Approved Research

Detecting individuals who are at risk of developing lifestyle diseases.

Lay summary

Our project at Labonovum B.V. applies machine learning in preventive health care in order to identify and notify individuals at risk of developing some lifestyle disease like diabetes type 2, Cardiovascular disease, obesity, Chronic obstructive pulmonary disease, osteoporosis, and asthma. We are also interested in detecting asymptomatic individuals who already have one of the previously mentioned diseases.

We believe that it is of great importance to detect those individuals at early stages of illness the earliest possible.

If they are at risk, our goal is to prevent the incidence of the disease later in life. If they are asymptomatic, our goal is informing them so they start treatment before their illness reaches a more severe stage.

Our motives are to reduce workload on doctors, reduce expensive healthcare costs, and increase the longevity and quality of life of individuals. Doctors in the Netherlands are facing a huge workload as there are not enough general practitioners. We contribute to decreasing that workload by reducing the number of lifestyle diseases patients, especially that those diseases are very much widespread. By preventing the incidence of those diseases, we reduce their treatment costs which are high. One of our motives is to impact public health in a helpful manner. Lifestyle diseases negatively impact the quality of life of patients as they are forced to go to the emergency room or visit doctors more often. We save our patients from suffering a poor lifestyle or even from death. The WHO (World Health Organization) estimates that 80% of premature deaths from cardiovascular disease and diabetes could be prevented by controlling of their risk factors. We conclude that our project increases longevity and quality of life of the public.