Using Big Data to Transform Laboratory Medicine

Arturo Weschler, Medial Research, Israel, Israel

Laboratory medicine has generated a huge amount of data (“big data”). The combination of massive quantities of historic laboratory data with clinical data stored in EMRs hold the promise of transforming laboratory medicine.

New ways for laboratory results interpretation and the generation of new algorithmic analytes based on the application of complex mathematical models on panels of laboratory results are just two examples of how big data analytics is changing the practice of laboratory medicine.

Laboratory results interpretation: We will discuss the transformation of laboratory results interpretation from standardized one fits all approach into a personalized predictive methodology. We will present clinical examples derived from our current projects to elucidate the approach.

Creation of algorithmic analytes: We will discuss the use of low-cost and readily available blood tests results and EMR data to simultaneously calculate risk scores for multiple types of cancers. The use of MeScore CRC, a calculated personal risk score for population-based early detection of colorectal cancer will be explained.

Laboratory medicine has generated a huge amount of data (“big data”). The combination of massive quantities of historic laboratory data with clinical data stored in EMRs hold the promise of transforming laboratory medicine.

New ways for laboratory results interpretation and the generation of new algorithmic analytes based on the application of complex mathematical models on panels of laboratory results are just two examples of how big data analytics is changing the practice of laboratory medicine.

Laboratory results interpretation: We will discuss the transformation of laboratory results interpretation from standardized one fits all approach into a personalized predictive methodology. We will present clinical examples derived from our current projects to elucidate the approach.

Creation of algorithmic analytes: We will discuss the use of low-cost and readily available blood tests results and EMR data to simultaneously calculate risk scores for multiple types of cancers. The use of MeScore CRC, a calculated personal risk score for population-based early detection of colorectal cancer will be explained.