As a pediatric radiologist, Jaishree Naidoo was used to seeing animals in scans, but she had a moment of epiphany after coming across a story detailing the use of artificial intelligence (AI) recognition patterns in distinguishing animals from human beings. After learning more about the technology, she was convinced that it could revolutionize the field and make it easier for doctors to identify problems with their patients. She started working on building an AI-based system to improve accuracy and helped develop an app that can be used by medical professionals across the globe. Today, her work has led her to become one of the pioneering figures in AI healthcare technology and she continues to share her knowledge with others so that they can benefit from its capabilities as well.
Naidoo is no stranger to the potential of AI in healthcare. As a radiologist with 20 years of experience, she was already familiar with pattern recognition, and recognized how AI could be used in the industry to transform diagnostic imaging access for patients. The partnership she formed with her husband, Terence Naidu and Andrei Migatchev in 2019 – Envisionit Deep AI – is a startup that uses artificial intelligence to bridge demand for diagnostic imaging by using data analytics and machine learning. By using this technology, they are able to provide more accurate results faster than traditional methods and help improve patient care by identifying issues sooner.
Envisionit Deep AI is on the path to growth with a $1.65 million investment from New GX Ventures SA. This follows their win of the Southern Africa regional winner at the African Startup Awards. With this money, they will be able to develop their platform further, expand their team and continue to bring innovative solutions to marketplaces across the continent.
The new company, called AI Radiology, is aiming to use artificial intelligence (AI) to help radiologists look more closely at imaging scans and make better diagnoses. This would be done through the use of machine learning algorithms, which would allow the software to learn from past data and improve its accuracy over time. This would revolutionize the way radiologists do their jobs, making it easier for them to identify problems that may not have been evident when originally viewed by a human being.
A hybrid solution refers to a method of combining two or more different approaches or tools to achieve the same goal. One
Radify claims that its AI platform ensures speedy, accurate, quality and affordable medical imaging diagnosis. This is important, as early diagnosis and treatment of disease is critical in reducing morbidity and mortality rates. Radify is planning to scale its products beyond South Africa, which will give users access to quality care worldwide.
Radify AI plans to expand its reach by obtaining approvals from the Food and Drug Administration (FDA) and European Medical Agency (EMA). Global approval would allow the technology to be used in a greater number of countries, potentially improving patient care across the board.
Why would reducing the burdens in the healthcare system be important to Africa?
There are a number of reasons why reducing the burdens in the healthcare system would be important to Africa. First, infrastructure and human resource investments remain dismal in many African countries, which makes it difficult to provide quality care for residents. Second, many Africans rely on traditional healers rather than doctors for medical assistance, so reducing needless health costs could go a long way towards improving people’s lives. Finally, widespread poverty and inequality can seriously impact people’s access to good health care, whether they are able to afford it or not. By addressing these issues head-on through deep AI technology initiatives like
One justification for this situation is the lack of appropriate training programs for medical professionals. In many cases, doctors in Africa only receive a few years of medical school and then proceed to work in rural clinics, which is not optimal preparation for dealing with complex disease cases. Additionally, there simply aren’t enough specialists available to treat patients who need deeper insight into their condition or more specialized treatments.
Radify AI’s hybrid solution makes it accessible to all, especially in peri-urban and rural regions, by combining the power of AI with the expertise of radiologists. This dearth in radiologists is the driving force behind Radify AI’s goal to provide healthcare solutions for everyone. By relying on AI to identify abnormalities on scans, and then bringing in an expert radiologist to review those scans and diagnose any Issues, RadifyAI hopes to provide quality care for all patients.
Radify AI provides diagnostic imaging solutions that are accessible to anyone, regardless of their location or resources. This democratization of imaging technology is beneficial for both first world and rural clinics, as it allows them to improve patient care regardless of their geographic location.
The startup’s on-site product can be integrated with devices such as X-ray machines to deliver diagnosis and treatment at the point of care. They also offer tele-radiology for patients that require radiology reports. This unique service allows patients to receive their diagnosis and treatment while they are standing in their office or hospital room, which could reduce wait times and improve patient satisfaction.
One of the proposed solutions to reducing tuberculosis complications and delayed diagnosis is through the use of a smartphone app. aptly named “TB Tracker,” this new app would allow patients to transmit their X-ray images electronically for immediate diagnosis and treatment. When developed for South Africa’s mining sector, this app would provide employees with easier access to information on their tuberculosis status and treatment recommendations, thereby eliminating needless delays in care.
In 2013, the startup was acquired by IBM for an undisclosed sum. The acquisition demonstrated IBM’s commitment to the development of innovative medical technologies, and underscores the importance of machine learning in gathering data for medical diagnosis and treatment.
Naidoo is optimistic about the future of artificial intelligence, believing that its applications will only continue to grow in the years to come. Already, AI has proved to be a valuable tool in helping hospitals more efficiently manage their workloads and improve patient care. As this technology continues to develop, Naidoo believes it will play an even larger role in helping us better understand and care for our environment and ourselves.
At the heart of Qualified, is the belief that data quality is essential to making accurate predictions. To ensure its models are trained using high-quality data drawn globally and from diverse ethnic groups, Qualified commitment combines rigorous quality controls with a diversified source of data.
The data collected by the product is a vital tool for companies like this, as it allows them to develop accurate models that can be used to help patients. However, this data can also be reviewed and validated through radiologists, who provide some assurance that the product is working accordingly. This feedback has helped the startup improve the accuracy of its models overall.
Deep AI’s computer-assisted training model for medical practitioners is an invaluable tool that can help them to gain radiology skills in a short amount of time. The model is designed to be user friendly and easy to use, making it an ideal resource for medical professionals who are looking to improve their knowledge in this field.