Who is Mohamed, our expert of Medical AI?
Mohamed Elsaid is an integral member of Humans in the Loop, particularly of Doctors in the Loop, our brand dedicated to medical AI annotation by certified medical professionals.
We sat down with Mohamed to better understand the specificities, challenges, and opportunities of AI in the medical field. Mohamed is my colleague, and I spent a good moment interviewing him to get to know his job better. I would like to thank him for spending some of his time off to answer my questions. I hope you will enjoy and learn things as well!
Artificial intelligence (AI) is changing the way we approach healthcare. It is being used in various ways, from disease detection to surgery. Mohamed Elsaid, a medical project coordinator, has been working on medical data annotation for over four years. In this interview, he sheds light on how AI is being used in medicine and the importance of medical image annotation.
What Are The Practical Uses Of AI In Medicine?
Medical image annotation is the process of labelling medical imaging data such as X-Ray, CT, MRI scans, Mammography, or Ultrasound. The labelled data is then used to train AI algorithms for medical image analysis and diagnostics, helping doctors save time, make better-informed decisions, and improve patient outcomes.
“In medical imaging, AI tools are being used to analyze CT scans, x-rays, MRIs, and other images for lesions or other findings that a human radiologist might miss”
It is used to train AI algorithms for medical image analysis and diagnostics, helping doctors save time, make better-informed decisions, and improve patient outcomes, which pave the way for more effective and efficient medical care.
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What are the differences between Medical Image Annotation and regular data annotation?
Medical image annotation is more complicated than regular data annotation. It requires a well-trained and certified medical professional for each specialty. Moreover, most of the projects require specific annotation tools that allow for more accurate and consistent annotations of medical images, which can lead to better diagnoses and treatments.
Can you share some examples?
Radiology is one of the fields where AI has an important role. “It helps in early disease detection like colon cancer, breast cancer. Also, it improves the reporting, provides faster diagnosis, enhances image quality, decreases the reporting time, and increases the clinician’s confidence,” said Mohamed.
Machine learning models could also be used to observe the vital signs of patients receiving critical care and alert clinicians if certain risk factors increase.
AI has an important role in surgery, especially in robotic-assisted surgeries. “AI can determine patterns and vital structures within surgical procedures to improve best practices and to improve a surgical robot’s control accuracy,” said Mohamed.
Who are the medical annotators working at HITL?
Humans in the Loop has a team of medical annotators from two different locations. One team is in Egypt, and another team is in Syria. The team is composed of medical specialists, practitioners, medical students, and healthcare professionals.
Can you share with us any use cases of medical annotation that you are passionate about?
Mohamed highlighted the colonoscopy annotation project used to train AI models to assist Gastroenterologists in their clinical routine, which will help in colon cancer early detection and significantly reduce the incidence and mortality of colon cancer patients.
Looking Forward
AI is an exciting development in the field of medicine, and we are only just beginning to realize its potential. By using AI tools like medical image annotation, we can improve the accuracy of diagnoses, reduce the incidence of disease, and ultimately save lives. We are proud of our Doctor in the Loop team !
The right annotation team for your medical AI project
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