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Annalise Enterprise is a device designed to be used in the medical care environment to aid in triage and prioritization of studies with features suggestive of the following findings: - pleural effusion* [1] - pneumoperitoneum* [2] - pneumothorax - tension pneumothorax - vertebral compression fracture* [3] *See additional information below. The device analyzes studies using an artificial intelligence algorithm to identify findings. It makes study-level output available to an order and imaging management system for worklist prioritization or triage. The device is not intended to direct attention to specific portions of an image and only provides notification for suspected findings. Its results are not intended: - to be used on a standalone basis for clinical decision making - to rule out specific findings, or otherwise preclude clinical assessment of chest X-ray studies **Intended modality:** Annalise Enterprise identifies suspected findings in digitized (CR) or digital (DX) chest X-ray studies. **Intended user:** The device is intended to be used by trained clinicians who are qualified to interpret chest X-ray studies as part of their scope of practice. **Intended patient population:** The intended population is patients who are 22 years or older. **Additional information:** The following additional information relates to the findings listed above: **[1] Pleural effusion** - specificity may be reduced in the presence of scarring and/or pleural thickening - standalone performance evaluation was performed on a dataset that included supine and erect positioning - use of this device with prone positioning may result in differences in performance **[2] Pneumoperitoneum** - standalone performance evaluation was performed on a dataset that included supine and erect positioning where most cases were of unilateral right-sided and bilateral pneumoperitoneum - use of this device with prone positioning and for unilateral left-sided pneumoperitoneum may result in differences in performance **[3] Vertebral compression fracture** - intended for prioritization or triage of worklists of Bone Health and Fracture Liaison Service program clinicians - standalone performance evaluation was performed on a dataset that included only erect positioning - use of this device with supine positioning may result in differences in performance

Annalise Enterprise is a software workflow tool which uses an artificial intelligence (AI) algorithm to identify suspected findings on chest X-ray studies in the medical care environment. The findings identified by the device include pneumothorax, tension pneumothorax, pleural effusion, pneumoperitoneum and vertebral compression fracture. Radiological findings are identified by the device using an AI algorithm – a convolutional neural network trained using deep-learning techniques. Images used to train the algorithm were sourced from datasets that included a range of equipment manufacturers including. This dataset, which contained over 750,000 chest X-ray imaging studies, was labelled by trained radiologists regarding the presence of the findings of interest. The performance of the device's AI algorithm was validated in a standalone performance evaluation, in which the case-level output from the device was compared with a reference standard ('ground truth'). This was determined by two ground truthers, with a third truther used in the event of disagreement. All truthers were US board-certified radiologists. The device interfaces with image and order management systems (such as PACS/RIS) to obtain chest X-ray studies for processing by the AI algorithm. Following processing, if any of the clinical findings of interest are identified in the study, the device provides a notification to the image and order management system for prioritization of that study in the worklist. This enables users to review the studies containing features suggestive of these clinical findings earlier than in the standard clinical workflow. It is important to note that the device will never decrease a study's existing priority in the worklist. This ensures that worklist items will never have their priorities downgraded based on AI results. The device workflow is performed parallel to and in conjunction with the standard clinical workflow for interpretation of chest X-ray studies. The device is intended to aid in prioritization and triage of radiological medical images only.

Rayvolve PTX-PE is a radiological computer-assisted triage and notification software that analyzes chest x-ray images (Postero-Anterior (PA) or Antero-Posterior (AP)) of patients 18 years of age or older for the presence of pre-specified suspected critical findings (pleural effusion and/or pneumothorax). Rayvolve PTX-PE uses an artificial intelligence algorithm to analyze the images for features suggestive of critical findings and provides study-level output available in DICOM node servers for worklist prioritization or triage. As a passive notification for prioritization-only software tool within the standard of care workflow, Rayvolve PTX-PE does not send a proactive alert directly to a trained medical specialist. Rayvolve PTX-PE is not intended to direct attention to specific portions of an image. Its results are not intended to be used on a stand-alone basis for clinical decision-making.

