Abstract: The invention relates to system and methods for combined curve temperature and shape sensing and, more particularly, but not exclusively, to system and methods for combined curve temperature and shape sensing in an interventional elongated device. An aspect of some embodiments of the invention relates to monitoring a temperature within a body of a patient before, while and/or after providing a temperature dependent treatment. In some embodiments, the monitoring comprises receiving a plurality of temperature measurement data from a plurality of sensors located along an elongated interventional device from one or more elongated interventional devices.

Abstract: Broadly speaking, the present techniques provide a method for training a machine learning, ML, model to perform named entity recognition in data items within an environment, and a method for using a trained ML model to autonomously perform named entity recognition. Advantageously, the present techniques enable sensitive information located in data items to be protected, which thereby reduces risk of data items that contain sensitive information from being accessed or manipulated by anyone without the requisite authority. In other words, by knowing what data items contain, appropriate security policies can be applied to the data items, and actions with respect to the data items can be controlled. The present techniques may also enable efficient and effective extraction of sensitive information from large sets of data items.

Abstract: Broadly speaking, the present techniques provide an automatic way of classifying data items within an environment (e.g. a business, workplace, organisation, etc.), and applying data management policies based on the classifications. This is advantageous over existing techniques which require manual classification of data items, which is time consuming in environments where hundreds of new data items may be generated in a day or week. The present techniques use an embedding machine learning, ML, model to automatically determine the relevant classification label(s) for an unlabelled data item, which is then used to select and apply the relevant data management policy(ies).

Abstract: Systems and methods of predicting a neuropsychological state of a user, including: monitoring the user, by at least one camera coupled to a processor, wherein the processor is to determine user characteristics based on input from the at least one camera, correcting, by the processor, at least one of the determined user characteristics, wherein the correction is applied to at least one of movement data and lighting data, applying a machine learning (ML) algorithm to predict a neuropsychological state of the user, wherein the ML algorithm is trained on cognitive reactions and of the user, and adjusting output of the user's media based on the predicted neuropsychological state of the user.

Abstract: A system for position and/or shape-tracking of an elongated device including a shape sensor to estimate a position and orientation of the device at a plurality of points along the device, and a processor configured to: obtain a plurality of predetermined points along a tracked portion of the device; allocate, for each of the plurality of the predetermined points, a local energy function dependent on the estimated position and orientation of device that incorporates relevant mechanical and sensor measurement constraints; generate a resultant unified energy function for the full shape and position of the entire tracked portion of the device with respect to relative locations and orientation of adjacent plurality of the predetermined points, the unified energy function is constructed based on the allocated local energy functions and segmental energy functions; and calculate a fully localized curve along the tracked portion of the device by minimizing the energy function.

Abstract: The present techniques provide a method for automatically and quickly providing information after a data breach or incident in relation to data has occurred. The present application provides a method for issuing data incident notifications when data items naming specific entities have been accessed by someone who should not have access to them. This enables the entities to obtain information on the data items they are named in and which have been accessed. An index may be used to quickly identify the data items which are subject to an incident and which name entities. After these data items are identified, a notification list can be generated that shows each data item naming an entity. A system administrator or security officer can then generate a data incident notification to notify an entity about the impacted data items in which they are named.

Abstract: A system for automatically monitoring efficacy of security controls in a computer network, including a probe engine configurable with at least one set of rules relating to access permissions to data in the computer network, at least one security probe forming part of the probe engine and operative to automatically place, at at least one storage location within the computer network and with access permissions that are non-compliant with the at least one set of rules, simulated data corresponding to the data in the computer network and attempt to access the simulated data following the placement thereof, using access privileges satisfying the non-compliant access permissions, and a security monitoring and reporting module operative to provide a user sensible output indicating at least whether the attempt to access the simulated data was successful and, if so, reporting mitigating activities by the security controls in response to the successful attempt.

Abstract: Broadly speaking, the present techniques provide an automatic way of classifying data items within an environment (e.g. a business, workplace, organisation, etc.), and applying data management policies based on the classifications. This is advantageous over existing techniques which require manual classification of data items, which is time consuming in environments where hundreds of new data items may be generated in a day or week. The present techniques use an embedding machine learning, ML, model to automatically determine the relevant classification label(s) for an unlabelled data item, which is then used to select and apply the relevant data management policy(ies).

Abstract: There is provided herein a system and a method for guiding insertion of a gastroenteral tube including: an electromagnetic field generator configured to generate an electromagnetic field covering a treatment area; wherein said electromagnetic field generator is external to the patient; a registration sensor configured to mark anatomic locations on the patient's torso; a gastroenteral tube comprising a tip sensor configured to sense its position and/or orientation relative to the electromagnetic field generator; and a processing circuitry configured to: calculate an orientation of the subject relative to the field generator based on the anatomic locations marked by the registration sensor, load a predefined anatomic map representing a torso; aligning the map based on the anatomic locations marked by the registration sensor, and showing on the map a path of the gastroenteral tube insertion; wherein the path is generated according to changes in the strength of the electromagnetic field sensed by the tip sensor's

Abstract: A method of classifying a file, including extracting metadata from the file, assigning a classification for the file by applying a machine learning model that was trained to classify files based on the metadata, determining a confidence level representing an accuracy of the classification, wherein if the confidence level is below a threshold value analyze the content of the file to assign a classification for the file based on the content; and store the assigned file classification.

