One of the major explanations for this exponential growth is the existence of incredible amounts of medical data in the form of patient clinical information, such as insurance data, diagnosis data, lab results, and R&D data like ones from clinical trials and published papers.
There are numerous instances where big data can be applied in healthcare, from enhancing patient engagement to informing strategic planning and from reducing fraud cases to enhancing security. The goal of AI in healthcare is to assist doctors in making data-driven decisions within seconds and improving the treatment of patients.
This is especially true for patients who have a complicated medical history or are suffering from multiple conditions. For instance, through evaluation, doctors can identify patients who are candidates for laparoscopic gallbladder removal (cholecystectomy) and those who aren’t. Doctors use the patient’s current and past medical information and compare them with other patients data in their databank in real-time, to help come with conclusions.
Widely speaking, there are five significant benefits of predictive analysis in medicine; and are as follows; Help pharmaceutical firms meet the public needs. The pharmaceutical industry is going to be one of the greatest beneficiaries of predictive analytics soon, as it will provide precise, more evidence-based speculation about the disorders and diseases that are likely to affect many people.