Rayvolve PTX-PE is a software-only device designed to help healthcare professionals. It's a radiological computer-assisted triage and notification software that analyzes chest x-ray imaqes (Postero-Anterior (PA) or Antero-Posterior (AP)) of patients of 18 years of age or older for the presence of pre-specified suspected critical findings (pleural effusion and/or pneumothorax). It is intended to work in combination with DICOM node servers. Rayvolve PTX-PE has been developed to use the current edition of the DICOM image standard. DICOM is the international standard for transmitting, storing, retrieving, printing, processing, and displaying medical imaging. Using the DICOM standard allows Rayvolve PTX-PE to interact with existing DICOM node servers (eg .: PACS), and clinical-grade image viewers. The device is designed to run on a cloud platform and be connected to the radiology center's local network. It can also interact with the DICOM Node server. When remotely connected to a medical center DICOM Node server, the software utilizes Al-based analysis algorithms to analyze chest X-rays for features suggestive of critical findings and provide study-level outputs to the DICOM node server for worklist prioritization. Following receipt of chest X-rays, the software device automatically analyzes each image to detect features suggestive of pneumothorax and/or pleural effusion. Rayvolve PTX-PE filters and downloads only X-rays with organs determined from the DICOM Node server. As a passive notification for prioritization-only software tool within the standard of care workflow, Rayvolve PTX-PE does not send a proactive alert directly to a trained health professional. Rayvolve PTX-PE is not intended to direct attention to a specific portion of an image. Its results are not intended to be used on a stand-alone basis for clinical decision-making. Rayvolve PTX-PE does not intend to replace medical doctors. The instructions for use are strictly and systematically transmitted to each user and used to train them on Rayvolve's use.

BriefCase-Triage is a radiological computer aided triage and notification software indicated for use in the analysis of CT images with or without contrast that include the ribs, in adults or transitional adolescents aged 18 and older. The device is intended to assist hospital networks and appropriately trained medical specialists in workflow triage by flagging and communicating suspect cases of three or more acute Rib fracture (RibFx) pathologies. BriefCase-Triage uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings in parallel to the ongoing standard of care image interpretation. The user is presented with notifications for cases with suspected RibFx findings. Notifications include compressed preview images that are meant for informational purposes only, and not intended for diagnostic use beyond notification. The device does not alter the original medical image and is not intended to be used as a diagnostic device. The results of BriefCase-Triage are intended to be used in conjunction with other patient information and based on their professional judgment, to assist with triage/prioritization of medical images. Notified clinicians are responsible for viewing full images per the standard of care.

BriefCase-Triage is a radiological computer-assisted triage and notification software device. The software is based on an algorithm programmed component and is intended to run on a linuxbased server in a cloud environment. The BriefCase-Triage receives filtered DICOM Images, and processes them chronologically by running the algorithms on each series to detect suspected cases. Following the Al processing, the output of the algorithm analysis is transferred to an image review software (desktop application). When a suspected case is detected, the user receives a pop-up notification and is presented with a compressed, low-quality, grayscale image that is captioned "not for diagnostic use, for prioritization only" which is displayed as a preview function. This preview is meant for informational purposes only, does not contain any marking of the findings, and is not intended for primary diagnosis beyond notification. Presenting the users with worklist prioritization facilitates efficient triage by prompting the user to assess the relevant original images in the PACS. Thus, the suspect case receives attention earlier than would have been the case in the standard of care practice alone.

VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is a radiological computer-assisted triage and notification software that analyzes adult chest X-ray images for the presence of prespecified suspected critical findings (pleural effusion and/or pneumothorax). VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage uses an artificial intelligence algorithm to analyze images for features suggestive of critical findings and provides case-level output available in the PACS/ workstation for worklist prioritization or triage. As a passive notification for prioritization-only software tool within standard of care workflow, VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage does not send a proactive alert directly to the appropriately trained medical specialists. VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is not intended to direct attention to specific portions of an image or to anomalies other than pleural effusion and/or pneumothorax. Its results are not intended to be used on a stand-alone basis for clinical decision-making.

