Qure AI

1 review

Qure.ai is a pioneering health technology company that leverages artificial intelligence (AI to enhance the accuracy and efficiency of medical imaging diagnostics. By integrating deep learning algorithms with existing radiology equipment, Qure.ai provides automated interpretation of X-rays, CT scans, and ultrasounds, delivering results within seconds. This rapid analysis empowers healthcare professionals to make timely, informed decisions, ultimately improving patient outcomes and making quality healthcare more accessible and affordable worldwide. Key Features and Functionality: - qXR: An AI-driven tool that analyzes chest X-rays to detect over 30 abnormalities, including signs of tuberculosis and lung cancer, in less than a minute. - qER: Designed for brain CT scans, this solution aids in the rapid detection of traumatic brain injuries and strokes, facilitating quicker decision-making in emergency settings. - qCT: An AI-powered tool for chest CT scans, enabling early detection of lung nodules and other abnormalities, crucial for lung cancer screening programs. - qMSK: An innovative AI solution focused on identifying musculoskeletal abnormalities, including fractures, to assist in orthopedic diagnostics. - qTrack: A comprehensive disease management platform that offers end-to-end solutions for screening programs and case management, enhancing care coordination and monitoring through customized dashboards. Primary Value and User Solutions: Qure.ai addresses critical challenges in medical diagnostics by providing AI-powered tools that significantly reduce the time required for image interpretation, thereby expediting diagnosis and treatment. This is particularly vital in time-sensitive situations like stroke care, where rapid intervention can be life-saving. Additionally, by automating routine diagnostic tasks, Qure.ai alleviates the workload of radiologists, allowing them to focus on complex cases. The technology's compatibility with existing imaging equipment ensures seamless integration without the need for costly hardware upgrades, making advanced diagnostic capabilities accessible even in resource-limited settings. Overall, Qure.ai's solutions enhance diagnostic accuracy, streamline clinical workflows, and improve patient outcomes on a global scale.

TB Care Cascades

0 reviews

qTrack is an AI-powered platform designed to enhance tuberculosis (TB) care cascades by streamlining screening programs and case management. Leveraging advanced artificial intelligence, qTrack facilitates rapid and accurate analysis of chest X-rays, significantly reducing the time from initial screening to confirmed diagnosis. This efficiency not only accelerates patient care but also optimizes resource utilization within healthcare systems.

Chest X-ray Reporting

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qXR is an advanced AI-powered solution designed to enhance the efficiency and accuracy of chest X-ray interpretation. Trained on over 9 million scans and having processed more than 10.7 million, qXR delivers comprehensive reports in under 20 seconds, significantly reducing turnaround times by 40%. It identifies a wide range of abnormalities across the lungs, pleura, mediastinum, bones, diaphragm, and heart, aiding in the detection of conditions such as tuberculosis and lung cancer. With a 99% negative predictive value in segregating unremarkable chest X-rays, qXR effectively clears reporting backlogs and supports high-volume settings like teleradiology and immigration screenings. Its multilingual support and flexible deployment options, including cloud and on-premise, ensure seamless integration into diverse clinical environments.

Lung Nodule Management

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Qure.ai's Lung Nodule Management suite is an AI-driven solution designed to enhance the early detection and management of lung nodules, thereby facilitating prompt intervention and improving patient outcomes. This comprehensive suite integrates advanced algorithms to analyze chest X-rays and CT scans, providing clinicians with rapid, accurate, and detailed assessments of lung health.

Stroke & TBI

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qER by Qure.ai is an AI-powered solution designed to enhance the diagnosis and management of stroke and traumatic brain injury (TBI) through rapid and accurate analysis of non-contrast head CT scans. By integrating seamlessly into existing radiology workflows, qER prioritizes critical cases, enabling faster team activation and improved patient outcomes. The system detects and quantifies key abnormalities such as intracranial hemorrhages, cranial fractures, mass effect, and midline shifts, providing clinicians with comprehensive insights to make informed decisions promptly. With regulatory clearances including FDA 510(k) and CE Class IIb certifications, qER is a trusted tool in neuro-critical care settings.

MSK X-Ray Reporting

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qMSK is an AI-powered assistant designed to enhance the interpretation and reporting of musculoskeletal (MSK) X-rays, particularly in trauma cases. It analyzes radiographs across 15 anatomical regions—including the clavicle, ribs, shoulder, humerus, elbow, forearm, wrist, hand/fingers, hip, pelvis, femur, knee, tibia-fibula, ankle, and foot/toe—to detect signs of fractures. The system processes scans in under 20 seconds, providing outputs such as bounding boxes highlighting suspected fracture sites and summaries of AI findings.

qER

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From medical images to connected devices, the amount of medical data being generated is growing exponentially. This coupled with new forms of data such as the ones generated by genome sequencing and biosensors renders traditional diagnostic methods obsolete. At Qure, we are a team of passionate computer scientists, medical practitioners and bioinformaticians who are on a mission to make healthcare more accessible and affordable using the power of deep learning.

Heart Failure

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Qure.ai's qXR-HF is an advanced AI-powered solution designed to facilitate the early detection of heart failure risk through the analysis of chest X-rays. By leveraging deep learning algorithms, qXR-HF identifies critical indicators such as cardiomegaly (enlarged heart) and pleural effusion (fluid accumulation), which are commonly associated with heart failure. This technology aims to enhance diagnostic accuracy, reduce the likelihood of late or missed diagnoses, and ultimately improve patient care outcomes.