Nowadays, mobile technology makes it possible for us to realize processes in a relatively short amount of time, showing the user friendly and efficient interfaces that any person is capable of adapting to. Continuing this trend, we develop a mobile application that aids in giving an early diagnosis of Influenza and Dengue, two diseases that affect approximately 5% of the world population (in the case of Dengue) and 5% - 15% of the northern hemisphere (in the case of influenza). Our application consists of an expert system based on fuzzy logic that analyzes symptoms introduced by the user and formulates a diagnosis in approximately 2 - 4 minutes. This system considerably reduced the diagnostic time, improving the recuperation process from these diseases due to their early detection.
In Mexico, two of the diseases that have most caused health problems in the society are Dengue and Influenza H1N1, whose symptoms can be confused amongst themselves or other simple sicknesses which in many cases can lead to a late diagnosis.
Influenza is an acute, contagious viral respiratory disease whose typical manifestations are fever, myalgia, coryza, throat pains and coughing. The influenza virus usually attacks the superior respiratory tract. However, in more extreme cases, it can affect the lower respiratory tract (lungs and bronchioles) [
The epidemiological vigilance is the key to an early detection of the first cases of this disease, helping the patient increase their recovery expectations and simultaneously fire an alarm and start response actions to avoid another pandemic [
Dengue disease is the most prevalent arthropod-borne viral disease in humans. It is caused by four serotypes of single-strand RNA flavivirus (dengue virus [DENV]-1, -2, -3, and -4), which are transmitted by blood-feed- ing mosquitos―mainly Aedesaegypti (Linnaeus) [
It’s one of the most important re-emerging diseases in the world [
In the present day, the rapid development of technology and telecommunications has offered humanity the opportunity to improve areas such as education, industrial productivity and productivity in general for that matter, and of course video game development, pressuring technological evolution worldwide. Some examples of the implementation of this technology can be observed in applications that carry out image analysis and three- dimensional reconstruction utilizing specific information. These diagnoses would have been impossible without the aid of experts. However once developed, this project would be useful in places where mentioned experts would not be of disposition, for example, accidents where muscular or bone damage is present.
In this case, our developed application (BioDnX) is focused on the diagnosis of diseases such as Influenza and Dengue, which have taken many lives on a global scale every year. Commonly, when people suffer of the first symptoms, they wait 1 to 3 days before consulting a physician and as more time goes by, the probabilities of recover are slimmer. BioDnX directly impacts this aspect, reducing the diagnostic time for all people with access to mobile platforms, enabling better recovery times, treatment and possibly saving the patient’s life. Apart from the simple and friendly environment, the available assistant (Dr. DnX), in every stage of the application, converts someone of any age into a potential user without presenting any difficulty in its use or operation.
Many electronic devices have been employed, such as a personal computer capable of running the developing software “Adobe Flash CS6”, a mobile device “Smart Phone” (Motorola G2) for testing and many others such as tablets, iPads and other Android operating system devices.
Computer: CPU: Intel Core i5-3210M 2.5 GHz, RAM: 6 GB, OS: Windows 8.1 Single Language 64 bits.
Testing Devices: Android Operating System Lg L5x, Moto G2 and Samsung Galaxy S3 mini.
Adobe Flash Professional CS6, Animation Software for app development, Adobe Air Version 15.00.249 (programming language converter for iOS and Android Systems), Adobe Photoshop CS6 Version 13.0 (photo and image editor), CorelDraw Graphics Suite X6 64bits Version 16.0.707 (image designer).
Fuzzy logic is an alternative logic as opposed to classical logic which introduces a level of uncertainty in what it evaluates, in the world that we live in there exists many ambiguous or imprecise concepts of nature. Fuzzy logic was designed precisely to imitate human behavior.
A diagnostic can be obtained due to the evaluation of the symptoms implementing fuzzy logic, we cannot determine exactly when a patient is actually suffering of these diseases or not, however we can calculate the probability of the user being victim to these diseases.
The program calculates every symptom, paying close attention to the slightest of details, (this is where expert knowledge comes into play), the user selects the symptoms presented and the system calculates the probability of the user possessing each disease. Finally, the diagnosis is determined based on the inputted symptoms.
The similitude between the symptoms of these two diseases is quite high, thus there is a probability of confusion between the two diseases upon their diagnosis, to resolve this confusion the system proceeds to ask the user if he/she has certain symptoms that they might have overlooked upon inputting data in the main menu, helping the system calculate the probabilities of their diagnosis as accurately as possible.
An expert system which implements fuzzy logic to give an approximate diagnosis of Influenza and Dengue utilizing a friendly interface based on images, where the user selects his/her gender and parts of the body where he/she feels pain with a simple tap, taking into consideration the patient’s age as the first parameter.