VUNO Med-Chest X-ray Triage/VUNO Med-CXR Link Triage is an automated computerassisted triage and notification software that analyzes adult chest X-ray images for the presence of pleural effusion and pneumothorax. It is based on an artificial intelligence analysis model, specifically a convolutional network (CNN), which employs deep learning technology to learn features from data. The training data is sourced from 4 distinct sites of South Korea and India data provider, including medical imaging centers, data partners, and medical hospitals, and over 13 different modality manufacturers such as GE. Philps, FUJI, Canon, Samsung, SIEMENS, etc. A "locked" algorithm is used, and the same input gives the same results every time. The software receives an image of a frontal chest radiograph and automatically analyzes it for the presence of pre-specified critical findings. If any findings are suspected, the image is flagged, and a passive notification is provided to the user. Subsequently, trained radiologists or healthcare professionals should make the final decision which is the standard of care at present. A user interface is provided for visualization, displaying the loaded image and any detected findings. The data can be transmitted from Picture Archive and Communications Systems (PACS) using the DICOM protocol.

CINA-VCF is a radiological computer aided triage and notification software indicated for use in patients aged 50 years and over undergoing non-enhanced or contrast-enhanced CT scans which include the chest and/or abdomen. The device is intended to assist hospital networks and appropriately trained medical specialists within the standard-of-care bone health setting in workflow triage by flagging and communication of suspected positive cases of Vertebral Compression Fractures (VCF) findings. CINA-VCF uses an artificial intelligence algorithm to analyze images and highlight cases with detected findings on a standalone application in parallel to the ongoing standard of care image interpretation. The device does not alter the original medical image, and it is not intended to be used as a diagnostic device. The results of CINA-VCF are intended to be used in conjunction with other patient information and based on professional judgment to assist with triage/prioritization of medical images. Notified clinicians are ultimately responsible for reviewing full images per the standard of care.

CINA-VCF is a radiological computer-assisted triage and notification software device. CINA-VCF runs on a standard "off the shelf" server/workstation and consists of VCF Image Processing Application, which can be integrated, deployed and used with the CINA Platform (cleared under K200855) or other compatible medical image communications devices. CINA-VCF receives nonenhanced or contrast-enhanced CT scans (which include the chest and/or abdomen) identified by the CINA Platform or other compatible medical image communications device, processes them using algorithmic methods involving execution of multiple computational steps to identify suspected presence of Vertebral Compression Fractures (VCF) findings and generates results files to be transferred by CINA Platform or a similar medical image communications device for output to a PACS system or workstation for worklist prioritization. DICOM images are received, recorded and filtered before processing. The series are processed chronologically by running algorithms on each series to detect suspected positive findings of a vertebral compressions fracture (VCF). The device uses deep learning models to detect VCF at the T1-L5 level. The models were trained endto-end on a dataset of 886 series collected from multiple centers in the USA and France satisfying the device protocol and representing a large distribution of scanner models from Siemens, Philips, GE and Canon (formerly Toshiba), acquisition protocols, spine presentation and fracture location and severity. Additional models, trained on subsets of this dataset, are used to locate the spine, identify the vertebra bodies and exclude vertebra which have been subjected to vertebroplasty or contains orthopedic material. The Worklist Application displays all incoming suspect cases, each notified case is marked with an icon. In addition, compressed, grayscale, unannotated images that are captioned "not for diagnostic use" is displayed as a preview function. This compressed preview is meant for informational purposes only, does not contain any marking of the findings, and is not intended for diagnostic use beyond notification. Presenting the specialist with worklist prioritization facilitates earlier triage by allowing prioritization of images in the PACS. Thus, the suspect case receives attention earlier than would have been the case in the standard of care practice alone. The CINA Platform is an example of medical image communications platform for integrating and deploying the CINA-VCF image processing applications. It provides the necessary requirements for interoperability based on the standardized DICOM protocol and services to communicate with existing systems in the hospital radiology department such as CT modalities or other DICOM nodes (DICOM router or PACS for example). It is responsible for transferring, converting formats, notifying of suspected findings and displaying medical device data such as radiological data. The CINA Platform server includes the Worklist client application which receives notifications from the CINA-VCF Image Processing application.

The VinDr-Mammo is a passive notification for prioritization-only, a parallel-workflow software tool used by MQSA qualified interpreting physicians to prioritize patients with suspicious findings in the medical care environment. VinDr-Mammo utilizes an artificial intelligence algorithm to analyze 2D FFDM screening mammograms and flags those that are suggestive of the presence of at least one suspicious finding at the exam-level. VinDr-Mammo produces an exam-level output to a PACS/ Workstation for flagging the suspicious case and allows worklist prioritization. MQSA qualified interpreting physicians are responsible for reviewing each exam on a display approved for use in mammography, according to the current standard of care. VinDr-Mammo device is limited to the categorization of exams, does not provide any diagnostic information beyond triage and prioritization, does not remove images from the interpreting physician's worklist, and should not be used in lieu of full patient evaluation, or relied upon to make or confirm diagnosis. The VinDr-Mammo device is intended for use with complete 2D FFDM mammography exams acquired using validated FFDM systems only.

