A method and system for visual presentation of genetic test reports

Abstract

This application discloses a method and system for visualizing gene testing reports, relating to the field of information visualization technology. The method includes the following steps: acquiring user interaction data on information items and risk markers for those items; identifying unreviewed potential abnormal items based on the risk markers and interaction data, and generating an information omission risk indicator; providing guidance information to encourage the user to focus on unreviewed potential abnormal items based on the information omission risk indicator; recording potential abnormal items that the user has been guided to focus on as reviewed; upon receiving a user-triggered instruction representing a final diagnostic decision, checking whether unreviewed potential abnormal items exist in the gene testing report; if so, interrupting the instruction and presenting a prompt interface for the user to choose to continue the decision or return to the report. This application can reduce the user's cognitive load, decrease the probability of key variants being missed during decision-making, and ensure the accuracy of diagnosis and treatment.

Description

Technical Field

[0001] This application relates to the field of information visualization technology, and in particular to a method and system for visualizing gene testing reports. Background Technology

[0002] Genetic testing reports play a crucial role in clinical diagnosis and treatment; however, their highly specialized content and information density make it difficult for doctors to quickly grasp key information using traditional static presentation methods, severely impacting diagnostic efficiency. To improve this situation, existing technologies have proposed visual presentation systems for genetic testing reports, enhancing information comprehension efficiency through graphical interfaces. However, these systems still face significant challenges in handling novel genetic data formats, managing information overload, and ensuring the accurate transmission of critical information.

[0003] Specifically, when the system's underlying data filtering logic malfunctions due to incompatibility with new data formats, a large number of clinically significant pathogenic variants may be misclassified as "of unknown clinical significance." To adhere to the design principle of information integrity, the system displays all variants marked as "of unknown clinical significance," leading to a dramatic increase in information overload and a dense, lengthy variant list. This information overload severely disrupts doctors' focus, making it difficult for them to quickly locate key variants and ultimately reducing interpretation efficiency.

[0004] In applications such as multi-report comparison, the system automatically compresses displayed content to accommodate an exceptionally large amount of information within a limited display space. This results in excessively small fonts and a crowded layout, significantly increasing the difficulty of identification and causing visual fatigue for doctors. More seriously, when doctors rely on color coding for rapid risk assessment when encountering difficulties in identification, high-risk variants may be marked with low-alert colors due to underlying classification errors, making them visually inconspicuous and easily overlooked during rapid browsing. This combination of underlying logical errors, interface compression, and misleading colors not only increases the user's cognitive load but may also lead to the omission of key variants during decision-making, posing a potential threat to the accuracy of diagnosis and treatment. Summary of the Invention

[0005] This application aims to address at least one of the technical problems existing in the prior art. To this end, this application proposes a method and system for visualizing gene testing reports, aiming to solve the technical problems of existing gene testing report visualization systems, such as increased user cognitive load, omission of key variants during decision-making, and potential threats to diagnostic accuracy caused by errors in the underlying data screening logic.

[0006] Firstly, this application provides a method for visually presenting a gene testing report, comprising the following steps:

[0007] Acquire user interaction data on information items and risk markers for information items on the genetic testing report interface;

[0008] Based on the risk markers and the interaction behavior data, unreviewed potential anomaly entries are identified, and an information omission risk indication is generated based on the unreviewed potential anomaly entries.

[0009] Based on the information omission risk indication, provide guidance information to make users pay attention to the unreviewed potential abnormal entries;

[0010] Potentially abnormal entries that users have been guided to pay attention to via the aforementioned guidance information will be recorded as reviewed.

[0011] Upon receiving a user-triggered instruction representing the final diagnosis and treatment decision, check the gene testing report for any unreviewed potential abnormal entries.

[0012] If any unexamined potential anomalies are found, the instruction is interrupted and a prompt interface is displayed, allowing the user to choose whether to continue the decision or return to view the previous content.

[0013] In some embodiments of this application, the interaction behavior data includes a attention duration parameter for characterizing the degree of attention a user pays to an information item. The attention duration parameter is determined based on pointer hover time obtained by listening to pointer device events or gaze focusing time obtained by processing eye-tracking sensor data.

