AI-powered imaging tools have been vital in the diagnosis of critical diseases in healthcare industries.
AI-powered imaging tools have contributed to improvements in the precision, economy, and safety of patient care. Apart from enabling ideal diagnosis or treatment on time leading to better health outcomes, it enables quality control and efficiency in the workflow. AI-powered imaging tools provide for automated risk stratification, which can be a powerful tool for identifying high-risk patients so they can receive specialized and optimized medical care. AI-powered imaging tools will definitely not eliminate radiologists but instead, will augment them in clinical diagnosis and clinical decision support, thereby helping reduce error and malpractice costs.
Enlitic uses Artificial Intelligence to distill actionable insights from billions of clinical cases by building solutions to help doctors leverage the collective intelligence of the medical community. Enlitic works with a wide range of partners and data sources to develop state-of-the-art clinical decision support products. Its AI-powered imaging tools can incorporate a wide range of unstructured medical data, including radiology and pathology images, laboratory results such as blood tests and EKGs, genomics, patient histories, and electronic health records (EHRs). This AI-based Medical Imaging tool allows higher accuracy and deeper insights for every patient.
2. Butterfly Network
Butterfly Network is a firm based in Guilford, Connecticut, that has introduced the Butterfly iQ portable ultrasound system. Butterfly Network, Inc. develops AI-powered imaging tools, designed to reduce the cost of real-time, three-dimensional imaging, and treatment. It consists of a portable transducer that connects directly to an iPhone, and an iOS app to display the images and to control settings. The AI-based Medical Imaging tool actually works as three different transducers thanks to an ultra-wideband matrix array.
Lunit is the first-ever, Real-time Imaging AI Analytics on the web. Lunit is an AI-powered imaging tool analysis software company. Founded in 2013, Lunit develops advanced AI-based Medical Imaging tool analytics and novel imaging biomarkers via cutting-edge deep learning technology, in order to empower healthcare practitioners to make more accurate, consistent, and efficient clinical decisions. Lunit INSIGHT is web-based AI-powered imaging tools software, developed as an imaging biomarker derived from large-scale medical image data.
ChironX deal uses a hybrid stack of complex and proprietary AI-powered imaging tools algorithms, in conjunction with classical machine learning techniques. There’s a lot of deep learning usage in some of its modules as well. It is a provider of an AI-powered imaging tools–based disease detection platform. The company employs machine learning and clinical imaging techniques where images can be screened on portable medical devices to diagnose software to detect complex diseases from medical images.
Aidoc is developing the most advanced healthcare-grade AI. The patent-pending technology analyzes all relevant AI-powered imaging tools and textual clinical data for comprehensive coverage of the study. Aidoc’s worklist widget empowers the radiologist to prioritize incoming cases with suspected findings. Aidoc was built by a team of deep learning experts and practicing radiologists, aimed at tackling the real technological challenges of AI-based Medical Imaging tools. AIDOC is a medical platform that makes use of the crypto network to help deliver users with a wide array of healthcare services.
Contextflow develops Artificial Intelligence technology for large medical image data. Motivated by bringing state-of-the-art research into clinical use, having an impact on providing better and more efficient care to patients, context flow shifted to focus on business development. With context flows supporting radiologists, it now has its latest deep learning-based technology ready to support them in their daily routine. Therefore, radiologists can easily get case-sensitive information, a summary of case descriptions, and distribution.
4Quant utilize the latest Big Data and Deep learning technology to extract meaningful, actionable information from images and videos. Its AI-powered imaging tools are involved in the entire cycle from experiment design to measurement to analysis and interpretation. It provides expertise in both static and dynamic X-ray imaging experiments on a wide variety of samples ranging from mouse bones to brain vasculature. It can help users design experiments, choose imaging modalities, scale up to a large number of samples, and interpret the results in order to gain high-quality, actionable information from imaging studies.
Quibim S.L. was created in late 2012 as an initiative from radiologists and biomedical engineers with recognized scientific careers, Quibim helps to improve human health by applying advanced and innovative AI-powered imaging tools techniques to radiological images in order to detect the changes produced by diseases and drugs in the body. The company was born as a spin-off of La Fa Health Research Institute in Valencia (Spain), the renowned research institute of La Fe Polytechnics and University Hospital. Quibim applies artificial intelligence and advanced computational models to radiological images.
Predible Health is a Banglore-based startup that builds AI-powered imaging tools software for radiology. It is an automated segmentation of the liver, enabling Surgical Planning and much more in just a couple of clicks. Prediblelung allows Malignancy scoring, Nodule tracking, and response assessment at the click of a button. It combines the power of Deep Learning and Cloud Computation to deliver the future of radiology reporting. Malignancy scoring helps to deliver non-invasive diagnosis with the help of high confidence malignancy detection and risk scoring of lung CT images.
Qure.ai uses cutting-edge AI-powered imaging tools to help diagnose disease and recommend personalized treatment plans from healthcare imaging data. Worldwide, the number of medical imaging procedures being performed is increasing several times faster than the number of doctors who can interpret them. Each scan is much more complex and information-rich than it used to be. Physician workload keeps increasing, as does the amount of information that they need to process before reaching a diagnosis.