Surgery Risk Prediction

What if we can predict and choice our surgery date?

People visit the hospital when they have problems with their bodies. Medical staff prescribe various prescriptions to patients and, in some cases, proceed with surgery. Patients who have undergone surgery fully recover and return to their daily lives after surgery, but some patients have problems after surgery, so they visit the hospital again and proceed with secondary treatment.

This study analyzes the causes of these postoperative secondary problems, namely the occurrence of Surgical Site Infection(SSI).

Risk Factor Analysis

"Will the higher the number of doctors who participated in surgery, the higher the SSI rate?"

"Will the longer the operation time, the higher the SSI rate?"

We want to analyze the correlation between the surgical environment in the hospital as above and the SSI rate to derive the results of which environment the SSI rate is high.

"Which day of the week would perform surgery have a high rate of SSI?"

"Will the higher the temperature and the higher the humidity, the higher the SSI rate?"

We intend to analyze risk factors not only for the surgical environment in the hospital but also for the environment outside the hospital. It analyzes the correlation of SSI occurrence according to the weather on the day of surgery and the weather after discharge after surgery.

Surgery Date Prediction

"It is recommended that three doctors participate in the operation."

"It is better to proceed with the surgery next month rather than this month."

In the case of weather, it informs people of future changes in advances so that they can prepare in advance. Similarly, we intend to develop a model that can predict ans inform them of which day the SSI incidence is the lowest to perform surgery. To this end, we derive the surgical environment with the lowest SSI incidence through the above risk factor analysis, and develop a model that predicts the optimal surgical date through time series data combined with it.