[0014] In some embodiments of this application, the step of determining unreviewed potential anomaly entries based on the risk markers and the interaction behavior data, and generating an information omission risk indication based on the unreviewed potential anomaly entries, includes:

[0015] Based on the risk markers, potential abnormal entries are identified from the information entries, and the duration of user attention to potential abnormal entries is obtained based on the interaction behavior data.

[0016] Determine whether the attention duration parameter meets the condition of being less than the dynamically adjusted attention duration threshold;

[0017] Add potential anomalies that meet the above conditions to the set of items to be reviewed;

[0018] Based on the set of items to be reviewed, the information omission risk indication is generated.

[0019] In some embodiments of this application, the attention duration threshold is dynamically adjusted based on the average attention duration required to effectively review different categories of information items in the user's historical operation information.

[0020] In some embodiments of this application, the step of providing guidance information to draw the user's attention to the unreviewed potentially anomalous entries based on the information omission risk indication includes:

[0021] Based on the aforementioned information omission risk indication, count the number of potentially abnormal entries that have not been reviewed in the current gene testing report;

[0022] At a predetermined location in the report display area, guidance information containing the number of entries is presented. This guidance information is configured to initiate a review process for potentially problematic entries that have not been reviewed in response to user actions.

[0023] In some embodiments of this application, the step of presenting guidance information containing the number of entries at a predetermined location in the report display area, the guidance information being configured to initiate a review process for unreviewed potentially problematic entries in response to a user action, includes:

[0024] At a predetermined location in the report display area, guiding information containing the number of items is presented;

[0025] In response to the trigger signal of the guidance information, potential abnormal entries to be reviewed are determined from the unreviewed potential abnormal entries according to preset priority rules;

[0026] Adjust the report display area to highlight the potential anomalies to be reviewed, thereby initiating the review process for unreviewed potential anomalies.

[0027] In some embodiments of this application, the step of responding to the trigger signal of the guidance information and determining potential anomaly entries to be reviewed from the unreviewed potential anomaly entries according to a preset priority rule includes:

[0028] In response to the trigger signal of the guidance information, the unexamined potential abnormal entries are divided into at least one group according to the type corresponding to the risk mark;

[0029] Based on the order in which the potential abnormal entries appear in the gene testing report, the potential abnormal entries within each group are sorted.

[0030] All groups are sorted according to the priority level of the type corresponding to the risk marker to form a group review sequence;

[0031] Based on the group review sequence and the order of potential anomalies within each group, the potential anomalies to be reviewed are determined sequentially.

[0032] In some embodiments of this application, the step of adjusting the report display area to highlight the potential anomaly entries to be reviewed in the display area to initiate the review process for unreviewed potential anomaly entries includes:

[0033] Dynamically calculate the visibility score of potential anomalies to be reviewed in the currently displayed interface:

[0034] The report display area is dynamically adjusted based on the visibility score, and the potential abnormal items to be reviewed are guided to the center of the visual field of the report display area through smooth scrolling and visual transition effects.

[0035] After the potential abnormal item to be reviewed enters the central area of ​​the field of view, a pulsed highlight border and background color temperature adjustment are applied to the potential abnormal item to make it stand out and initiate the review process for the unreviewed potential abnormal item.

[0036] In some embodiments of this application, the step of applying a pulsed highlight border and adjusting the background color temperature to the potential abnormal item after it enters the central area of ​​the field of view to make the potential abnormal item stand out and initiate the review process for the unreviewed potential abnormal item includes:

[0037] After the potential abnormal item to be reviewed enters the central area of ​​the field of view, the ambient light intensity information of the current display device and the user's physiological state indicators are obtained.

[0038] Based on the ambient light intensity information and physiological state indicators, the user's current visual comfort index is calculated;

[0039] Based on the visual comfort index, the flashing frequency and brightness of the pulsed high-brightness border, as well as the hue and intensity of the background color temperature adjustment, are dynamically adjusted.

[0040] Applying an adjusted pulsed highlight border and background color temperature adjustment to the potential anomaly entries makes them stand out, thereby initiating the review process for unreviewed potential anomalies.