The VinDr-Mammo is an innovative medical device designed to assist in the analysis and triage of 2D full-field digital mammogram (FFDM) screening mammograms. Operating as non-invasive computer-assisted software, known as SaMD, it employs a machine learning algorithm to identify potential suspicious findings within the images. Once identified, the system promptly notifies a PACS/workstation for further examination. This passive-notification feature enables radiologists to prioritize their workload efficiently and view studies in order of importance using standard PACS or workstation viewing software. It is important to note that the VinDr-Mammo software is intended solely to aid in the prioritization and triage of radiological medical images. It serves as a valuable tool for MQSA interpreting physicians who specialize in mammogram readings, complementing the standard of care. It should be emphasized that the device does not replace the need for a comprehensive evaluation as per established medical practices. During the algorithm's training, independent datasets from various global sites were utilized, ensuring a robust and diverse training experience. The VinDr-Mammo code can be viewed by radiologists on a Picture Archiving and Communication System (PACS), Electronic Patient Record (EPR), and/or Radiology Information System (RIS) worklist and can be used to reorder the worklist: the mammographic studies with code 1 should be prioritized over those with code 0 and, thus, should be moved to the top of the worklist. As a software-only device, VinDr-Mammo can be hosted on a compatible host server connected to the necessary clinical IT systems such that DICOM studies can be received and the resulting outputs returned where they can be incorporated into the radiology worklist. The following modules compose the VinDr-Mammo software: - Data input and validation: Following retrieval of a study, the validation feature assessed the input data (i.e. age, modality, view) to ensure compatibility for processing by the algorithm. - VinDr-Mammo algorithm: Once a study has been validated, the algorithm analyzes the 2D FFDM screening mammogram for detection of suspected findings. - API Cognitive service: The study analysis and the results of a successful study analysis are provided through an API service, whose outputs will then be sent to the appropriate clinical IT system for viewing on a radiology worklist. - Error codes feature: In the case of a study failure during data validation or the analysis by the algorithm, an error is provided to the system.

SmartChest is a radiological computer assisted triage and notification software that analyzes frontal chest X-ray images (Postero-Anterior (PA) or Antero-Posterior (AP)) of transitional adolescents (18 -21 yo but treated like adults) and adults (≥22 yo) for the presence of suspected pleural effusion and/or pneumothorax. SmartChest uses an artificial intelligence algorithm to analyze the images for features suggestive of critical findings and provides case-level output available to a PACS (or other DICOM storage platforms) for worklist prioritization. As a passive notification for prioritization-only software tool within the standard of care workflow, SmartChest does not send a proactive alert directly to a trained medical specialist. SmartChest is not intended to direct attention to a specific portion of an image. Its results are not intended to be used on a stand-alone basis for clinical decision-making.

