Artificial Intelligence (AI) is a specialized branch of computer science that focuses on getting computer systems to mimic human-level thinking. This, at least, is the theoretical aim. At the moment, we are far more satisfied with getting computers to take big chunks of data and derive meaning, learn, and even suggest decisions based on big data and algorithms that train computers to learn and get better at processing large chunks of data.

Over the past few years, the attention on AI has greatly increased. AI powers many systems and gadgets spanning from augmented reality mobile apps to large AI-powered medical applications such as the recent Dr. Watson powered medical diagnostics software.

There is a growing number of AI applications actively improving people’s lives and creating positive change in the world. For years, this has been a very hot topic in the medical industry. Scientists and IT experts have been working on developing AI technologies that could bring significant improvements in the healthcare sector. And they have succeeded.

Let’s take a look at some significant AI contributions in the Medical sector.

AI Expansion in the Healthcare Sector

Some of the most influential companies in the world like Apple, IBM and Google have channeled hundreds of millions of dollars into AI, especially in healthcare.

Google’s research team has high hopes:

“Machine learning has dozens of possible application areas, but healthcare stands out as a remarkable opportunity to benefit people.
Deep learning has already revolutionized the field of computer vision, making practical, in-your-pocket technologies out of what seemed like science fiction just a few years ago. If these new computer vision systems can reach human-level accuracy in identifying dog breeds or cars, we asked ourselves, might those same systems be capable of learning to identify the disease in medical images?”

And Google is putting their money where the mouth is. Google is investing over 30% of its annual venture-capital budget into AI. The money trail is clearly forecasting a future in which AI-powered systems will carry the weight of our healthcare system.

Rank	2013	2014	2015	2016	2017
Rank	2013	2014	2015	2016	2017
1	Enterprise Insights	Enterprise Insights	Enterprise Insights	Enterprise Insights	Enterprise Insights
2	Retail Product Recommendations	NLP / Sentiment Analysis	Retail Product Recommendations	Virtual Assistant	Solutions for Financial Institutions
3	NLP / Sentiment Analysis	Retail Product Recommendations	NLP / Sentiment Analysis	Retail Product Recommendations	Retail Product Recommendations
4	Virtual Assistant	Virtual Assistant	Virtual Assistant	Solutions for Financial Institutions	Virtual Assistant
5	Marketing Analytics	Marketing Analytics	Marketing Analytics	Drug Discovery & Medical Diagnostics	Marketing Analytics
6	Computer Vision	Computer Vision	Drug Discovery & Medical Diagnostics	Biometrics & Facial Recognition Security	Medical Dictation
7	Drug Discovery & Medical Diagnostics	Solutions for Financial Institutions	Solutions for Financial Institutions	NLP / Sentiment Analysis	AR/VR
8	Medical Dictation	Medical Dictation	AR/VR	Computer Vision	Drug Discovery & Medical Diagnostics
9	AR/VR	AR/VR	Computer Vision	Robotics & Autonomous Systems	Biometrics & Facial Recognition Security
10	Biometrics & Facial Recognition Security	Cybersecurity	Cybersecurity	AR/VR	Computer Vision

A deeper look at the table (source) above reveals an interesting fact. Even though Enterprise Insights is the most interesting AI application for years now, it is the Medical field as a combined group, that gets the most investments, especially in 2017.

Although AI could never entirely replace medical professionals, it can totally have a high impact on healthcare. Machine learning can easily improve diagnostics, treatments, and even predict medical outcomes. The most impact AI technologies could have on the healthcare sector is probably regarding the medical history of patients. As AI becomes more sophisticated every day, experts believe that AI even has the potential to save lives.

Many AI gadgets and systems have been developed to help patients and medical professionals in:

• Providing healthcare consultations based on a comparison between patients’ symptoms and data of disease records,
• Predicting possible changes in the body like heart attack, blood pressure, seizures, etc.,
• Determining diagnosis procedures and appropriate treatments for common diseases,
• Improving new medication research,
• Assessing patient’s pain level.

How Can AI Help ER Units With Identity Issues

Although healthcare providers focus their efforts on preventive healthcare systems, it is medical emergencies that continue to claim many lives. For emergency patients, the first phase of the treatment is usually the most important.

The U.S Department of Transportation reported that the number of car accidents with passengers who were unresponsive to ER’s treatments is massive. To add up to the problem, in a crisis situation, it is very difficult to quickly find the personal identification of the patient.
In life-threatening situations like these, which, unfortunately, are not rare, another major problem is slow access to a critical medical background of the patient.

The inability of ER units to identify the patient and their medical history when the patient is unresponsive can cost that person’s life.

Having a face recognition technology that can identify the person in question and provide a list of medical history in situations like these, enables paramedics to treat the patient properly, and quickly. Such technology could indeed save lives.

How Face Recognition Technologies Work

Every person has several distinguishable characteristics that constitute their unique facial features. Such as:

• The distance between the eyes,
• The shape of the cheekbones,
• The depth of the eye sockets,
• The length of the jawline,
• The width of the nose…

The facial recognition technology operates by detecting a face and then measuring these unique facial features. These measurements are combined to produce a quantifiable numerical code that is used in the facial recognition process.
Unlike other biometric technologies like voice recognition, iris recognition, and fingerprint scanning, face recognition has several key advantages:

• Face recognition is easy to use thanks to smartphones ability to take solid photos and run apps that can send and receive data to a central repository
• It does not require the unknown person to be able to communicate
• It does not require a physical contact with the person.

There are already many face recognition systems used by law enforcement, transportation, and other security-oriented organizations. So there is plenty of technology on the market that makes face recognition industry to provide very affordable solutions.

How ER Units Would Use AI & Face Recognition Technology

A simple, easy to use application for face-recognition that is connected to a Medical Records System can offer paramedics critical, timely details needed for the right treatment.

This app could provide details such as previous treatments, any known allergic reactions to common medication, possible alcohol abuse and dependence, dementia, epilepsy, multiple sclerosis, psychiatric disorders, etc.

Patient registration could be done by the patient’s Primary Care Physician (PCP). All patient medical information would be stored in a centralized, encrypted national database. During the registration process, patients could be photographed, and this photo would become part of their medical record.
An access-level management system would make this information accessible only for authorized persons, on a need-to-know basis. The data could be accessible normally by medical staff through any internet-enabled device.

To identify the patient and find their medical record, paramedics would use their smartphone. The camera would scan the patient, and the app would send the data through an encrypted channel for processing and match-making.
The centralized database of faces would find the best match. Paramedics would determine which one is the patient, in case if there are several close matches.

After positive identification, the paramedic would have access to the needed patient’s medical history details, as allowed by the access level rights system.

This crucial information can be a life-saver for a patient who has a known medical condition but is unable to communicate with the paramedics.

This system would be affordable, reliable, and easy to use (capture, store, access and retrieve medical information).

Last Thoughts

AI is continuing to power systems that are creating positive change in the world. Many large and established companies are investing millions of dollars in AI. And the most vibrant use AI, according to investments alone, seems to be the healthcare sector.

Considering that such a simple AI application as a smartphone app can save lives, automatic face recognition has become an important part of the next generation of computing technology.

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