May 14
0

eKare wins SAWC Award for Oral Presentation

We are delighted to announce that eKare won 2nd place for best Oral Abstract on “Using Artificial Intelligence to Model Wound Healing Prediction – a Preliminary Study Practice Innovations” at the Symposium on Advanced Wound Care Spring/WHS Annual Meeting. Dr. Kyle Wu presented the abstract during the conference and accepted the award on behalf of the entire team at the conference which took place May 7-11, 2019 at the Henry B. Gonzalez Convention Center in San Antonio, Texas. Congratulations to the team of authors: Ozgur Guler, PhD., Patrick Cheng, MS, MBA, Emmanuel Wilson, MS, and Kyle L. Wu, MD, MBA.

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Dr. Kyle Wu awarded plaque by Abstract Chairperson for the SAWC Marie Brown-Etris, RN CWON, CCHP

May 07
0

eKare Sponsors Scholarships for Researchers at SAWC Spring Meeting

Each year, The Wound Healing Foundation recognizes deserving scientists and clinicians in the field of wound healing by facilitating their attendance at key industry meetings throughout the year.  eKare is honored to sponsor travel scholarships to six attendees of this year’s SAWC Spring Meeting in May 2019 in San Antonio, TX.  “We would like to congratulate all of the scholarship recipients for their contributions in the field of wound healing and look forward to meeting them at the SAWC Spring meeting,” says Patrick Cheng, CEO of eKare. Scholarship awardees will be recognized during a ceremony on Thursday, May 9th, 2019.  To learn more about The Wound Healing Foundation and the scholarship program visit:

http://woundhealingfoundation.org/programs/Scholarships.aspx

whf-logo-color-full[1] Aug2015

Dec 10
0
Hybrid DCN_DNN

Using Artificial Intelligence (AI) to Identify Wound Etiology – 
A Preliminary Study

Innovations in Wound Healing Annual Conference. Dec, 2018.

“The proposed hybrid model achieves an accuracy of 94 % in differentiating burn, pressure injury, venous ulcer, and diabetic wound. This early application of artificial intelligence on etiology identification demonstrates the potential of AI in wound care. Future work will focus on improving the robustness and generalizability of the DCN/DNN hybrid model with more images and data augmentation, including the use of infrared image, depth map, and other clinical input.”

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Nov 12
0
Burns logo

3-D Wound Scanner: A Novel, Effective, Reliable, and Convenient Tool for Measuring Scar Area

Burns Journal. Oct, 25, 2018 (epub ahead of print).

Highlights:
•Innovative use of portable 3D wound scanners to measure scar area;.
•Questioned the gold standard of the measurement of scar area, profile method, and showed this method is not suitable for measurement of hypertrophic scar area;
•Traditional methods are adequate for flat areas, however, errors are large in radial and angled areas. Scar was divided into three categories, flat, radial (cylindrical), and angled such as joints…

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Oct 31
1
How IoT is Changing the Science of Medicine

How IoT is Changing the Science of Medicine

Automation is everywhere – in our phones, in our cars, in our homes. The Internet of Things (IoT) is an inter-operational network of physical devices, vehicles, and other electronic items. The network enables all of these devices to connect to one another and to the internet via wireless technology. This allows developers to add technology-based features, including the ability to deliver real-time experiences.

As of this year, IoT is starting to transform healthcare. More specifically, the Internet of Medical Things (IoMT) is transforming how patients are being kept safe and healthy. The IoMT allows medical devices and applications to gather data and communicate, over a wireless network, with healthcare IT systems. A few examples of this connecting network include remote patient monitoring of chronic patients and tracking medication orders. Its main objective is to enable a greater range of services in device management, patient care, and service delivery.

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Oct 24
0
prevent infections

Preventing Infections Before They Happen with Predictive Analytics

Predictive analytics is a rapidly growing area of data science. It uses various statistical techniques, such as predictive modeling and machine learning, to make predictions about unknown future events. In healthcare, predictive analytics analyzes historical and real-time data to identify patient behavior, manage chronic diseases, and improve patient care. The tool allows clinicians, administrative staff, and financial experts to receive alerts about potential events before they happen. This, in turn, helps them to make more informed decisions revolving around patient care.

Today, numerous hospitals across the nation are using real-time predictive analytics. One area in particular where the integration of predictor and intervention are showing efficacy is in preventing infections before they happen.

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