The application of Big Data and artificial intelligence technologies in the healthcare sector has achieved great advances in recent years at an organisational and healthcare level, with highly relevant innovations for medicine, science and research. With these techniques, it is possible to obtain better diagnoses, better treatments and better lines of research more quickly and easily, with a substantial increase in efficiency, precision and optimisation of resources.
Traditionally, most of the data generated in the healthcare sector is static or structured, such as personal data of a patient (name, surname, age, etc.), laboratory test results, pharmacology, pathologies, etc. All this information can be stored, consulted and analysed easily through different tools and applications, forming part of each patient’s electronic health record.
However, there are other types of highly valuable unstructured information, such as free text notes recorded by professionals during a consultation, medical images (X-rays, scans or MRIs) whose treatment is more complex.
It is in this scenario where Big Data and artificial intelligence are presented as great allies of the health sector, improving the ability to prevent, diagnose and treat health problems.
In order to be able to apply all these techniques effectively, it is necessary to go a step beyond the traditional methods of storing information in the clinical records of the different health services, a scenario in which data lakes offer great potential.
Data lakes are centralised, unstructured and unfiltered data repositories that can be processed with big data techniques. They are highly scalable environments that support extremely large data volumes, accepting data in its native format from a wide variety of data sources. With this we find interesting applications in medical fields, for example:
- Predictive modelling and personalised medicine
- Decision Support Systems (DSS)
- Clinical drug research
- Design of clinical and therapeutic protocols
- Guided treatment choice
The maturity of Big Data technologies, which are being used successfully in other sectors such as banking, transport or telecommunications, invites us to face the challenge of converting the healthcare system into an integrated knowledge ecosystem that allows us to discover unknown factors with a direct impact on health and disease.