[0041] Secondly, this application also provides a visualization system for gene testing reports, including:

[0042] The acquisition module is used to acquire user interaction data on information items and risk markers for information items on the genetic testing report interface;

[0043] The indication module is used to determine unreviewed potential abnormal entries based on the risk markers and the interaction behavior data, and to generate an information omission risk indication based on the unreviewed potential abnormal entries;

[0044] The guidance module is used to provide guidance information based on the information omission risk indication to make the user pay attention to the unreviewed potential abnormal entries;

[0045] The recording module is used to record potentially abnormal items that the user has been guided to pay attention to via the guidance information as having been reviewed.

[0046] The recognition module is used to recognize the decision commands issued by the user;

[0047] The verification module is used to verify whether there are any unreviewed potential abnormal entries in the gene testing report after receiving a user-triggered instruction that represents the final diagnosis and treatment decision.

[0048] The interrupt module is used to interrupt the instruction and present a prompt interface for the user to choose to continue the decision or return to view if there are unexamined potential abnormal entries.

[0049] The technical solution according to the embodiments of this application has at least the following beneficial effects:

[0050] In summary, this application effectively addresses the core challenges of existing technologies in the visualization of gene testing reports, such as information overload, omission of key information, and decision-making risks, through key steps including intelligent identification of potential anomalies, proactive guidance of user attention, and mandatory pre-decision verification. It provides a safer, more efficient, and accurate auxiliary tool for clinical diagnosis and treatment, reduces the cognitive load on users, lowers the probability of key variants being missed during decision-making, and ensures the accuracy of diagnosis and treatment.

[0051] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0052] The accompanying drawings are used to provide a further understanding of the technical solutions of this application and constitute a part of the specification. They are used together with the embodiments of this application to explain the technical solutions of this application and do not constitute a limitation on the technical solutions of this application.

[0053] Figure 1 This is a flowchart illustrating a method for visualizing a gene testing report, as provided in an embodiment of this application.

[0054] Figure 2 This is a schematic diagram of the architecture of a gene testing report visualization system provided in an embodiment of this application. Detailed Implementation

[0055] To make the objectives, technical methods, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application. In the embodiments of this application, "at least one" refers to one or more, and "more than one" refers to two or more.

[0056] Existing gene testing report visualization systems aim to improve information comprehension efficiency through graphical interfaces. However, in practical applications, these systems still face numerous challenges in handling new gene data formats, dealing with information overload, and ensuring the accurate transmission of key information. Specifically, in gene testing report visualization systems, when the underlying data filtering logic causes a large number of key variants to be incorrectly classified as "of unknown clinical significance" due to compatibility issues with new data formats, the system, in order to adhere to the design principle of "not omitting any potentially important information," displays all these misclassified variants on the report's visualization interface. This results in a dramatic increase in information overload on the originally concise and focused report interface, presenting a dense list of variants, filled with numerous entries that actually have clear clinical significance but have been incorrectly classified as "of unknown clinical significance." This information overload severely hinders clinicians' ability to quickly capture truly critical information, requiring them to spend a significant amount of extra time and effort filtering and identifying, ultimately reducing the efficiency of report interpretation.

[0057] For this, please refer to Figure 1 This application discloses a method for visualizing a gene testing report, comprising the following steps:

[0058] S110, acquire user interaction data on information items and risk markers for information items on the genetic testing report interface;

[0059] S120, Identify unreviewed potential anomalies based on risk markers and interaction behavior data, and generate an information omission risk indication based on the unreviewed potential anomalies;

[0060] S130, based on the information omission risk indication, provide guidance information to draw the user's attention to potentially anomalous entries that have not been reviewed;

[0061] S140, record potentially abnormal items that the user has been guided to pay attention to via guidance information as reviewed;

[0062] S150, upon receiving a user-triggered instruction representing the final diagnosis and treatment decision, checks the gene testing report for any unreviewed potential abnormal entries;

[0063] S160, if there are unexamined potential abnormal entries, the instruction is interrupted and a prompt interface is displayed for the user to choose to continue the decision or return to view.

[0064] It should be noted that, in order to better understand the method proposed in this application, some key terms involved will be explained first.

[0065] "Information entries" refer to any independently identifiable unit of information contained in a genetic testing report, such as gene mutation sites, descriptions of clinical significance, and drug sensitivity predictions. These entries form the basis for users' review and decision-making.

[0066] "Interactive behavior data" refers to the data generated when users interact with information items on the genetic testing report interface, such as mouse hovering, clicking, scrolling, and typing. This data reflects the user's level of attention and operating habits towards specific information items.

