Machine Learning Helps to Control Diabetes

By Hubert Yoshida posted 03-20-2018 00:00


There is a good probability that you or someone you know has diabetes. The World Health organization believes that an estimated 8.8 percent of the adult population worldwide had diabetes. This figure is projected to rise to 9.9 percent by the year 2045. Type-2 diabetes is the most prevalent form of diabetes and affects more people as the population ages. Today one in every four Americans, 65 years or older has Type-2 diabetes. The spread of Western lifestyles and diet to developing countries has also resulted in a substantial increase.


Diabetes is a chronic, incurable disease that occurs when the body doesn't produce any or enough insulin, leading to an excess of sugar in the blood. Diabetes can cause serious health complications including heart disease, blindness, kidney failure, and lower-extremity amputations and is the seventh leading cause of death in the United States. Diabetes can be controlled by medication, a healthy diet, and exercise.

The problem with medication is that there are many ways to treat the disease with different combinations of drugs. Some medications breakdown starches and sugars, others decreases the sugar your liver makes, some affect rhythms in your body and prevent insulin resistance, others help the body make insulin, still others control how much insulin your body uses, some prevent the kidneys from holding on to glucose, and others help fat cells to use insulin better. New medications are being developed continuously as the population of diabetics increases.  Diabetics often need to take other medications to treat conditions that are common with diabetes like heart health, high cholesterol, retinopathy, and high blood pressure. The efficacy of the drugs changes with the patient's age and other physical factors. There are also different side effects depending on the individual’s situation, and the drugs can be expensive. The effectiveness of the treatment is measured every three months by a blood test for a measure called A1C. A1C measures the average blood glucose level for the last 3 months. An A1C measure of 7.0% indicates that the blood glucose level and the diabetes are under control. However, 7.0% is an ideal reading and higher readings may be acceptable depending on the individual. Up to now the prescription of medication is usually a trial and error approach and more than half of diabetes patients fail to achieve the treatment targets according to the World Journal of Diabetes. The selection and monitoring of the most effective medication or combination of medications that is also safe, economical and better tolerated by patients is often hit or miss.

On March 12, Hitachi and the University of Utah Health, a leading institution in electronic health records and interoperability clinical information systems research announced the joint development of a decision support system that allows clinicians and patients to choose pharmaceutical options for treating type-2 diabetes. The system uses machine learning methods to predict the probability of a given medication regimen achieving targeted results by integrating with electronic health records which allows for guidance that is personalized for individual characteristics.


The system compares medication regimens side-by-side, predicting efficacy, risks of side effects, and costs in a way that it is easy for clinicians and patients to understand.


Using Machine learning combined with the individual’s individual health records will increase the probability of selecting the right combination of medications that will help individuals reach their targeted goals to control diabetes. Think how this could be applied to other treatments like chemo therapy for cancer. If you know anyone with diabetes please forward this post to them so they can understand what is possible when you apply machine learning to the control of this disease.