Dr. Olivia Chang on her KL2 award for studying AI in neurogenic bladder

Opinion
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"My hope is that from the KL2 data that I'll generate, hopefully in the next 6 to 12 months, we can apply for an RO1 to push this one step further so that we can benefit other people with brain tumors, other people with strokes, and other peoples with other neurological disorders with bladder symptoms," says Olivia H. Chang, MD, MPH, FACOG.

In this video, Olivia H. Chang, MD, MPH, FACOG, discusses her KL2 award for studying the use of artificial intelligence for predicting neurogenic bladder treatment outcomes. Chang is a UCI Health urologist and an assistant professor and chief of female urology, pelvic reconstructive surgery and voiding Dysfunction, department of urology, at UCI School of Medicine.

Transcription:

Could you discuss you KL2 award from the National Institutes of Health?

This past year, I received a KL2 award, which is an institutional career development award from the NIH. My proposal for the KL2 is to utilize artificial intelligence to see if we can predict neurogenic bladder treatment outcomes, specifically in patients with multiple sclerosis. As we all know, patients with multiple sclerosis have neurogenic bladder; up to 90% of them will experience some sort of urinary dysfunction throughout their care. It also happens to be something that's very undertreated because a lot of MS patients prioritize their MS treatment, maybe their mobility, even though they're living with debilitating urinary incontinence. In my own clinic, in the female urology clinic, I see lots of patients with this condition, and it really inspired me to think about, how can we better predict what treatment to give these patients? Because not all patients are the same. MS patients are not the same as a non-MS patient, and we shouldn't be applying the same overactive bladder treatment outcomes for these patients. So what we are using is a lot of artificial intelligence techniques; we're using supervised learning and machine learning models to see if we can find a predictive pattern to treatment outcomes. The next phase of this is incorporating MRI imaging to see if the specific MS lesions could correspond with their neurogenic bladder symptoms and ultimately, if that corresponds with their neurogenic treatment outcomes. This is a 3-year project for me because it's a 3-year career development award. And throughout this process, I'm also enriching my own education and understanding of artificial intelligence and machine learning through UCI by taking classes with that, and I'm also collaborating with an artificial intelligence expert that we have here at UCI, which is Dr. Peter Chang. I'm also collaborating with the MS institute that we have at UCI, which includes Dr. [Michael] Demetriou, Dr. [Michael] Sy, and Dr. [Gaby] Thai. So it's truly a multidisciplinary, collaborative effort. And my hope is that from the KL2 data that I'll generate, hopefully in the next 6 to 12 months, we can apply for an RO1 to push this one step further so that we can benefit other people with brain tumors, other people with strokes, and other peoples with other neurological disorders with bladder symptoms.

This transcription was edited for clarity.

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