
RADLogics
Founded Year
2010Stage
Acq - Fin | AliveAbout RADLogics
RADLogics is a healthcare software company offering an AI image analysis platform and applications supporting imaging data associated with CTs, MRIs, PET-CTs, and X-rays, to improve radiologists' productivity while enhancing patient outcomes. In addition to largest set of AI algorithms, the RADLogics cloud-based Virtual-Resident(tm) solution provides full integration with radiologists existing workflow environment.
RADLogics's Product Videos



ESPs containing RADLogics
The ESP matrix leverages data and analyst insight to identify and rank leading companies in a given technology landscape.
The radiology AI — diagnostics (multiple modalities) market utilizes artificial intelligence to improve patient outcomes and increase access to life-saving treatments. The market covers various imaging modalities such as CT, MRI, ECG, Echo, and X-ray, and conditions including stroke, aneurysm, and pulmonary embolism. This technology assists in coordinating patient care, providing faster diagnoses,…
RADLogics named as Challenger among 15 other companies, including Aidoc, Viz.ai, and Qure.ai.
RADLogics's Products & Differentiators
RADLogics AIMI
Software platform and AI algorithms to automatically detect findings on medical images typically associated with cancer
Expert Collections containing RADLogics
Expert Collections are analyst-curated lists that highlight the companies you need to know in the most important technology spaces.
RADLogics is included in 2 Expert Collections, including Artificial Intelligence.
Artificial Intelligence
10,944 items
Companies developing artificial intelligence solutions, including cross-industry applications, industry-specific products, and AI infrastructure solutions.
Digital Health
10,563 items
The digital health collection includes vendors developing software, platforms, sensor & robotic hardware, health data infrastructure, and tech-enabled services in healthcare. The list excludes pureplay pharma/biopharma, sequencing instruments, gene editing, and assistive tech.
RADLogics Patents
RADLogics has filed 5 patents.
The 3 most popular patent topics include:
- Health informatics
- Image processing
- Magnetic resonance imaging