[0067] "Risk markers" refer to pre-defined risk levels or classification labels associated with information items, such as "high risk," "medium risk," "low risk," and "unknown clinical significance." These markers are usually automatically generated by the genetic testing system based on a professional knowledge base or algorithm, and are used to initially indicate the importance or potential harm of the information item.

[0068] "Potentially abnormal entries" refer to information entries that, based on risk markers and interaction behavior data, may be abnormal but have not yet been fully reviewed by the user. These information entries are the ones the system needs to guide users to focus on.

[0069] "Information omission risk indication" is a visual or auditory prompt generated by the system based on potential abnormal entries. It is used to inform users that there is potentially abnormal information in the current report that has not been fully reviewed, and to guide users to conduct further review.

[0070] This method typically runs on a genetic testing report visualization system, which can be a standalone software application or a module integrated into a medical information system. This system usually includes a user interface for displaying the genetic testing report and allowing users to interact with the report content.

[0071] First, the system acquires user interaction data on information entries within the genetic testing report interface, as well as risk markers for those entries. For example, when a user browses the genetic testing report, the system can record the time the user hovers their mouse over a specific gene variant entry or the number of times the user clicks a risk warning icon. Simultaneously, each information entry is assigned a risk marker, such as "pathogenic," "benign," or "unknown significance." These risk markers can be pre-defined or automatically generated based on a genetic database.

[0072] Secondly, the system identifies unreviewed potential anomalies based on the acquired risk markers and interaction behavior data, and generates information omission risk indicators based on these unreviewed potential anomalies. For example, if an information item is marked as "pathogenic," but the user hovers their mouse over it for a very short time or never clicks to view its details, the system may classify it as an "unreviewed potential anomaly." Subsequently, the system generates an information omission risk indicator based on these identified potential anomalies, such as displaying a red warning icon at the top of the reporting interface, along with the text "You may have missed X pieces of important information."

[0073] Next, based on the generated information omission risk indicator, the system will provide guidance to draw the user's attention to unreviewed potential anomalies. For example, when the user sees the warning icon and clicks it, the system can automatically scroll the report interface, center the first unreviewed potential anomaly on the screen, and highlight it with a flashing border to attract the user's attention.

[0074] The system will then record potentially problematic items that the user has been guided to view via the guidance information as reviewed. For example, once a user clicks the warning icon and views a potentially problematic item, the system will update the item's status from "unreviewed" to "reviewed" to avoid repeated reminders.

[0075] Upon receiving a user-triggered instruction representing the final treatment decision, the system checks the genetic testing report for any unreviewed potential anomalies. For example, the system performs a check when a doctor clicks the "Submit Treatment Plan" or "Confirm Treatment Plan" button.

[0076] If the review results reveal unreviewed potential anomalies, the system will interrupt the command and present a prompt interface allowing the user to choose between continuing the decision or returning to the previous screen. For example, the system will display a dialog box stating, "X potential anomalies in the report have not been fully reviewed. Are you sure you want to submit the treatment plan?" and providing the options of "Continue Submission" and "Return to Review" to ensure that the user makes a final decision after fully understanding all key information.

[0077] This application intelligently identifies "unreviewed potential abnormal items" by introducing user interaction behavior data and risk markers for information entries, and generates "information omission risk indicators" accordingly. This mechanism enables the system to proactively identify clinically significant information that may be overlooked by users, rather than passively presenting all information. Based on the information omission risk indicators, this application provides guidance information to draw users' attention to unreviewed potential abnormal items. This proactive guidance mechanism effectively focuses users' attention on key information, preventing users from missing important information due to fatigue or negligence in an information overload environment. More importantly, upon receiving a user-triggered instruction representing the final treatment decision, this application checks the genetic testing report for unreviewed potential abnormal items. If any are found, the instruction is interrupted, and a prompt interface is presented allowing the user to choose to continue the decision or return to the previous page. This "mandatory pre-decision verification" step provides users with a final safety barrier, ensuring that all potentially critical information is fully reviewed before making a final treatment decision. This significantly reduces the risk of misdiagnosis or delay due to information omission, and significantly improves the accuracy and safety of treatment decisions.

