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
LGC Clinical Diagnostics

Hologic

Designs and provides products for clinical laboratory and blood screening, including testing items for detection of h... read more Featured Products: More products

Download Mobile App




Hologic Partners with Google Cloud to Focus on AI and Machine Learning for Advancing Digital Diagnostic Capabilities

By LabMedica International staff writers
Posted on 04 Feb 2021
Print article
Illustration
Illustration
Hologic, Inc. (Marlborough, MA, USA) and Google Cloud have entered into a new agreement to focus on enhancing artificial intelligence (AI) and machine learning (ML) to bring about breakthrough results in cervical cancer screening.

The multi-year strategic collaboration will feature the integration of Google Cloud’s ML technologies with Hologic’s Genius Digital Diagnostics System to transform screening and accelerate the eradication of cervical cancer across the globe. Genius Digital Diagnostics is the first digital cytology platform to combine AI with advanced digital imaging to help identify pre-cancerous lesions and cancer cells in women. Now, Hologic is enhancing the deep learning component of the system with Google Cloud. The expectation is that the Genius Digital Diagnostics System will derive even more actionable insights from cytology slides for cytotechnologists and pathologists. Google Cloud also provides a secure and reliable cloud data architecture to further extend the system’s capabilities. Hologic is conducting research to explore the meaningful differences working at the intersection of AI and ML can have within diagnostics, improving laboratory performance, healthcare provider decision-making, and ultimately patient care.

“Hologic has been at the forefront of cervical cancer screening for more than 30 years, and we are building on that legacy with this strategic collaboration,” said Kevin Thornal, President of Hologic’s Diagnostic Solutions Division. “Enhancing our use of AI with Google Cloud’s machine learning capabilities and cloud architecture is the next natural step in this journey forward.”

“Through this collaboration with Hologic, we are helping to evolve digital diagnostics by complementing their expertise in diagnostics and AI with our expertise in machine learning,” said Joe Miles, Managing Director of Google Cloud Healthcare and Life Sciences. “We are further bringing to life our two organizations’ shared commitment to reimagining digital diagnostic capabilities for laboratories and healthcare providers across the globe, ultimately enabling them to better serve their patients.”




Gold Member
Flocked Fiber Swabs
Puritan® Patented HydraFlock®
Verification Panels for Assay Development & QC
Seroconversion Panels
New
Creatine Kinase-MB Assay
CK-MB Test
New
Chlamydia Trachomatis Assay
Chlamydia Trachomatis IgG

Print article

Channels

Clinical Chemistry

view channel
Image: QIP-MS could predict and detect myeloma relapse earlier compared to currently used techniques (Photo courtesy of Adobe Stock)

Mass Spectrometry-Based Monitoring Technique to Predict and Identify Early Myeloma Relapse

Myeloma, a type of cancer that affects the bone marrow, is currently incurable, though many patients can live for over 10 years after diagnosis. However, around 1 in 5 individuals with myeloma have a high-risk... Read more

Immunology

view channel
Image: The cancer stem cell test can accurately choose more effective treatments (Photo courtesy of University of Cincinnati)

Stem Cell Test Predicts Treatment Outcome for Patients with Platinum-Resistant Ovarian Cancer

Epithelial ovarian cancer frequently responds to chemotherapy initially, but eventually, the tumor develops resistance to the therapy, leading to regrowth. This resistance is partially due to the activation... Read more

Technology

view channel
Image: Ziyang Wang and Shengxi Huang have developed a tool that enables precise insights into viral proteins and brain disease markers (Photo courtesy of Jeff Fitlow/Rice University)

Light Signature Algorithm to Enable Faster and More Precise Medical Diagnoses

Every material or molecule interacts with light in a unique way, creating a distinct pattern, much like a fingerprint. Optical spectroscopy, which involves shining a laser on a material and observing how... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.