Muhammed A. Moukhtar Hammad, MBBCh, on machine learning models to predict IPP complications

Machine Learning


Hamad said the goal is to develop a risk calculator that doctors can use in clinical practice. This test could provide actionable insight into individual risk of complications based on a patient’s baseline characteristics, comparable to that seen in other fields such as internal medicine.

Hamad also said risk calculators can help patients set realistic expectations about what to expect after a particular procedure.

“Sometimes a patient comes in and they’re not happy after a procedure. It’s not the doctor’s fault, it’s not that the doctor gave them unrealistic expectations, but sometimes the patient is not happy. [an idea that] “I’m going to go back to normal, even better than usual.” “This is not how it works,” Hamad explained. So patients can also get some insight from the machine. ”

reference

1. SMSNA Sexuality Research Grants Program. SMSNA. Accessed November 24, 2025. https://www.smsna.org/grants/grants-available/smsna-scholars-in-sexuality-research-grants-program



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