2023
Artificial Intelligence is revolutionizing the field of ophthalmology by enabling faster, more accurate detection of vision-threatening diseases. Through advanced image analysis of retinal scans, AI systems can identify early signs of conditions like diabetic retinopathy, age-related macular degeneration (AMD), and glaucoma—often before symptoms appear.
This early detection is vital. In regions with rising diabetes prevalence, such as the Gulf and Middle East, thousands of individuals are at risk of losing vision due to undiagnosed or untreated diabetic eye disease. AI-based screening offers a scalable, efficient solution for mass population screening, especially in primary care settings where access to ophthalmologists may be limited.
By analyzing retinal images within seconds, AI can flag abnormalities, prioritize urgent cases, and support clinicians in delivering timely referrals and treatment. This not only helps preserve sight but also reduces the burden on healthcare systems by catching disease before irreversible damage occurs.
AI in ophthalmology is not the future—it’s the present, and it’s already saving vision.
First introduced five decades ago, MRI scanners are now a cornerstone of modern medicine, vital for diagnosing a wide range of conditions — including strokes, tumors, and spinal conditions — while avoiding exposing patients to radiation.
But they remain hard to come by in developing countries: Africa has less than one MRI machine per million people, while the figures in the United States and Japan are 40 and 55 per million, respectively.
To tackle the problem, Yujiao Zhao and colleagues at the University of Hong Kong built a simplified, low-powered MRI machine using store-bought hardware that cost around $22,000, and published their findings in the prestigious journal Science.
MRI uses a strong magnetic field and radio waves to align and manipulate the body’s hydrogen atoms, producing detailed images of internal structures and organs.
The strength of magnets is measured in units called teslas (T), with conventional MRIs requiring powerful electromagnets that have wires bathed in supercooled liquid helium to generate magnetic fields of 1.5T to 7T.
These machines demand high electricity inputs, far exceeding what standard wall outlets can provide, and must be housed in radio frequency-shielded rooms to prevent equipment interference. Current clinical use MRIs cost upwards of million dollars.
By contrast, the Hong Kong research team’s full body MRI machine used a helium-free 0.05T magnet and required just 1800 watts — comparable to a hair dryer, meaning it could use a standard socket. What’s more, it did not require radio shielding.
To compensate for the reduced image detail and higher levels of radio interference, the researchers integrated their system with a deep learning algorithm trained on a vast dataset of high-resolution images of human anatomical structures.
They then tested their machine on 30 healthy adult volunteers, performing scans over their bodies from their brains down to their knees.
2025
As part of our strategic growth across the Middle East, SIMCO has officially expanded its operations into the Kingdom of Bahrain & to Sultanate of Oman
2025
Early detection is the most powerful tool in the fight against heart disease. One of the most dangerous and often silent cardiac conditions