Our Mission at Wounds A.I. is to Organize and Gain Insights About All the World’s Wound Data
We believe by doing so we can reduce patient suffering associated with delayed wound healing. We are Machine Learning as a Service that optimizes the clinical, operational, and financial decisions related to wound care.
Our patent pending Cognitive Imagery System (CIS) is the only decision support system that automatically combines a myriad of data into a simple and intuitive user interface to provide the clinician and administrator actionable intelligence about the wound, patient and patient populations.
Mrs. Ryan is 64 years old and lives alone. In January 2016, she had developed a large ulcer on her right leg. The ulcer had been present for a year and had developed because of a trauma. Mrs. Ryan had tried to manage the chronic wound herself for several months when it was quite small but as it began to deteriorate, she had to reduce her activities. The chronic wound was affecting her quality of life. She expressed feelings of helplessness, hopelessness and lack of control. The odor and excess drainage from her ulcer contributed greatly to feelings of loneliness, isolation and reduced self-esteem.
Mrs. Ryan sought medical advice when she could no longer cope. She knew very little about leg ulcers and was very distressed when she arrived at the Metropolitan Wound Center.
Wounds A.I. analytics software automatically identified the type of chronic wound as a venous ulcer and as a result we could select and employ the most appropriate treatment immediately. Our wound analytics software identified the potential impact these risks factors could have on Mrs. Ryan's healing. This was essential, as it is usually extrinsic factors like depression or poor nutrition that causes wound healing to stall and not the wound itself.
A vascular surgeon later confirmed our software's assessment. Wounds A.I. software not only identified the key risk factors but it also predicted how long it was going to take for the wound to heal. It was clear to me that Mrs. Ryan was looking at a very long process unless we addressed these risk factors.
I wanted to show Mrs. Ryan that if other patients could heal so could she. So, I had our wound analytics software provide a list of similar patients who had played an active role in their healing and had successful outcomes. After sharing their stories with Mrs. Ryan, we saw her confidence start to reappear.
By September 2016, Mrs. Ryan's wound had healed. In conclusion, an accurate assessment is the key to successful diagnosis and management of a patient with a leg ulcer. However, this goes hand-in-hand with being able to preemptively identify the extrinsic risks to healing and knowing how they were successfully managed previously.