Smart Chest is a radiological computer assisted triage and notification software that analyzes (Postero-Anterior (PA) and/or Antero-Posterior (AP)) of transitional adolescents (18 ≤ age ≤ 21 yo but treated like adults) and adults (22 yo ≤ age) for the presence of suspected pleural effusion and/or pneumothorax. The software utilizes Al-based image analysis algorithms to detect the findings. SmartChest provides case-level output available in the worklist prioritization by appropriately trained medical specialists qualified to interpret chest radiographs are automatically received from the user's image acquisition or storage systems (e.g., PACS, other DICOM storage platforms) and processed by SmartChest for analysis. After receiving Chest X-Ray images, the device automatically analyzes the images and identifies pre-spectied findings (pleural effusion and/or pneumothorax). Then the analysis results are passively sent by SmartChest yia a notfication to the worklist software being used (PACS, or other platforms). The results are made available via a newly generated DICOM series (containing a secondary capture image), where DICOM tags contains the following information: 1. "SUSPECTED FINDING" or "CASE PROCESSED" if the algorithm ran successfully, "NOT PROCESSED" if the algorithm receives a study containing chest images that are not part of the intended use (lateral views or excluded age for example). 2. "SUSPECTED PLEURAL EFFUSION" OR "SUSPECTED PNEUMOTHORAX" if one pre-specified finding category identified OR, 3."SUSPECTED PLEURAL EFFUSION, PNEUMOTHORAX" if the two pre-specified finding categories identified - 4. The secondary capture image returned in the storage system indicates at the study-level: - The number of images received by SmartChest, - The number of images processed by SmartChest, - The status of the study: "NOT PROCESSED", "SUSPECTED FINDING" or "CASE PROCESSED". The DICOM storage component may be a Picture Archiving and Communications (PACS) system or other local storage platforms. This would allow the appropriately trained medical specialists to group suspicious exams together that may potentially benefit their prioritization. Chest radiographs without an identified anomaly are placed in the worklist for routine review, which is the current standard of care. The device is not intended to be a rule-out device and for cases that have been processed by the device without notification for prespecified suspected findings it should not be viewed as indicating that the pre-specified findings are excluded. SmartChest device does not alter the order nor remove imaging exams from the interpretation queue. Unflagged cases should still be interpreted by medical specialists. The notification is contextual and does not provide any diagnostic information. The results are not intended to be used on a stand-alone basis for clinical decision-making. The summary image will display the following statement: "The product is not for Diagnostic Use-For Prioritization Only".

RADIFY® Triage is a radiological computer-assisted triage and notification software that analyzes adult chest X-ray images for the presence of pre-specified suspected critical findings (pleural effusion and/or pneumothorax). RADIFY® Triage uses an artificial intelligence algorithm to analyze images for features suggestive of critical findings and provides case-level output available in the PACS for worklist prioritization or triage. As a passive notification for prioritization-only software tool within the standard of care workflow, RADIFY® Triage does not send a proactive alert directly to the appropriately trained medical specialists. The product is not intended to direct attention to specific portions of an image. Its results are not intended to be used on a stand-alone basis for clinical decision-making. The device does not remove the cases from the queue and does not flag the condition as being absent.

RADIFY® Triage is a radiological computer-assisted prioritization software that utilizes Albased image analysis algorithms to identify pre-specified critical findings (pleural effusion and/or pneumothorax) on frontal (AP and PA) views chest X-ray images and flag the images in the PACS to enable worklist prioritization by the appropriately trained medical specialists who are qualified to interpret chest radiographs. The software does not alter the order or remove cases from the reading queue. The algorithm was trained on datasets from US and non-USA sources. This training dataset consisted of 93.7% of the data from South Africa, and 6.3% of the data from the USA. The input for RADIFY® Triage is a frontal chest x-ray (AP and PA view) in digital imaging and communications in medicine (DICOM) format. Chest X-rays are sent to RADIFY® Triage via PACS (Picture Archiving and Communication System (PACS) and processed by the device for analysis. Following receipt of chest x-rays, the software device automatically analyses each image to detect features suggestive of pneumothorax and/or pleural effusion. Chest x-rays without the suspicious findings are placed in the worklist for routine review, which is the standard of care. RADIFY® Triage does not provide any proactive alerts and is not intended to direct attention to specific portions of the image. The results are not intended to be used on a standalone basis for clinical decision-making nor is it intended to rule out the target conditions or otherwise preclude clinical assessment of x-ray cases.

BraveCX is a radiological computer-assisted triage and notification software that analyzes adult (≥18 years old) chest Xray images for the presence of pre-specified suspected critical findings (pleural effusion and/or pneumothorax). BraveCX uses an artificial intelligence algorithm to analyze images for features suggestive of critical findings and provides caselevel output available in the PACS/workstation for worklist prioritization or triage. As a passive notification for prioritization-only software tool within standard of care workflow, BraveCX does not send a proactive alert directly to the appropriately trained medical specialists. BraveCX is not intended to direct attention to specific portions of an image or to anomalies other than pleural effusion and/or pneumothorax. Its results are not intended to be used on a stand-alone basis for clinical decision-making.

