Every industry has been striving towards automation and applying innovative strategies to their business to gain maximum profitability and success. Data science is being used by varied industrial domains, but its usage in the healthcare sector has drastically transformed the overall healthcare ecosystem.
Traditionally, we only relied on the doctor’s manual prescriptions which were suggested by questioning or assuming our symptoms. This led to a wrong diagnosis and thus wrong prescriptions leading to complications. The introduction of data science has changed the way we perceive this case, now the advanced tools and techniques are used to derive an accurate diagnosis with the least human errors. With the advancement of data science in healthcare, medical professionals need to familiarize and upgrade their skills concerning data science, machine learning, artificial intelligence, business intelligence, virtualization, big data, and more.
Fields using data science in healthcare
Data science is been used in various fields in the healthcare industry. We will focus on diagnosis, disease prevention, patient monitoring, drug discovery, and virtual assistance.
Data science has played a significant role in the field of medical diagnosis which has helped to accurately interpret images of X-rays, CT scans, MRI, and mammography. This helps to detect the microscopic details that could have missed from the manual examination by any medical professional. This helps to reduce the misdiagnosis leading to wrongly prescribed medicines. According to BBC
, there are 40,000 to 80,000 cases of deaths in the US reported annually due to the diagnostic errors. (Dusenbery). Data science plays a major role in detecting tumours, irregular heart rhythms
, organ anomalies, and cancers through accurate data-driven models. (Pranav Rajpurkar). Data science and Big Data have been used to research in genomics which means to derive results about how a certain drug is used and reacts in treating a genetic disorder.
Data science plays an important role to detect and alerts well in advance about a potential disease. It makes use of predictive analysis to detect and prevent various chronic and auto-immune disease at an early stage. The predictive analysis uses the patient’s history to derives meaningful predictions by correlating their symptoms, habits, and diseases. The predictive analysis model also helps to optimize costs in healthcare. Since the disease is diagnosed at an early stage, it requires less cost for treating it as compared to advanced stages. Companies like IQuity are using data science and machine learning techniques for treating autoimmune diseases.Visit Site