We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us
ARAB HEALTH - INFORMA

Download Mobile App




Events

27 Jan 2025 - 30 Jan 2025
15 Feb 2025 - 17 Feb 2025

Machine Learning Algorithm Detects Cervical Cancer

By HospiMedica International staff writers
Posted on 24 Jan 2019
Print article
Image: The EVA3 mobile colposcope, with smartphone attached (Photo courtesy of MobileODT).
Image: The EVA3 mobile colposcope, with smartphone attached (Photo courtesy of MobileODT).
A novel colposcope uses an automated visual evaluation (AVE) algorithm to detect cervical cancer from even a single image.

The MobileODT (Tel Aviv, Israel) Enhanced Visual Assessment 3 (EVA3) system is a compact colposcope designed for durability and portability. Features include an ultra-bright powered light source with cross-polarization (to reduce glare); a complementary metal-oxide semiconductor (CMOS) sensor with 13 megapixel resolution; and a powerful 4X optical/16X digital zoom magnification lens that provides a working distance of 225-400 mm. The rechargeable, long-lasting battery provides up to 10 hours of continuous use.

Secure software allows for real-time visualization of the cervix, with enhancement filters that can be applied directly to captured images. Secure online data management allows users to document cases, add annotations, and export the information to an electronic medical record (EMR), simplifying the medical workflow. In addition, a cloud-based information system (EVA Cloud) provides secure access to real time data so as to monitor provider utilization, identify cases reviewed, collect anonymized patient statistics, and enhance quality control and quality improvement opportunities.

The EVA Colposcope is currently used in 29 countries, using smartphone technology and augmented intelligence cervical cancer detection to improve cancer identification. The augmented AVE algorithm can identify problematic lesions with greater reliability than traditional Pap cytology testing, and with a higher level of accuracy than expert human colposcopists, as validated by the U.S. National Cancer Institute (NCI, Rockville, MD, USA) and the National Library of Medicine (Bethesda, MD, USA).

“For this new technology to move out of the laboratory and into healthcare practice, a practical application was needed. The EVA System is the only colposcope on the market ready to deliver AVE at the point-of-care,” said Ariel Beery, CEO of MobileODT. “We are excited by the new AVE algorithm and the promise it holds in fighting cervical cancer. Our team is proud to make available an AVE enabled colposcope to reach more women and save more lives.”

Cervical cancer is the fourth most common cancer in women, with more than 500,000 new cases occurring annually worldwide. The two most common detection methods include the Pap smear, which can be performed by a non-specialist, and colposcopy, which requires visualization of the cervix using a speculum, a colposcope, and a trained professional to administer the test. Colposcopes and people who know how to use them are difficult to find in many low-income regions.

Related Links:
MobileODT

Gold Member
12-Channel ECG
CM1200B
Gold Member
Real-Time Diagnostics Onscreen Viewer
GEMweb Live
New
Computed Tomography System
Aquilion ONE / INSIGHT Edition
New
Transducer Covers
Surgi Intraoperative Covers

Print article

Channels

Surgical Techniques

view channel
Image: The surgical team and the Edge Multi-Port Endoscopic Surgical Robot MP1000 surgical system (Photo courtesy of Wei Zhang)

Endoscopic Surgical System Enables Remote Robot-Assisted Laparoscopic Hysterectomy

Telemedicine enables patients in remote areas to access consultations and treatments, overcoming challenges related to the uneven distribution and availability of medical resources. However, the execution... Read more

Patient Care

view channel
Image: The portable biosensor platform uses printed electrochemical sensors for the rapid, selective detection of Staphylococcus aureus (Photo courtesy of AIMPLAS)

Portable Biosensor Platform to Reduce Hospital-Acquired Infections

Approximately 4 million patients in the European Union acquire healthcare-associated infections (HAIs) or nosocomial infections each year, with around 37,000 deaths directly resulting from these infections,... Read more

Point of Care

view channel
Image: The acoustic pipette uses sound waves to test for biomarkers in blood (Photo courtesy of Patrick Campbell/CU Boulder)

Handheld, Sound-Based Diagnostic System Delivers Bedside Blood Test Results in An Hour

Patients who go to a doctor for a blood test often have to contend with a needle and syringe, followed by a long wait—sometimes hours or even days—for lab results. Scientists have been working hard to... Read more
Copyright © 2000-2024 Globetech Media. All rights reserved.