How Medical Imaging Datasets Can Help AI to Diagnosis the Covid-19 Like Deadly Virus?
The highly contagious disease coronavirus or COVID-19 spread rapidly confronted healthcare professionals globally with unprecedented clinical trial and diagnostics challenges. As they struggle to cope with such highly transmissible disease at the same time also continue to take care of patients and diagnosis timely among new people who are at risk of getting infected.
Here, AI can play a big role in detecting the COVID-19 like disease from the infected patients, helping others for early diagnosis without the help of radiologists. Actually, over the past few years AI algorithms, particularly deep learning, have demonstrated remarkable progress in image-recognition tasks with amazing results in medical imaging analysis.
AI in Healthcare
Though, AI with the help machine learning and big data in healthcare industry is already playing a vital role through various computer systems, applications and AI-enabled devices working round-the-clock to assist patients, control disease, carrying medical supplies and disinfecting the hospital premises, buildings and other places automatically without the help of humans keeping them away from such infections.
AI in robotics, autonomous flying drones, AI security cameras and self-driving cars are providing the automated solution in fighting with COVID-19 like a deadly disease. AI applications in healthcare industry is immense, from discovering and developing effective drugs and vaccines for new diseases with the best level of accuracy. So, in the radiology department, let’s find out how AI in medical imaging can help to diagnose and cure the COVID-19 like a deadly disease.
AI in Radiology
AI in radiology works like an artificial mind detecting the disease with an acceptable level of accuracy. And AI-enabled machines or medical systems not only can detect the diseases but can also suggest the medicines as per the patient’s biological conditions and types of syndromes evident at the initial stage of diagnosis by the doctors or medical attendants.
And when AI-enabled devices or computer systems are trained with a huge quantity of annotated medical imaging datasets, with the right algorithm, it can diagnosis such disease without the help of radiologists. Similarly, to avoid human contacts, AI in radiology can be used to diagnose COVID-19 like a deadly disease with a high level of accuracy.
Earlier in radiology practice, medical imaging analysis specialist doctors or you can say radiologists visually assess the medical images for the detection, characterization, and monitoring of diseases. But now AI systems perform automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics.
AI in Epidemiology
Similarly, AI in epidemiology can help doctors and medical experts before the outbreak of deadly disease to minimize its impact on the people. But again here AI medical diagnosis system can do this job precisely if the model is trained with the right quality and quantity of medical imaging training datasets that have been prepared with CT Scan, MRI or ultrasound medical imaging reports of infected patients.
And the hosting of such images at one place along with annotation and analysis framework will enable researchers to understand epidemiological trends and to generate new AI algorithms to assist with COVID-19 disease detection, differentiation from other pneumonia and quantification of lung involvement on CT for forecast or therapy planning in advance.
Apart from medical imaging, AI in epidemiology can be implemented with various other types of other data that only big data experts or data scientists can analyze the certain trends in changing the behavior of people or other types of a sudden change in economic activities or unexpected increase in demand of specific medicines or healthcare products, etc.
AI in Coronavirus Diagnosis
In the case of COVID-19 outbreak, most of the patients infected into their lungs started with pneumonia or the common cold, sneezing and throat infections with short of breathing. And the diagnosis of all such symptoms are possible with imaging technology, like X-rays, CT Scan or MRI of chest or lungs of patients which a radiologist can analyze to understand the severity of the infection.
AI Medical Imaging Analysis for COVID-19 Diagnosis: Use Cases
A Canadian startup and researchers from the University of Waterloo are open-sourcing COVID-Net, a convolutional neural network that aims to detect COVID-19 in X-ray imagery. In response to the pandemic, a global community of health care and AI researchers have produced a number of AI systems for identifying COVID-19 in CT scans.
Similarly, tech giants like Yahoo and AI startups claimed they’ve created systems capable of recognizing COVID-19 in X-ray or CT scans with more than 90% accuracy. Similarly, a new artificial intelligence-powered deep learning model has helped radiologists in China to distinguish COVID-19 from community-acquired pneumonia and other lung diseases in chest CT imaging.
