Neural Networks at Healthcare

A modern medical facility is equipped with the most advanced technological devices and equipment.

It is much easier to correctly interpret the results and analyze the data obtained when there are automatic systems specially designed for this - artificial neural networks.

● during laboratory tests and screening;
● in endoscopy;
● with electrocardiography;
● in radiology and radiology;
● for monitoring conditions

Of particular importance is the use of neural networks in radiological research. X-ray images processed and analyzed by networks reveal much more pathologies at the earliest stages, which is very important for an early diagnosis and timely treatment.

For example, a doctor can make only a few probable diagnoses from photographs of the patient’s chest, which he sees from his experience in the image. But neural networks compare thousands of similar images of patients from the ones uploaded to the database, compare and analyze. Quickly, clearly and they are not distracted by trifles.

So there is not two or three probable diagnoses, but even more. Since attention is drawn not to one organ or problem, but immediately to the whole picture as a whole.

That is, neural networks are able to see several serious diseases in humans in one ordinary x-ray of the lungs:
● pneumonia;
● tuberculosis;
● rib fracture;
● vertebral hernia;
● retinopathy;
● hemorrhage;
● heart hypertrophy;
● skin lesion;
● collapse of the lung and many concomitant diseases.

With neural networks, diagnosis reaches a new level and significantly improves the work of dozens of medical services, since one study reveals more information than a team of doctors can collect for the entire period of the medical examination.

Early diagnosis and analysis of results by neural networks is a huge help not only to the patient himself on the path to recovery, but also for many therapists, ophthalmologists, oncologists, surgeons, dermatologists, allergologists, cardiologists and doctors of other specialties. For whom it is very important to find the problem at an early stage.

Even for psychotherapists, neural networks are useful, because based on the analysis of medical records and family history, they can track the prerequisites for mental disorders and depression. And, therefore, on time to prescribe and start taking medications, which is able to save the mind of patients.

Not only radiology and images from computed tomography or from an X-ray machine can process neural networks well.

They are also developing well in the field of cardiology, where, according to the results of diagnostics, they put on treatment the treatment of heart and vascular diseases.

The system was developed by Italian specialists, especially for the detection and treatment of hypertension. It is a neural network of three modules, the results of one or two are input data for others.

The Italian system includes three neural network modules, and some answers are input to others.

1) collecting data on systolic and diastolic blood pressure during the day, every 30 minutes, then the results are averaged once every 60 minutes, so that there are only 24 measurements for both types of pressure per day;
2) neural networks process data and produce their result.

As a result, the optimal treatment option and a simple scheme for relieving high blood pressure are formed for the patient.

It is important to note that in this case, when working with a blood pressure measurement, networks take into account not only bare numbers. The calculation also includes:
● age of the patient;
● history (concomitant and chronic diseases);
● condition at the time of analysis (moderate or severe);
● stress factors;
● the presence of pets;
● marital status;
● place of residence or with whom (family, single or in a nursing home).

This is the most accurate and correct approach, since cardiology is not a simple pathology of the heart or vessel, and the general life condition of a person with a similar disease.
The neural network will not be able to draw up the correct schedule for taking drugs if an elderly person lives alone. Since he will not be able to independently track all the medications and keep records of this.

In addition, smart medical neural networks rarely offer a treatment regimen with nightly taking pressure pills, due to difficulties in monitoring and the risk of diuretics at night.

Interestingly, the networks continue to learn and “grow smart” with each new experience and patient. The creators of the program have provided such an opportunity where doctors transmit their knowledge and adjust if the network is wrong.

This approach has helped to significantly improve the situation in the early diagnosis of myocardial infarction.

Modern artificial neural networks diagnose heart and blood vessel problems better than experienced cardiologists by almost 50%.

What about therapy? Same. Liver diseases have become more common in routine laboratory tests and are now more accurate. Studies of the function of the liver and gall bladder using an ultrasound machine, and then analyzed by neural networks are wider and fuller than before.

With the beginning of the use of the neural network, one of the most problematic and urgent tasks for modern medicine has acquired a new meaning - the diagnosis of malignant neoplasms and oncological diseases before it is too late.

For example, monitoring and accurate diagnosis of skin melanoma are now 80% performed by neural networks. And they succeeded in this, since their accuracy is amazing.

Not only complex medical devices, like MRI, ultrasound or CT, are part of the study of neural networks.

Of course, it is important to take high-quality images and analyzes during the examination. But the collection of preliminary data also plays a crucial role.

Such as heart rate, drug or insulin control, pressure measurement, etc.

To do this, you do not have to go to a hospital or clinic. Everything can be controlled at home with the help of modern technologies and applications.


For example, a smart watch with a built-in module for detecting arrhythmias. They are even able to record an ECG and send it to the doctor within hours. Heart rate and ECG results interpret the network.


We summarize why we need neural networks in medicine:
1) to help doctors correctly diagnose and minimize errors in its formulation;
2) for the early diagnosis of serious and dangerous diseases or conditions;
3) for the correct appointment of treatment and the preparation of a suitable regimen for the administration of drugs;
4) for self-monitoring of their health by patients;
5) to monitor the patient's condition and doctor's prescriptions.

Of course, the cars are wrong. Therefore, neural networks continue to learn, develop and become more literate every year.

While humanity trusts networks only a routine, in the form of x-rays and a set of numbers in laboratory analyzes, all this minimizes possible harm to health and is used only for consulting purposes.