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Rabat – In an era defined by rapid technological advancement, artificial intelligence (AI) has spread through diverse sectors and has started to make waves in medicine.
The technology’s uses in healthcare include the integration of algorithms into diagnostic and treatment processes, which contributes to improving patient care and outcomes.
Morocco World News spoke with Doctor Nacer Abid, known as DNA, who contributed to the development of a model for detecting anomalies in amniotic fluid ultrasounds using deep learning techniques. Amniotic fluid is a crucial indicator of fetal health during pregnancy.
Abid spoke about the inspiration behind the innovative model, emphasizing its potential to address healthcare disparities and improve global access to high-quality ultrasound diagnostics.
“The inspiration behind developing the model for detecting anomalies in amniotic fluid stems from a commitment to advancing prenatal care and improving maternal and fetal health outcomes,” he said.
The Moroccan doctor added that the initiative directly addresses healthcare disparities, in line with the World Health Organization’s (WHO) recommendation for regular ultrasound examinations during pregnancy.
The model was developed by Moroccan startup Deepecho with the help of a team of artificial intelligence experts and physicians, including Abid.
The “collaborative synergy” between medical professionals and AI experts is central to Abid’s approach. He underlined that this interdisciplinary teamwork played a pivotal role in shaping the project, which combined medical insights with technological innovation.
Reflecting on the impact of the model, Abid emphasized its precision, efficiency, and potential to revolutionize prenatal healthcare. “Our model for detecting anomalies in amniotic fluid is set to revolutionize prenatal healthcare by significantly improving the precision and affordability of ultrasound diagnostics,” he said.
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“The enhanced accuracy ensures early identification of complications, facilitating timely interventions for better maternal and fetal outcomes,” he explained.
Beyond the model’s accuracy, Abid said it enhances the speed of diagnosis and enables quicker medical interventions when necessary. This technological integration, he noted, translates into faster utilization and more rapid decision-making during ultrasound examinations.
An article detailing the model, “Fetal Biometry and amniotic fluid volume assessment end-to-end automation using Deep Learning,” was published in the journal Nature last November.
According to the article, the model significantly simplifies the process of capturing fetal biometry (FB) and amniotic fluid volume (AFV) measurements during ultrasound examinations, reducing the steps from 12 to 3.
Social media impact
In addition to his research, Abid is committed to raising awareness about innovative medical research through his online presence. Through platforms like @welcometodna, he aims to make complex scientific information accessible and interesting to the general public, inviting everyone to explore the world of new technologies.
“With a focus on videos, articles, and infographics, I aim to make complex scientific information accessible and interesting to a non-specialized audience,” Abid said. His content delves into a wide range of areas, from Artificial Intelligence to stem cells and peptides.
For Abid, his involvement in the project represents a notable milestone in his career, particularly in terms of media exposure and recognition within the medical and social spheres.
Looking to the future, Abid envisions a seamless integration of AI into every facet of medicine. While AI will undoubtedly play a key role in improving diagnostics and personalized medicine, Abid believes it will never replace human doctors.
“Instead, AI will emerge as the doctor’s greatest ally, empowering healthcare professionals to make faster and more accurate decisions,” he concluded.
