TR2021014071A2 - AI-SUPPORTED ELECTRONIC DIAGNOSTIC DEVICE FOR DISEASE DIAGNOSIS - Google Patents

Abstract

The invention relates to a diagnostic device that can diagnose Covid-19 and similar infectious diseases by analyzing breath data by using artificial intelligence modules that have previously learned.

Description

DESCRIPTION AI-SUPPORTED ELECTRONIC DIAGNOSTIC DEVICE FOR DISEASE DIAGNOSIS TECHNICAL FIELD The invention is made with an artificial intelligence supported device that can diagnose Covid from breathing data in general. KNOWN STATE OF THE TECHNIQUE With the impact of the Covid-19 pandemic, public health has gained importance at all levels and contagious and each individual has begun to take care to reduce the risk of disease. Mask. distance and With hygiene protection and complete closure that sometimes stops life, contamination is prevented. has been studied. It seems that the effects of Covid-19 will continue for a long time.

It is difficult to determine whether people infected with Covid-19 are sick. airplanes, To control people entering and exiting public and closed areas such as schools, hospitals and this control also needs to be reliable. The person's carrier of the disease with a quick test It is important to immediately determine whether

In the current technique, PCR-based methods are used to diagnose Covid-19 and similar diseases in individuals. diagnostic kits have been developed. These kits have a long diagnostic time. In a short time The reliability of rapid diagnostic kits is also low by giving results. In addition, the patient's throat and nose Methods such as taking a swab from it disturb the patient and complicate the process.

In the study titled 'Detection System', the general illness of the passengers within the airline system A solution with control is provided. Invention, on the other hand, is both individuals alone. Covid-19, which companies can use and which companies in every branch of the industry can apply. offers an electronic nose product that can detect similar infectious diseases. In the study titled 'detecting plasmodium infection', the disease caused by the plasmodium parasite was New compounds that can detect diseases such as These compounds cause the disease to be easily and they are able to detect quickly; only in the laboratory environment and by experts. should be used by The invention means that covid and similar infectious diseases are fast and high. It is a tool that can be used both personally and on a large scale, which ensures its accurate detection. recommends the product.

System and methods with patent number CN102378981A, which is in the state of the art sensors in the study titled for health monitoring of anonymous animals in Iivestock groups' A system that enables the determination of the diseases of poultry and barn animals with the help of has been suggested. In the study, data such as the temperature, weight, and sounds of animals were used by sensors. and diseased ones were determined by the system. In the invention only It is a device that can detect Covid-19 and similar infectious diseases in humans with breath data. device is provided. electronic nose management in personal devices' It is a system that enables different sensors and electronic nose devices to be managed from a central place. system is presented. This system does not focus on any disease or problem; It deals with the processing and interpretation of data obtained from a large number of devices. takes. The invention, on the other hand, has been trained with a large number of patient data and is specifically designed for Covid-19 and similar recommends a device that can detect diseases with high accuracy.

As a result, improvements are made in diagnostic devices, therefore, the above-mentioned new structures that will eliminate the disadvantages and bring solutions to the existing systems. is needed.

OBJECTIVE OF THE INVENTION The present invention satisfies the above-mentioned requirements, eliminates all disadvantages. relates to a diagnostic device that removes

The main purpose of the invention; Artificial diseases that have previously learned about C0vid-19 and similar infectious diseases A device that can be diagnosed by analyzing breath data by making use of intelligence modules is to provide.

With the invention, it has the feature of diagnosing different gas sensors by competing with each other. By updating itself, a device is provided that can be competent for different diseases.

With the invention; - will self-sterilize by trapping dirty or pathogenic air - Can be used in crowded indoor or outdoor areas - will be able to diagnose very quickly and give the probability of this as a percentage o be able to work with any machine learning algorithm it will be able to sterilize itself automatically A device is provided.

The structural and characteristic features of the invention and all its advantages are given in the following figures and More clearly thanks to the detailed explanation with references to the figures. will be understood.

BRIEF DESCRIPTION OF THE FIGURES The embodiment of the present invention and the best use of its advantages with additional elements In order to be understood, it should be evaluated together with the figures explained below.

Figure 1: The schematic view of the diagnostic device of the invention REFERENCE NUMBERS . blow stick . blowing funnel . oxygen sensor . CO sensor . CO2 Sensor . hydrogen sensor . nitrogen sensor OCJWIOÜCJW-I>›CJLJI\J-` . Argon sensor . Helium sensor . ozone sensor . methane sensor . Krypton sensor . xenon sensor . nitrogen oxide sensor . Digitization module . Learned module . Learned module update piece 18. LCD mini display 19. Mini fan . air outlet pipe 21. UV light 22. Balloon insertion tube 23. Balloon 24. Bluetooth connection . USB connection 26. WIFI Connection 27. Mini USB connection 28. Update Module (In another computer) 29. Power battery DETAILED DESCRIPTION OF THE INVENTION In this detailed description, preferred embodiments of the inventive diagnostic device are only for a better understanding of the subject and will not have any limiting effect is explained in the following.

Figure 1 shows the schematic view of the diagnostic device, which is the subject of the invention.

