Wound healing progress prediction through Machine Learning

Equipping clinicians with an accurate predictive wound healing model would be significant in the triage and the care of patients. This would allow timely diagnosis, and lower treatment cost by ensuring that the clinicians implement aggressive treatment methods for patients with compromised wound healing. Patients with normal wound healing can be treated without requiring frequent visits to the clinic.

Often times, patients experience compromised wound healing, commonly referred as chronic wounds. Chronic wounds are more common amongst the diabetic and elderly population. In the United States alone, around 6.5 million people are affected by it. These wounds fail to heal on time, and instead result in complications that could possibly lead to amputation or even fatal infection. Quick and aggressive treatments require the clinicians to be able to distinguish chronic wounds from other wounds during the initial treatment phase.


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With a background in Biomedical Engineering and Data Science, Ali Javaid aspires to bring innovative solutions and unique opportunities to the HealthTech industry. Reach out to him via LinkedIn or email at ali@getgrom.com

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