BraveCX is a Deep Learning Artificial Intelligence (AI) software that analyzes adult (≥18 years old) chest X-ray images for the presence of pre-specified suspected critical findings (pleural effusion and/or pneumothorax. It uses deep learning to analyze each image to identify features suggestive of pleural effusion and/or pneumothorax. Upon image acquisition from other radiological imaging equipment (e.g. X-ray systems), Anteroposterior (AP) and Posteroanterior (PA) chest X-Rays are received and processed by BraveCX. Following receipt of an image, BraveCX de-identifies a copy of each DICOM file and analyses it for features suggestive of pleural effusion and/or pneumothorax. Based on the analysis result, the software notifies PACS/workstation for the presence of the critical findings, indicated by "flag" or "(blank)". This allows the appropriately trained medical specialists to group suspicious exams together with potential for prioritization. Chest radiographs without an identified anomaly are placed in the worklist for routine review, which is the current standard of care. The intended user of the BraveCX software is a health care professional such as radiologist or another appropriately trained clinician. The software does not alter the order or remove cases from the reading queue. The software output to the user is a label of "flag" or "(blank)" that relates to the likelihood of presence of pneumothorax and/or pleural effusion. BraveCX platform ingests prediction requests with either attached DICOM images or DICOM UIDs referencing images already uploaded to DICOM storage. The results will be made available via a newly generated DICOM that is stored in DICOM storage or as a JSON file. The DICOM storage component may be a Picture Archiving and Communications (PACS) system or some other local storage platform. BraveCX works in parallel to and in conjunction with the standard of care workflow to enable prioritized review by the appropriately trained medical specialists who are qualified to interpret chest radiographs. As a passive notification for prioritization-only software tool within standard of care workflow, BraveCX does not send a proactive alert directly to the appropriately trained medical specialists who are qualified to interpret chest radiographs. BraveCX is not intended to direct attention to specific portions or anomalies of an image and it should not be used on a standalone basis for clinical decision-making. BraveCX automatically runs after image acquisition. It prioritises and displays the analysis results through the worklist interface of PACS/workstation. An on-device, technologist notification is generated within 15 minutes after interpretation by the user, indicating which cases were prioritized by BraveCX in PACS. The technologist notification is contextual and does not provide any diagnostic information. The on-device, technologist notification is not intended to inform any clinical decision, prioritization, or action.

qXR-PTX-PE is a radiological computer-assisted triage and notification software that analyzes adult chest X-ray images for the presence of pre-specified suspected critical findings (pleural effusion and/or pneumothorax). qXR-PTX-PE uses an artificial intelligence algorithm to analyze images for features suggestive of critical findings and provides case-level output available in the PACS/workstation for worklist prioritization or triage. As a passive notification for prioritization-only software tool within standard of care workflow, qXR-PTX-PE does not send a proactive alert directly to the appropriately trained medical specialists. qXR-PTX-PE is not intended to direct attention to specific portions of an image or to anomalies other than pleural effusion and/or pneumothorax. Its results are not intended to be used on a stand-alone basis for clinical decision-making.

qXR-PTX-PE is a radiological computer aided triage and notification software that analyses adult frontal (AP or PA views) CXR images for the presence of pre-specified suspected target conditions (pleural effusion and/or pneumothorax). The algorithm was trained on training data from across the world. The training dataset consisted of 74% of the data from India, 20.04% from the EU, 3.9% from the US, 1.4% from Brazil and 0.63% from Vietnam. The input for qXR-PTX-PE is a frontal chest X-ray (AP and PA view) in digital imaging and communications in medicine (DICOM) format Chest X-rays are sent to qXR-PTX-PE by the means of transmission within the user's image storage system (e.g., Picture Archiving and Communication System (PACS)) or other radiological imaging equipment (e.g., X-ray systems) and processed by the qXR-PTX-PE for analysis. Following receipt of chest radiographs, the software device automatically analyses each image to detect features suggestive of pneumothorax and/or pleural effusion. This would allow the appropriately trained medical specialists to group suspicious exams together that may potentially benefit for their prioritization. Chest radiographs without the suspicious findings are placed in the worklist for routine review, which is the standard of care at present. A secondary capture is available for the information on presence of the suspicious findings. qXR-PTX-PE does not provide any proactive alerts. qXR-PTX-PE is not intended to direct attention to specific portions of the image. The results are not intended to be used on a standalone basis for clinical decision-making nor is it intended to rule out the target conditions or otherwise preclude clinical assessment of X-Ray cases.