more information than humans can, enabling accurate disease diagnosis before overt symptoms start to have an impact.
Use case: For instance, using eye images as the foundation for diabetic retinopathy tips.
Benefit 2: Improving the patient experience (journey)
- Personalized medicine
The speed with which a patient receives care when it is most needed is critical.
Fact: People complain when there are lengthy waits for the necessary medical care, and people pass away while waiting for the care they most urgently need.
AI brings these platforms to a new level. Patients can use apps that offer real-time health monitoring to check their condition without going to the doctor. Patients can communicate with doctors through medical platforms that shorten wait times in lines.
This has a powerful effect on the overall patient journey. Patients who engage in shared decision-making are more trusting of their physicians. They’re also better educated, which is another key component of the patient's journey.
Benefit 3: Speeding up medicine development
- Drug discovery
Fact: Research has shown that a challenging part of the approximately X billion dollars assigned to drug development is lost irrevocably due to testing, errors, and regulations.
Examples of AI in medicine analyze enormous amounts of data to speed up the development of medical technology. Smaller AI-driven startups are sought-after by pharmaceutical companies because they can identify untapped markets and new avenues for drug development.
Use cases of AI in healthcare can be applied to every stage of drug development, including:
- Reduce the costs of the research.
- Preventing human error and verifying that calculations are accurate.
- Identify critical areas that require improvement and necessary action.
By maintaining a position of intermediary between hospitals and other mediums that will produce analytics and predictions to support the points mentioned above, Datatera Technology is designed to break down silos and ensure that all data and knowledge sharing does not just remain with a single data provider, such as a hospital, but can also result in a variety of products and projects for scientific purposes.