How to Handle Urgent Care Situations When Traveling

Sometimes, when we least expect it, we find ourselves looking for an urgent care facility on the road, out of town, or even across the country. Finally taking that dream road trip to the Grand Canyon? Nobody ever expects food poisoning from that adorable roadside diner. Taking your kids to the regional soccer championship? Where should you go when a sprained ankle spoils the game?

It can feel like enough of a challenge to remember all of the electronics chargers, to fit the sneakers into the suitcase, and to remember to put all of those little toiletry bottles in a separate plastic bag for airport security. If you haven’t put together a first aid kit for your car or suitcase, schedule some time to put one together scraping google. When a big scrape happens, and you need to head to urgent care for a few stitches, you’ll be glad to have cotton pads and gauze on hand right away.

When the flu sets in on the first day of that three-day beach weekend, and you Google the urgent care facility in your area, be sure to check their website or call ahead, because you’ll need to be sure that the clinic is open and that you can arrive without scheduling an appointment ahead of time. Talk to someone on the phone at the center to make sure that the place you’re planning to go is equipped to specifically address the particular type of injury or illness for which you’re seeking treatment.

If you’re headed to urgent care during a time of day during which your primary care doctor is in his or her office, place a phone call or contact your physician to alert them to your situation. If that minor injury takes place outside of your primary care doctor’s office hours, then let him or her know at the next opportunity. You may choose to see your primary care doctor for follow-up care, or you may choose to return to the urgent care clinic for a follow-up appointment. That decision will be up to you and the doctor who treats your minor injury, and you can discuss it with them during your treatment.

Numeric forecasting seems to be the most well known area here. For a long time computers were actively used for predicting the behavior of financial markets. Most models were developed before the 1980s, when financial markets got access to sufficient computational power. Later these technologies spread to other industries. Since computing power is cheap now, it can be used by even small companies for all kinds of forecasting, such as traffic (people, cars, users), sales forecasting and more.

Anomaly detection algorithms help people scan lots of data and identify which cases should be checked as anomalies. In finance they can identify fraudulent transactions. In infrastructure monitoring they make it possible to identify problems before they affect business. It is used in manufacturing quality control.

The main idea here is that you should not describe each type of anomaly. You give a big list of different known cases (a learning set) to the system and system use it for anomaly identifying.

Object clustering algorithms allows to group big amount of data using wide range of meaningful criteria. A man can’t operate efficiently with more than few hundreds of object with many parameters. Machine can do clustering more efficient, for example, for customers / leads qualification, product lists segmentation, customer support cases classification etc.

Recommendations / preferences / behavior prediction algorithms gives us opportunity to be more efficient interacting with customers or users by offering them exactly what they need, even if they have not thought about it before. Recommendation systems works really bad in most of services now, but this sector will be improved rapidly very soon.

The second point is that machine learning algorithms can replace people. System makes analysis of people’s actions, build rules basing on this information (i.e. learn from people) and apply this rules acting instead of people.

First of all this is about all types of standard decisions making. There are a lot of activities which require for standard actions in standard situations. People make some “standard decisions” and escalate cases which are not standard. There are no reasons, why machines can’t do that: documents processing, cold calls, bookkeeping, first line customer support etc.