Using Machine Learning To Provide Solutions To Business Problems

Using Machine Learning to Provide Solutions

Using Machine Learning to Business Solutions

Machine learning is finding its way into every aspect of computing from social media to complex financial applications. Machine learning can be used to enhance the customer experience, better handle and predict results from complex data, and even transform the way different businesses can operate. Being able to correlate data to detect patterns and anomalies can help an organization predict outcomes and improve operations. There are numerous examples in almost every industry.

Applying Machine Learning to Patient Health

One of the biggest problems in treating patients is that drugs often affect individuals differently. Some medications may cause terrible side effects for one patient while being an effective treatment for a different patient. A patient may have additional medical conditions that may cause a reaction to a treatment. Age and gender may also impact the effectiveness of a drug. Too often physicians have to resort to trial and error to find the right treatment.

One solution to selecting the most effective treatment is to build a machine learning model based on classification and regression algorithms. The classification model is needed to predict the impact of the drug based on known results from patient tests and conditions. The regression model is then used to predict the changes in the patient’s condition when she takes a certain drug. Creating this model by using data helps provide researchers with an understanding of how a population of patients historically reacts to various drugs. As the model is built and trained, it will be able to determine the probability that a certain drug will be most effective for a patient.

If the model is online, it will continue to evolve as more patient data is added. A solution can be built to include a conversational interface using cognitive Application Programming Interfaces (APIs). In this way, a physician can interact with the model and ask a variety of questions to ensure that the right treatment is provided with fewer side effects.

Leveraging IoT to Create More Predictable Outcomes

Machine learning models are an ideal application for the Internet of Things (IoT). The first thing to understand about analytics on the IoT data is that it involves data sets generated by sensors. These sensors are now both cheap and sophisticated enough to support a seemingly endless variety of applications. The data generated by sensors contains a specific structure and is therefore ideal for applying machine learning techniques. While the data itself is not complex, there is often an enormous amount of data produced. By using this sensor data, along with known outages, machine learning algorithms can build models to predict future mechanical problems. The model would include data about the optimal indicators of a baseline of a well-run machine as well as data points the preceded a failure. As the model is trained, it will be able to determine anomalies that will predict the potential for failure.