The person who will be using the device should move towards the inside of the device from the blowing rod (1) or the blowing funnel (2). blows air. Oxygen sensor (3), C0 sensor (4), C02 Sensor (5), Hydrogen in the device sensor (6), Nitrogen sensor (7), Argon sensor (8), Helium sensor (9), Ozone sensor (10), Methane sensor (11), Krypton sensor (12), Xenon sensor (13), Nitrogen oxide sensor (14) They measure their part in the air entering the interior. Each sensor measurement sends it to the digitization module (15).

The digitization module (15) measures the incoming measurements, the difference of each value with the other value, Calculate the square, the Ioarithm, the sum of the squares of the differences between the Ioarithms, by calculating creates separate variables. These variables are related to the numerical values of the air in the environment. smoothed out. Smoothing New Min-Max, Z-Score, Logarithmic, Exponential One or more of the smoothing methods are used. Digitization module (15), transmits the data it produces to the learned module (16). Learned module (16) LSTM, XBOOST, Logistic Regression, linear regression, gradient decent boosted tree, Artificial Neural Networks. Probabilistic Neural Networks, Bayes Nayev learning, Bayes Nayev Networks, Random forest, Adaboost, C4.5, ID3 trained with algorithms. is a module. Learned module (16) includes one or more of all algorithms and all data. predicts the diagnosis of the disease as previously learned. Learned module (16) It is a module that can be updated and new algorithms can be loaded. Learned module (16); to computer via bluetooth (24), USB (25), wifi (26), Mini USB connection (27) can connect and use the update program on the computer.

Update module 28; smart mobile phone, tablet, computer, windows, linux, mac os, android is a software that can run on IOS operating systems. Update module (28) specific checks for new learning updates from the center at intervals. In this way, different can easily diagnose diseases. Device update module at any time It is updated by connecting to (28). LCD mini screen (18) writes the diagnosis of the device with probability value.

The LCD mini display (18) shows which disease or diseases it has been diagnosed with. Mini fan (19) It ensures that the air is filled into the balloon (23) after it is placed.

The air outlet pipe (20) provides communication with the balloon placing pipe (22). air outlet pipe (20) allows some of the air to pass into the balloon (23) during blowing. positive diagnosis When placed, the mini ventilator (19) removes all the air, the air outlet pipe (20) and the balloon insertion. sends it into the balloon (23) with its tube (21). The blown air is inside the balloon (23) The reason for the confinement is that the possible positive patient breath is in contact with the outside environment or the person holding the instrument. to prevent it from happening. After the air is sent into the balloon (23) the air outlet pipe (20) It closes the cap and traps the air in the balloon (23). The balloon insertion tube (21) turns The balloon (23) bends its mouth and prevents the passage of air. UV light (21) active after each treatment and sterilizes the air inside. Air outlet tube (20) when diagnosed negative it expels the air with the help of the mini fan (19). Air outflow even when a negative diagnosis is made tube (20) can trap air inside the balloon (23) as a precaution. The power battery (29) is attached to the device. It provides electrical power, works in the range of 12-40 volts. The power battery (29) is a rechargeable is in the structure.

Claims (1)

REQUESTS . It is a diagnostic device and its feature is; At least one blow bar (1) or blow funnel (2) to help the person who will use the device blow air into the device, At least one Oxygen sensor (3), C0 sensor (4), (302 Sensor) to analyze the air blown into the device ( 5), Hydrogen sensor (6), Nitrogen sensor (7), Argon sensor (8), Helium sensor (9), Ozone sensor (10), Methane sensor (11), Krypton sensor (12), Xenon sensor (13) , Nitrogen oxide sensor (14), At least one digitization module (15) that creates separate variables by calculating the measurements from the aforementioned sensors, the difference of each value with the other value, the square of the difference, the logarithm, the sum of the squares of the differences between the logarithms, ) at least one learned module (16), which can be updated and new algorithms can be loaded, predicts the diagnosis of the disease as it has learned before by taking the data it produces module (28) At least one mini ventilator (19) that ensures the homogeneous distribution of the air blown into the device in the device, At least one balloon (23) in which the air is trapped after the diagnosis and thus prevents the people in the environment from being affected, It becomes active after each procedure. passes through and contains at least one UV that sterilizes the air inside. . It is a diagnostic device according to claim 1, its feature is; It comprises at least one air outlet pipe (20) and a balloon placing pipe (22) that allows some of the air to pass into the balloon (23) during blowing. . It is a diagnostic device according to claim 1, its feature is; said learned module (16) includes at least one bluetooth (24) in order to be able to connect to the computer and use the update program on the computer. . It is a diagnostic device according to claim 1, its feature is; said learned module (16) includes at least one USB (25) to enable it to be connected to the computer and to use the update program on the computer. . It is a diagnostic device according to claim 1, its feature is; said learned module (16) includes at least one wifi (26) in order to be able to connect to the computer and use the update program on the computer. . It is a diagnostic device according to claim 1 and its feature is; at least one of the aforementioned learned module (16) LSTM, XBOOST, Logistic Regression, linear regression, gradient deoent boosted tree, Artificial Neural Networks, Probabilistic Artificial Neural Networks, Bayes Nayev learning, Bayes Nayev Networks, Random forest, Adaboost, 04.5, ID3 algorithms is trained with. . It is a diagnostic device according to claim 1 and its feature is; said power battery (29) is of a rechargeable nature. . It is a diagnostic device according to claim 7, and its feature is; said power battery (29) works in the range of 12-40 volts.