Converge of Data Science and Laboratory Medicine
Author Information
Author(s): Nieto-Moragas Javier, Marull Arnall Anna, Calvo Boyero Fernando, Martin Perez Salomón, Marqués García Fernando, Hernando Redondo Javier, Blanco Grau Albert, Cauqui Lende Cristian, Molina Borrás Ángel, Prieto Arribas Daniel, de Rafael González Elena
Primary Institution: SEQCML Data Science Working Group
Conclusion
The integration of data science into laboratory medicine is transforming healthcare systems towards personalized precision medicine.
Supporting Evidence
- Data science tools help extract relevant information from complex data.
- Interest in data science applications in laboratories has grown since the COVID-19 pandemic.
- Laboratory professionals are increasingly collaborating with computer scientists.
- New technologies in laboratory medicine require strong analytical skills and creativity.
Takeaway
Data science helps doctors understand and use large amounts of information to make better decisions about patient care.
Potential Biases
Potential biases and errors in implementing new technologies need to be addressed.
Limitations
The adaptation process faces challenges that require healthcare managers to support the integration of new technologies.
Digital Object Identifier (DOI)
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