After inputting all of the user’s symptoms, the consultation is finalized by tapping the “OK” button from the main menu. The system also contains an assistant, Dr. DnX that makes the user experience much more comfortable.
In order to proceed with the development process and to create a knowledge database that contains all the symptoms and their values, it was necessary to consult information from medical experts in the Virology area at the University of Guadalajara.
Equation (1) and Equation (2), describe each disease operation, adding each value of the symptoms corresponding to index (i).
At the final stage of the application in the diagnosis window, the algorithm compares the values of both disease variables and shows the higher result to the user.
In
In this development we implemented mobile technology to improve the pre-diagnostic times in case of the need for efficient and accurate recognition of the symptoms pertaining to said diseases. The development of BioDnX
Disease | Symptoms and values | |||
---|---|---|---|---|
Symptom | Index | Value | Impact | |
Influenza | Nasal irritation | 0 | 8 | High |
Influenza | Loss of appetite | 1 | 5 | Moderate |
Influenza | Red eyes | 2 | 10 | High |
Influenza | Watery eyes | 3 | 7 | High |
Influenza | Cough | 4 | 5 | Moderate |
Influenza | Nasal congestion | 5 | 7 | High |
Influenza | Breathing difficulties | 6 | 3 | Low |
Influenza | Sore throat | 7 | 15 | High |
Influenza/dengue | Fever (temperature > 99˚F) | 8 | 40 | High |
Influenza/dengue | High temperature to touch | 9 | 20 | High |
Influenza/dengue | Diarrhea | 10 | 2 | Low |
Dengue | Vomit | 11 | 1 | Low |
Dengue | Drowsiness | 12 | 8 | High |
Dengue | Joint-aches | 13 | 7 | High |
Dengue | Skin Problems | 14 | 6 | Moderate |
Dengue | Headaches | 15 | 7 | Moderate |
Dengue | Eye-aches | 16 | 6 | High |
Dengue | Chills | 17 | 3 | Low |
Dengue | Chest pressure | 18 | 2 | Low |
Dengue | Body pain | 19 | 15 | High |
Dengue | Dizziness | 20 | 3 | Low |
aKnowledge database implemented on BioDnX (supervised by medical experts).
showed satisfactory results regarding the detection time of these two diseases, due to what granted the patients a pre-diagnosis within 2 - 4 minutes. It is common for people with the first symptoms to wait days while scheduling a physician’s appointment before being able to receive a reliable diagnosis. BioDnX considerably reduced the time of uncertainty concerning these diseases by allowing the patients to have access to a tool permitting reliable diagnoses.
Situation | Diagnosis data | ||||
---|---|---|---|---|---|
Name | Diagnosis | 1st symptom date | Diagnosis date | Recovery time | |
Without BioDnx | Marisela Fernandez Serrano | Dengue | 27/04/2010 Body pain | 29/04/2010 | 12 days |
With BioDnx | High probabilities of dengue | 14/05/2015 5:07 pm | 14/05/2015 5:09 pm | - | |
Without BioDnx | Nicole Muñoz Filippetti | Dengue | 09/10/2012 Joints-aches | 12/10/2012 | 15 days |
With BioDnx | Dengue | 14/05/2015 11:18 pm | 14/05/2015 11:21 pm | - | |
Without BioDnx | Carlos Gonzalez Ávila | Dengue | 20/08/1998 Eye-aches | 24/08/1998 | 11 days |
With BioDnx | High probabilities of dengue | 15/05/2015 12:09 am | 15/05/2015 12:12 am | - | |
Without BioDnx | Fernando Miguel Saucedo | Influenza | 02/03/2013 10:00 am Simple Flu | 02/03/2013 8:00 pm | 3 days |
With BioDnx | High probabilities of influenza | 15/05/2015 12:55 am | 15/05/2015 12:57 am | - | |
Without BioDnx | Jonathan Arredondo Macias | Dengue | 27/05/2009 Fever | 4/06/2009 | 21 days |
With BioDnx | Dengue | 15/05/2015 1:08 am | 15/05/2015 1:11 am | - |
aBioDnX was used for the recreation of the cases (the procedure was executed with the same symptoms presented on the same day).
In this investigation we designed an Android based application utilizing human expertise to obtain an early diagnosis of Influenza and Dengue, whose symptoms are very similar, taking into account the growing use of mobile devices in the Mexican population. Given that both diseases have impacted the population and due to the time consuming diagnoses, many lives have been lost. We hope that with an application of this nature, the society can have a tool to obtain information pertaining to their symptoms in a timely manner.
We utilized BioDnX to improve the response time of the diagnosis of diseases Influenza H1N1 and Dengue and even though this is just a pre-diagnosis, this will aid the physician. However, it is necessary to debug the diagnostic algorithm to add more diseases and symptoms to the database.