- 18:07 Nearly 800 killed in Gaza while seeking aid
- 17:20Morocco launches “Morocco 2030 Foundation” to Lead Major Football Events
- 16:50State Department begins major staff cuts amid reorganization effort
- 16:20Catalan firefighters mourn colleague’s death while battling Paüls wildfire
- 15:54Mediterranean ports see slight rise in coastal and small-scale fishing in early 2025
- 15:50Brits in Spain struggle with appointment chaos for residency renewals
- 15:22France opens investigation into platform X over suspected algorithm manipulation
- 15:20Stephen Miller’s rise: How Trump’s closest aide reshaped U.S. immigration policy
- 14:55Russia seen as a long-term threat by France’s top military officer
Follow us on Facebook
Moroccan Researcher Pioneers AI-Powered Surgical Risk Assessment Tool
In a significant advancement for surgical medicine, Moroccan researcher Sara Ben Hmido has developed and pilot tested an innovative artificial intelligence model designed to predict complications during colorectal surgery. The groundbreaking trial, conducted at Amsterdam UMC in October, marks a notable step forward in surgical risk assessment.
Ben Hmido's model analyzes real-time patient data, including vital signs such as blood pressure and blood loss, to forecast potential surgical complications like anastomotic leaks. This predictive capability enables surgeons to make more informed decisions during procedures, such as opting for a colostomy instead of intestinal repair when dealing with high-risk cases.
"When provided with a patient's current pre-operative parameters, our model is tuned to generate an individualized risk prediction for that specific patient," Ben Hmido explained. The system's ability to identify low-risk patients also helps prevent unnecessary invasive procedures and can facilitate earlier hospital discharges.
The implementation of this technology extends beyond individual patient care, offering broader benefits to healthcare systems through reduced complications, costs, and workload. However, Ben Hmido emphasizes that maintaining patient autonomy and ensuring ethical usage remain paramount concerns in the development process.
To address these challenges, Ben Hmido and her team are developing protocols and recommending legislation to regulate the model's use. "This way the machine learning model can be used to the benefit of our patients and at the same time make sure their rights are protected," she stated.
The researcher strongly emphasizes that this technology is designed to complement, not replace, medical professionals. "There is simply no replacement for the human touch of a nurse, the empathy and compassion that build trust with patients, or the nuanced decision-making and creativity of a surgeon," Ben Hmido affirmed. Instead, she envisions the system as a decision-support tool that enhances evidence-based clinical choices while maintaining physician responsibility for patient outcomes.
Looking ahead, Ben Hmido sees significant potential for countries like Morocco to advance AI-driven healthcare solutions. She advocates for strengthening digital infrastructure, particularly electronic health record systems, as a foundation for effective AI implementation in healthcare settings.
The development of this surgical risk assessment tool represents a significant step forward in combining technological innovation with practical medical applications, while maintaining a focus on patient care and ethical considerations. As Ben Hmido concludes, it's a tool that "streamlines processes, allowing healthcare professionals to focus on what they do best—delivering compassionate, personalized care."