When we hear about algorithms or Machine Learning, the first things that often come to mind are the tech world: search engines, Netflix recommendations, or online advertising. But in reality, these tools are already being applied across a wide variety of fields—from medicine to logistics, sports, and even real estate.

The key lies in their ability to learn from data and detect patterns that often go unnoticed by the human eye. With that foundation, algorithms not only help make better decisions, but also open the door to predictions that were once unimaginable.

Imagine that, just as a doctor can estimate a patient’s survival based on multiple variables, an algorithm could predict how long it will take for a house to sell and which factors influence that process. This isn’t science fiction: it’s exactly what a team of researchers at the Indiana University-Purdue University Indianapolis School of Science has achieved.

Their work shows how techniques originally designed to estimate the survival of patients with serious illnesses can be adapted to answer a key question in the housing market: what is the probability that a property will sell in one month, two, three, or more?

This type of breakthrough demonstrates that algorithms are versatile and that their applications transcend sector boundaries. Today, they help sell homes; tomorrow, they could optimize transportation routes, anticipate energy demand, or even design better sustainability strategies.

To learn more about how this research was carried out and its impact on the real estate sector, read the full article here:
Waiting to be sold: researchers develop model to predict probability of home sales