[0078] In summary, this application effectively addresses the core challenges of existing technologies in the visualization of gene testing reports, such as information overload, omission of key information, and decision-making risks, through key steps including intelligent identification of potential anomalies, proactive guidance of user attention, and mandatory pre-decision verification. It provides a safer, more efficient, and accurate auxiliary tool for clinical diagnosis and treatment, reduces the cognitive load on users, lowers the probability of key variants being missed during decision-making, and ensures the accuracy of diagnosis and treatment.

[0079] It should be noted that, in some embodiments of this application, the interaction behavior data preferably includes a attention duration parameter for characterizing the user's attention to information items. The interaction behavior data includes a attention duration parameter for characterizing the user's attention to information items. The attention duration parameter is determined based on the pointer hover time obtained by listening to pointer device events or the gaze focusing time obtained by processing eye-tracking sensor data.

[0080] Interactive behavior data refers to the data generated when users interact with information items on the gene testing report interface. This data reflects the user's level of attention to specific information items and their operating habits. Attention duration is a crucial component of interactive behavior data, aiming to quantify the length of time a user spends or focuses on a specific information item, thus indirectly reflecting the user's level of attention to that item. Specifically, attention duration can be obtained in ways including but not limited to the following two: One is by monitoring pointer device events to obtain pointer hover time. For example, when a user uses a mouse, touchpad, or other pointer device to hover the cursor over an information item, the system records the time the cursor remains on that item; this time is the pointer hover time. The other is by processing eye-tracking sensor data to obtain gaze focus time. In scenarios equipped with eye-tracking devices, the system can monitor the user's eye movement trajectory in real time and identify the length of time the user's gaze is focused on a specific information item; this length of time is the gaze focus time. Both methods can be used to accurately measure the user's level of attention to information items, providing data support for subsequent risk assessment.

[0081] This application's solution incorporates attention duration parameters into interaction behavior data, enabling a more refined assessment of the user's actual level of attention to each information item in the genetic testing report. Traditional methods may rely solely on coarse-grained interactions such as clicking and scrolling, making it difficult to accurately determine whether a user has truly read and understood an item. By introducing pointer hover time or gaze focus time as attention duration parameters, the system can more objectively and accurately capture the user's attention allocation on specific information items. For example, even if an item is not clicked, if the user hovers the cursor over it for a long time or focuses their gaze on it for an extended period, it indicates that the user may be carefully reading or thinking about the item, thus avoiding the erroneous labeling of it as unattended due to a lack of clicking behavior. This provides a more reliable basis for subsequently identifying potentially abnormal items that have not been reviewed, improving the accuracy of information omission risk indications.

[0082] In a further embodiment of this application, the step of determining unreviewed potential anomaly entries based on risk markers and interaction behavior data, and generating an information omission risk indication based on the unreviewed potential anomaly entries, preferably includes:

[0083] Based on the risk markers, potential abnormal entries are identified from the information entries, and the duration of user attention to potential abnormal entries is obtained based on the interaction behavior data.

[0084] Determine whether the attention duration parameter meets the condition of being less than the dynamically adjusted attention duration threshold;

[0085] Add potential anomalies that meet the above conditions to the set of items to be reviewed;

[0086] Based on the set of items to be reviewed, the information omission risk indication is generated.

[0087] The process of identifying potential anomalies from information entries based on risk markers and obtaining the user's attention duration parameter for these potential anomalies based on interaction behavior data involves using risk markers, which are pre-defined labels in the genetic testing report to identify information entries that may be abnormal or require special attention. These labels could be high-risk variants, drug sensitivity indicators, or susceptibility to genetic diseases. The system first filters out preliminary potential anomalies from the genetic testing information based on these risk markers. Simultaneously, the system continuously acquires user interaction behavior data on information entries in the genetic testing report interface and extracts the user's attention duration parameter for these potential anomalies. This attention duration parameter reflects the length of time a user spends on a specific information entry, thus indirectly representing the user's level of attention. The attention duration parameter can be determined based on pointer hover time obtained by monitoring pointer device events or gaze focus time obtained by processing eye-tracking sensor data.

[0088] The condition for determining whether the attention duration parameter meets the requirement of being less than the dynamically adjusted attention duration threshold is that the attention duration threshold is a dynamically adjusted reference value used to measure the minimum attention time required for a user to effectively review a certain information item. The system compares the user's actual attention duration parameter for each potentially abnormal item with this dynamically adjusted attention duration threshold. If the user's attention duration parameter is less than the threshold, it indicates that the user may not have adequately reviewed the item.