Application Date | Grant Date | Title | Related Topics | Status |
---|---|---|---|---|
3/7/2014 | 4/19/2022 | Medical imaging, Health informatics, Image processing, Radiology, Telehealth | Grant |
Application Date | 3/7/2014 |
---|---|
Grant Date | 4/19/2022 |
Title | |
Related Topics | Medical imaging, Health informatics, Image processing, Radiology, Telehealth |
Status | Grant |
Latest RADLogics News
Mar 15, 2021
Share The Moscow Center for Diagnostics & Telemedicine presented clinical research findings during ECR 2021 highlighting that full integration of AI into radiology workflow during the pandemic increased radiologists’ productivity by saving an average of 7 minutes per radiology report RADLogics and the Moscow Center for Diagnostics & Telemedicine shared the results of a large-scale study conducted by the Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department. The clinical research found that the introduction of RADLogics’ AI-Powered solution into radiology workflow to analyze Chest-CT scans during the COVID-19 pandemic reduced report turnaround time by an average of 30 percent, which is equivalent to 7 minutes per case. Presented by Dr. Tatiana Logunova, MD, of the Research and Practical Clinical Center for Diagnostics and Telemedicine Technologies of the Moscow Health Care Department during the recent ECR 2021 conference, the extensive research included a total of 128,350 Chest-CT scans, of which 36,358 were processed by RADLogics AI-Powered COVID-19 solution, reported by 570 participating radiologists at over 130 hospitals and outpatient clinics in Moscow. “Early on in the pandemic, it was clear to us that COVID-19 required new healthcare management approaches, and effective clinical management depends more on disease severity than on the virus identification,” said Dr. Sergey Morozov, MD, PhD, MPH, who serves as CEO of Moscow Diagnostics and Telemedicine Center. “As a result, the aim of our research was to determine the impact of the introduction of AI-services analyzing Chest-CTs for COVID-19 related findings on the radiologists’ workflow and performance. In addition to finding that the integration of AI did not have a negative effect on the interpretation or report accuracy, our researchers found a significant improvement in productivity and report turnaround time by the expert radiologists that leveraged AI.” Related Posts The study was conducted over two separate phases with the first taking place between April 30, 2020 to June 18, 2020 and the second taking place between June 18, 2020 to August 31, 2020. The study found that report turnaround time was significantly shorter for all time periods in a group of radiologists with available AI results that were seamlessly integrated into radiologists’ current workflow, compared to a group with non-available AI results. In addition, in the shift between the two study time periods, additional clinical parameters were added to the standard of care, including the addition of a disease severity score. The added information created an increased workload on radiologists, which increased the average read time by more than 25 percent. In response, the RADLogics AI-Powered COVID-19 solution was enhanced to support the new clinical requirements. Results shown indicate that with the augmented AI solution, including all clinical measurements and severity scoring, was able to maintain the overall productivity gain of 30 percent. “We applaud this significant real-world research by Dr. Morozov and his team, who were on the frontline of Moscow’s successful fight against the COVID-19 pandemic while demonstrating the value of embracing new AI technologies to aid in these efforts,” said Moshe Becker , CEO and Co-Founder of RADLogics. “This study – first of its kind in its scale – demonstrates the full potential of AI as a tool to augment radiologists to increase throughput, improve efficiency and reduce time-to-treatment. This research provides large-scale clinical validation to an earlier academic study by UCLA that was published in Academic Radiology, which conducted a time-motion study using our AI-powered solution to measure the impact of our solution on radiologists’ productivity that found out using our solution saved up to 44 percent in radiologists’ reading time.” Since the start of the pandemic, RADLogics has responded with the deployment of the company’s AI-Powered medical image analysis solution worldwide. Designed for easy installation and integration both on-site and via the cloud, RADLogics’ algorithms are supported by the company’s patented software platform that enables rapid deployment at multiple hospitals, and seamless integration with existing workflows. In accordance with FDA guidance for imaging systems and software to address the COVID-19 public health emergency, RADLogics has made its FDA cleared CT and X-ray solutions available to hospitals and healthcare systems throughout the U.S. for patient triage and management. All the company’s AI-Powered solutions are available worldwide through major OEM distribution partners including Nuance via the AI Marketplace in the U.S. market. “In addition to the sheer scale of this research, it is important to note the demonstrated ability of our AI-powered solution to quickly adapt to the change in clinical requirements and maintain the overall performance as demonstrated in the second phase of the study,” added Becker. “In the near-term, responsive and scalable AI algorithms could play a critical role as healthcare systems across the world contend with potential coronavirus surges as new variants spread – not to mention the tremendous burnout and economic pressures across the healthcare sector. In the long-term, this groundbreaking research also illustrates the tremendous benefit of adopting robust AI platforms that can be deployed rapidly at scale and seamlessly integrated into existing workflows to augment radiology teams.”
RADLogics Frequently Asked Questions (FAQ)
When was RADLogics founded?
RADLogics was founded in 2010.
Where is RADLogics's headquarters?
RADLogics's headquarters is located at 11 Times Square, New York.
What is RADLogics's latest funding round?
RADLogics's latest funding round is Acq - Fin.
Who are the investors of RADLogics?
Investors of RADLogics include East Ocean Ventures and Tianjin Dazhen Asset Management.
Who are RADLogics's competitors?
Competitors of RADLogics include Viz.ai and 7 more.
What products does RADLogics offer?
RADLogics's products include RADLogics AIMI.
Compare RADLogics to Competitors

Ultromics provides autonomous echocardiography analysis through artificial intelligence (AI) solutions, empowering physicians to make decisions when diagnosing cardiovascular disease. Its cloud-based service, EchoGo, uses artificial intelligence to fully automate the pathway to diagnosis, providing reports for clinicians without any need for physical software on-site. The company was founded in 2017 and is based in Oxford, United Kingdom.
Kheiron Medical Technologies operates as a healthcare software company. It helps cancer patients by analyzing medical images and helps to enable the automation of radiology reporting tasks. It was formerly known as Maesterai. The company was founded in 2016 and is based in London, United Kingdom.

InformAI is a healthcare informatics company. The company develops predictive analytics tools to help in medical diagnosis at the point of care and extract data insights to improve patient outcomes. Its products focus on various medical conditions including cancer, cardiac/thoracic surgery, wound care, and sinus. InformAI was founded in 2017 and is based in Houston, Texas.

Aidoc operates as a healthcare technology company. It offers a Care Coordination platform that provides medical images to detect life-threatening conditions such as intracranial hemorrhage, brain aneurysm, pulmonary embolism, and more. Aidoc was founded in 2016 and is based in New York, New York.

Enlitic develops a diagnosis system that uses deep learning to analyze medical data in order to enable quick and more accurate detection of diseases that can be identified through medical images such as X-rays and CT scans.

Qure.ai provides an artificial intelligence (AI) based system to identify abnormalities in head computed tomography (CT) scans. It leverages deep learning to diagnose diseases from radiology and pathology imaging and create personalized cancer treatment plans from psychopathology imaging and genome sequences. The company was founded in 2016 and is based in Mumbai, India.