Abstract: Improved email security and prevention of phishing attacks using a Large Language Model (LLM) engine. A computerized method includes evaluating whether a digital message received at a Protected Entity is malicious or legitimate, by performing: (a) obtaining extracted data from documents and data repositories of the Protected Entity; feeding the extracted data into an LLM engine; and constructing an Organizational Context Index having vectors of LLM-generated embeddings that describe relations and roles of members and objects of the Protected Entity; (b) prompting the LLM to evaluate whether the digital message is malicious or legitimate, based on LLM analysis of a query envelope that includes at least: (i) content of the digital message, and (ii) meta-data of the digital message, and (iii) a set of LLM-based embeddings from the Organizational Context Index that pertain to that digital message.

Abstract: A system and method for controlling an interventional robotic system, including an elongated flexible device, including a non-deflectable section in a proximal part of the device, a deflectable section in a distal part of the device, a curve sensor, configured to sense a curve of the deflectable section, and steering wires to deflect the deflectable section, and a processing module including a curve tracking module and a robot controller, configured to calculate and perform steering actions by positioning each of the steering wires in a certain state, for bringing the device to a target pose, receive curve tracking data from the curve tracking module, and use the received curve tracking data as feedback to the robot controller, to determine a difference between a current pose of the device to the target pose of the device, and adjust the state of the steering wires to decrease the calculated difference.

Abstract: Device, system, and method for automatically detecting and classifying personally identifiable information (PII) in documents and files. A method includes performing a deterministic rule-based search, in a plurality of stored documents, for PII data-items. If the deterministic rule-based search indicates that a particular document is more likely than not to contain a PII data-items then the method includes: extracting a textual snippet from the particular document, wherein the textual snippets surrounds the PII data-item; adding the textual snippet and the particular document to one or more training datasets utilized for training a Large Language Model (LLM) configured to find PII data-items in documents for Named Entity Recognition (NER) in those documents.

Abstract: A method of classifying a file, including extracting metadata from the file, assigning a classification for the file by applying a machine learning model that was trained to classify files based on the metadata, determining a confidence level representing an accuracy of the classification, wherein if the confidence level is below a threshold value analyze the content of the file to assign a classification for the file based on the content; and store the assigned file classification.

Abstract: A system for automatically monitoring efficacy of security controls in a computer network, including a probe engine configurable with at least one set of rules relating to access permissions to data in the computer network, at least one security probe forming part of the probe engine and operative to automatically place, at at least one storage location within the computer network and with access permissions that are non-compliant with the at least one set of rules, simulated data corresponding to the data in the computer network and attempt to access the simulated data following the placement thereof, using access privileges satisfying the non-compliant access permissions, and a security monitoring and reporting module operative to provide a user sensible output indicating at least whether the attempt to access the simulated data was successful and, if so, reporting mitigating activities by the security controls in response to the successful attempt.

Abstract: An apparatus for displaying a moving region of interest located within a body includes a positioning system to determine a position and orientation (P&O) of a medical device as well as to track, using an internal position reference sensor, the motion of the region of interest over time. A compensation function block generates a motion compensation function based on the motion of the region of interest, which is configured to compensate for the motion of the region of interest between a first time, for example a time at which an image was acquired and a second time, for example a time at which a P&O of the device was measured. The measured P&O is corrected using the compensation function. A representation of the medical device is superimposed on the image in accordance with the corrected P&O.

Abstract: Systems and methods of predicting a neuropsychological state of a user, including: monitoring the user, by at least one camera coupled to a processor, wherein the processor is to determine user characteristics based on input from the at least one camera, correcting, by the processor, at least one of the determined user characteristics, wherein the correction is applied to at least one of movement data and lighting data, applying a machine learning (ML) algorithm to predict a neuropsychological state of the user, wherein the ML algorithm is trained on cognitive reactions and of the user, and adjusting output of the user's media based on the predicted neuropsychological state of the user.

Abstract: A system and a method for an insertion device positioning guidance system comprising: an electromagnetic field generator configured to generate an electromagnetic field covering a treatment area; a plate sensor configured to be positioned within the treatment area in a location defining an orientation of a subject; a reference sensor configured to be positioned, within the treatment area, on the subject's torso, the reference sensor is configured to define a reference coordinate system representing the position and orientation of the subject's torso relative to said field generator; a registration sensor configured to mark at least a first and a second anatomic locations relative to the reference coordinate system; and a processor configured to operate said field generator, read signals obtained from said the plate sensor, said reference sensor and said registration sensor, calculate a position and orientation thereof relative to said field generator, generate a 3D anatomic map representing the torso of the s

Abstract: There is provided herein a system and a method for an insertion device positioning guidance system comprising: an electromagnetic field generator configured to generate an electromagnetic field covering a treatment area; a plate sensor configured to be positioned within the treatment area in a location defining an orientation of a subject; a reference sensor configured to be positioned, within the treatment area, on the subject's torso, the reference sensor is configured to define a reference coordinate system representing the position and orientation of the subject's torso relative to said field generator; a registration sensor configured to mark at least a first and a second anatomic locations relative to the reference coordinate system; and a processor configured to operate said field generator, read signals obtained from said the plate sensor, said reference sensor and said registration sensor, calculate a position and orientation thereof relative to said field generator, generate a 3D anatomic map repres

Abstract: There is provided herein a system and a method for guiding insertion of a gastroenteral tube including: an electromagnetic field generator configured to generate an electromagnetic field covering a treatment area; wherein said electromagnetic field generator is external to the patient; a registration sensor configured to mark anatomic locations on the patient's torso; a gastroenteral tube comprising a tip sensor configured to sense its position and/or orientation relative to the electromagnetic field generator; and a processing circuitry configured to: calculate an orientation of the subject relative to the field generator based on the anatomic locations marked by the registration sensor, load a predefined anatomic map representing a torso; aligning the map based on the anatomic locations marked by the registration sensor, and showing on the map a path of the gastroenteral tube insertion; wherein the path is generated according to changes in the strength of the electromagnetic field sensed by the tip sensor's