The medical field continues to evolve through the era of sterile techniques and antibiotics to the development of advanced imaging modalities into the last decades embrace of big data and informatics. Each advancement has taken time to be fully implemented in medical care, however, each iteration has improved patient outcomes over the last century. I believe the next evolution in medicine lies in the integration of artificial intelligence and machine learning with patient outcomes data. With more physicians seeing more patients and documenting encounters and results on electronic medical records, a plethora of data is being collected daily by hospitals and clinics around the country and even the world. It will be impossible for humans to sift through all these data points to draw conclusions, however, AI will provide an avenue through which patient care and outcomes can be studied in a comprehensive and specific manner to draw inferences with statistical power. I completed a research project at the Brownsville Community Health Center where I created a database to study risk factors and the management of patients with T2DM and their respective HbA1C levels. This experience brought to light actionable goals in patient care and highlighted the need for more robust data mining and the need for algorithms to automate the data collection and analysis. However, AI will not replace the need for caring physicians who can take the analyzed data and develop care plans tailored to their communities and to their individual patients.
Lakshman's Blog 