AI Medical Compendium Journal:
Wounds : a compendium of clinical research and practice

Showing 1 to 4 of 4 articles

VGG19 demonstrates the highest accuracy rate in a nine-class wound classification task among various deep learning networks: a pilot study.

Wounds : a compendium of clinical research and practice
BACKGROUND: Current literature suggests relatively low accuracy of multi-class wound classification tasks using deep learning networks. Solutions are needed to address the increasing diagnostic burden of wounds on wound care professionals and to aid ...

Comparison of wound surface area measurements obtained using clinically validated artificial intelligence-based technology versus manual methods and the effect of measurement method on debridement code reimbursement cost.

Wounds : a compendium of clinical research and practice
BACKGROUND: Evidence shows that ongoing accurate wound assessments using valid and reliable measurement methods is essential to effective wound monitoring and better wound care management. Relying on subjective interpretation in measuring wound dimen...

Enhancing complex wound care by leveraging artificial intelligence: an artificial intelligence chatbot software study.

Wounds : a compendium of clinical research and practice
INTRODUCTION: In the realm of complex wound care, where effective diagnosis and treatment are critical, AI holds immense potential. With the advent of AI chatbot software, the field of wound care can potentially benefit from AI-driven advancements.