The beauty of our time is that medical advancements have seen huge leaps and bounds in the past few decades. There are a plethora of Cases of Machine Learning in Healthcare which all point to the fact that technology and healthcare go hand in hand now and it is almost impossible to have healthcare without technology tagging along. As time goes on, machine learning will require less and fewer data and information in order for it to learn and adapt to whatever system it’s operating in. Thus, there will be systems that can learn much faster with significantly smaller data sets and these systems will be more sophisticated than what is available now. Some of the Cases of Machine Learning in Healthcare came into being only a few years ago or maybe two decades ago. As such, there are several machine learning trends in not only the healthcare industry but in other industries as well. Let’s discuss some of these trends below.
Machine Learning in Cyber Security
The use of machine learning to help revolutionalize cybersecurity is one that has turned a lot of heads. Cybercrime and data breaches have been a bone of contention for many large companies and with machine learning, they can reduce and even eliminate the occurrences of data breaches or data theft. Machine learning helps improve data security by monitoring, securing and responding quickly to data storage and data access issues. So in conclusion machine learning helps to add extra layers of prevention and protection against DDoS attacks, data breaches, data theft and much more.
Machine Learning in Customer Support
The customer service industry is always looking for ways to improve and is always looking to adopt new technology that can help serve customers better. With machine learning, there are more improved options for technology that can help with customer service. Some of these options are chatbots and automated responses or automated phone call responses. The machine learning software can answer a call and through the training, it has received, be able to respond correctly to the questions and prompts of the human caller. The machine learning can understand user queries better and with each new query or a new type of wording the machine stores it and learns from it thus making it more and more human like the longer it runs. Google has had some advancement in this area with technology that can make calls for an individual and make phone appointments like at a salon or a restaurant reservation.
Machine Learning in Search Engines
Search engines are already pretty smart and can provide search results in as quickly as milliseconds. Machine learning helps to improve search engines by learning something new every time a new type of search query or sentence wording is used in the search bar, thus making the search results more and more accurate and specific each time. In addition, the machine learning algorithms keep watching for how people respond to the search results and then they start to use that information to improve the search each time. This is big in SEO (search engine optimization). Websites struggle to have the most relevant content so they improve their search result ranking and so people spend more time on their pages. When people search for a term and then click on their site, the better the content, the longer they stay on the page and this tells the search engine machine learning algorithms that the site is a good search result for that term and so they keep it on and even rank it higher than before. On the other hand, if the result is rarely clicked on or people click on it and quickly exit, the machine learning search engine algorithms will view it as a bad search result for that search term and they will stop to provide it or put in on the first page.
Machine Learning in Product Recommendations
E-commerce companies love this functionality of machine learning. With machine learning being used on a product website, users can get recommendations for products based on their past purchases or based on the products on the website that they viewed, liked, saved, or showed any kind of interest in while browsing. This makes the shopping experience more refined and it also means more sales for these e-commerce websites. Some machine learning programs can even be programmed to send customers prompt emails to finish their purchase or to email them when there are new products in the store.
Machine Learning in Fraud Detection
Machine learning in fraud detection can be seen as another type of cybersecurity as it helps keeps fraudulent activities and fraudulent people out of the system it is meant to protect. Thus, when there is a suspicious activity that may go unnoticed to the human eye, machine learning helps to identify these activities and warn the monitoring bodies. It can also be programmed to take other actions like luck down a system after a threat has been spotted or prevent further access.
Machine Learning for Video Surveillance
Machine learning is used in video surveillance not only by security companies but by any company or individual that has a great interest in security. Thus machine learning us used to not only record videos but to notice suspicious activity and take action. The systems can track unusual behavior and even in advanced situations run real-time facial recognition on suspects to help apprehend them. This technology further improved can be used by security agencies both government and private and will have many different and useful applications.