[0089] Adding potentially anomalous entries that meet the aforementioned conditions to the set of entries to be reviewed means that the set of entries to be reviewed is a temporary storage area used to collect potentially anomalous entries that the system determines may not have been sufficiently reviewed by the user. Only potentially anomalous entries whose attention duration parameter is lower than the attention duration threshold will be included in this set.

[0090] The generation of the information omission risk indicator based on the set of items to be reviewed means that the information omission risk indicator is a prompt message generated by the system based on the set of items to be reviewed, designed to remind users of potentially abnormal items that may have been omitted or not fully reviewed. The information omission risk indicator can be presented in various forms, such as a warning icon at the top of the report, a list prompt in the sidebar, or a prominent label next to a specific item, with the aim of guiding users to review these items and reducing the risk of information omission.

[0091] Through the above technical solution, this application can more accurately identify potential abnormal items that users have not actually reviewed. Compared with relying solely on raw interaction behavior data, the introduction of a dynamically adjusted attention duration threshold allows the system to flexibly judge the user's level of attention based on the actual situation, effectively avoiding misjudgments caused by users' brief glances or distractions.

[0092] The following is a specific example to illustrate this.

[0093] The user is viewing a genetic testing report containing several potentially abnormal entries, such as "Gene Mutation A (High Risk)," "Drug Metabolizing Enzyme B (Medium Risk)," and "Genetic Susceptibility C (Low Risk)." The system first identifies these three potential abnormal entries based on these risk markers. Simultaneously, the system continuously monitors the user's pointer events on the report interface, recording that the user hovered over "Gene Mutation A" for 2 seconds, over "Drug Metabolizing Enzyme B" for 1 second, and over "Genetic Susceptibility C" for 5 seconds. At this point, based on the user's historical activity, the system dynamically adjusts the attention duration threshold to 3 seconds. The system then compares the user's attention duration parameter with this threshold.

[0094] For "gene mutation A", the attention duration of 2 seconds was less than the threshold of 3 seconds, so it was judged as insufficient review.

[0095] For "drug-metabolizing enzyme B", the attention duration of 1 second was less than the threshold of 3 seconds, and therefore it was judged as insufficient review.

[0096] For "genetic susceptibility C", the attention duration of 5 seconds is greater than the threshold of 3 seconds, and therefore it is judged to have been fully reviewed.

[0097] Therefore, the system adds "gene mutation A" and "drug-metabolizing enzyme B" to the set of items to be reviewed, and generates an information omission risk indicator based on the set, such as displaying a prompt at the top of the report that "you may have missed 2 potential abnormal items", guiding the user to go back and check.

[0098] In a specific embodiment of this application, the attention duration threshold is preferably dynamically adjusted based on the average attention duration required for effective review of different categories of information items from the user's recorded historical operation information. Here, the attention duration threshold refers to the time limit used to determine whether a user has given sufficient attention to a specific information item. Recording user historical operation information means that the system continuously collects various interaction data of the user on the gene testing report interface, including but not limited to the time the user views different information items, click behavior, scrolling behavior, etc. Different categories of information items refer to the fact that the gene testing report may contain multiple types of information, such as disease risk, drug sensitivity, genetic characteristics, etc. These different categories of information may have different complexities and importance, and require different amounts of attention from the user. The average attention duration required for effective review refers to the average time spent by the system analyzing historical operation data when the user successfully reviews different categories of information items (e.g., the user explicitly marks them as reviewed, or no erroneous decisions are made due to this item in subsequent operations). Dynamic adjustment means updating the attention duration threshold in real time or periodically based on the above-mentioned statistical average attention duration.

[0099] This application's solution achieves dynamic adjustment of the attention duration threshold by recording users' historical interaction information with different categories of information items and calculating the average attention time required for effective review. Specifically, when a user reviews a genetic testing report, the system continuously collects their interaction data with various information items. This historical data is used to train or statistical models to identify how long different categories of information items typically require for effective review. For example, for items involving complex genetic variations related to rare diseases, users may need a longer attention time to understand their meaning and potential impact; while for common gene loci information that users are already familiar with, the required attention time may be shorter. In this way, the attention duration threshold is no longer a fixed value, but is intelligently adjusted according to the specific category of the information item, making the judgment of the user's level of attention more accurate and personalized.