The study developed as part of a six-hospital study, where researchers refined the model using 4,356 exams from 3,322 patients. The COVID-19 Detection Neural Network for short—scored high marks, notching 90% sensitivity and 96% specificity for diagnosing coronavirus infection.
This kind of amazing results demonstrates that the right machine learning datasets using the convolutional networks model can distinguish COVID-19 from community-acquired pneumonia. And this model also scored high marks in differentiating such diseases from novel coronavirus, with the 87% sensitivity rate and 92% specificity rate.
AI for Faster Detection with High Accuracy
AI is detecting the infection faster than doctors with better accuracy. In china using 5,000 confirmed cases as their training data, scientists built an algorithm claiming it can detect coronavirus infections in CT scans in just 20 seconds and with 96% accuracy.
Radiologists are saying results are the proof-of-principle for using artificial intelligence to extract radiological features for timely and accurate COVID-19 diagnosis.
In another study, researchers reached a similar conclusion after going through over 46,000 images. They said the deep learning model showed comparable levels of performance with expert radiologists, and greatly improve the efficiency of radiologists in clinical practice.
Similarly, in China, a new smart image-reading system has been launched by a company that can assist doctors with efficient and accurate diagnoses by leveraging AI technology and can help to control the epidemic through earlier diagnoses and treatment.
Role of AI in Safe Diagnosis of COVID-19
As, we know the COVID-19 virus is a highly contagious disease, hence, doctors or radiologists are also vulnerable to get infected with this deadly virus. But with the help of AI in medical imaging diagnosis, AI’s strengths find its ways and liberate the medical staff for more intimate care for the patients where human presence and interventions are indispensable and invaluable.
Actually, while handling a patient, a radiologist or technician has to come in physical contact with the patient for instructions about how to position and breathe correctly. AI is used to take the human presence out of the exam room and allow the radiologist to guide the patient through the process contact-free minimizing their risk of getting infected.
Medical Imaging Datasets for COVID-19 Analysis
To develop the AI model that can detect such disease through medical imaging analysis, a huge amount of training dataset is required. As the COVID-19 smart image-reading system has been trained using similar clinical data and aims to close this gap.
Moreover, AI in medical imaging and diagnostics can conduct a comparative analysis of multiple CT scan images of the same patient and measure the changes in infections. That helps doctors to track the development of the disease, evaluate the treatment and arrive at the prognosis for the patients.
It can assist doctors in diagnosing, triaging and evaluating COVID-19 patients speedily and effectively. The COVID-19 smart image-reading system also supports AI image-reading remotely by medical professionals outside the epidemic areas.
The medical imaging community globally united to control such disease with early and safe detection of such disease using the AI. Hence, to create and share the medical imaging dataset, The Radiological Society of North America continues to build on its extensive body of COVID-19 research and education resources, announcing a new initiative to build a COVID-19 Imaging Data Repository.
This open data repository will compile images and correlative data from institutions, practices, and societies around the world to create a comprehensive source for COVID-19 research and education efforts like training the new AI models.
And such data can be also used by a highly experienced radiologist to analyze and annotate the area of interest to create the medical imaging datasets for developing the more reliable AI model that can easily and timely detect such an epidemic with the best level of accuracy.
And to make the COVID-19 infection or contagion recognizable to machines, the medical images need be labeled or annotated manually by experts or you can say by experienced radiologists. Once the data is annotated, machine learning algorithms can detect and learn how to recognize the infection among such patients and diagnosis the disease timely through a successfully develop AI model.
Cogito is providing healthcare training data for AI and machine learning development. Actually, it is an expert in image annotation services with the next level of precision to provide high-quality training datasets for computer vision-based AI models.
For deep learning medical imaging diagnosis, Cogito can be a game-changer to annotate the medical imaging datasets detecting different types of diseases done by the highly-experienced radiologist making the AI in healthcare more practical with an acceptable level of prediction results in different scenarios.