[0100] The following is a specific example to illustrate this.

[0101] Suppose a genetic testing report contains three categories of information: "Disease Risk," "Drug Metabolism," and "Genetic Traits." The system, through long-term recording of users' historical actions regarding these categories, has found that: for "Disease Risk" categories, users require an average of 45 seconds of attention time for effective review; for "Drug Metabolism" categories, an average of 30 seconds; and for "Genetic Traits" categories, an average of 20 seconds. Based on this historical data, the system dynamically sets the attention time threshold for "Disease Risk" categories to 45 seconds, for "Drug Metabolism" categories to 30 seconds, and for "Genetic Traits" categories to 20 seconds. When a user views a specific category on the genetic testing report interface, the system first identifies the category to which the category belongs, and then applies the corresponding attention time threshold to determine if the user's attention time parameter meets the requirements. For example, if a user views a "Disease Risk" entry for only 10 seconds, even if their attention span exceeds the threshold for "Genetic Characteristics," the entry may still be flagged as an unreviewed potential anomaly because it hasn't reached the 45-second threshold for "Disease Risk," thus triggering an information omission risk indicator. This dynamic adjustment mechanism ensures that information entries of varying importance and complexity receive appropriate attention assessments.

[0102] In some embodiments of this application, the step of providing guidance information based on the information omission risk indication to draw the user's attention to potentially anomalous unreviewed entries preferably includes:

[0103] Based on the information omission risk indicator, count the number of potentially abnormal entries that have not been reviewed in the current genetic testing reports;

[0104] At a predetermined location in the report display area, guidance information containing the number of entries is presented. This guidance information is configured to initiate a review process for potentially problematic entries that have not been reviewed in response to user actions.

[0105] The information omission risk indicator is determined based on the risk markers of information items and user interaction data with those items, and is used to identify key information that the user may have overlooked. Unreviewed potential anomaly items refer to report content that the system identifies as potentially abnormal but has not yet been fully noticed or confirmed by the user. The predetermined location of the report display area can be a fixed area on the genetic testing report interface, such as the top navigation bar, sidebar, or bottom status bar, ensuring that the guidance information is easily noticeable to the user. The guidance information can be a visual element, such as an icon with a numerical label, a prompt box, or a text link, clearly indicating how many unreviewed potential anomaly items exist in the current report. When the user clicks, touches, or otherwise interacts with the guidance information, the system will trigger a preset review mechanism designed to guide the user step-by-step through viewing and addressing these potential anomaly items.

[0106] This application's solution quantifies potential risks in the current report by first counting the number of unreviewed potential anomalies, providing users with an intuitive risk overview. Subsequently, guidance information containing this number of items is displayed in a predetermined location within the report's display area, allowing users to easily notice these potentially overlooked key information while browsing the report. This proactive visual cue mechanism effectively prevents users from ignoring important information due to negligence or fatigue. Furthermore, the guidance information is configured to initiate the review process in response to user actions, enabling users to proactively intervene and systematically review these potential anomalies, thereby transforming potential information omission risks into controllable review behavior.

[0107] In a further embodiment of this application, the step of presenting guidance information containing the number of entries at a predetermined location in the report display area, wherein the guidance information is configured to initiate a review process for unreviewed potentially problematic entries in response to a user action, preferably includes:

[0108] At a predetermined location in the report display area, guiding information containing the number of items is presented;

[0109] In response to the trigger signal of the guidance information, potential abnormal entries to be reviewed are determined from the unreviewed potential abnormal entries according to preset priority rules;

[0110] Adjust the report display area to highlight the potential anomalies to be reviewed, thereby initiating the review process for unreviewed potential anomalies.

[0111] The "trigger signal responding to the guidance information" can be understood as the system receiving a corresponding trigger signal when the user activates the guidance information presented at a predetermined location in the report display area through clicking, touching, voice commands, or other interactive methods. This trigger signal indicates that the user intends to begin reviewing unreviewed potential anomaly items. The "preset priority rules" refer to a set of criteria used to sort and filter unreviewed potential anomaly items. These rules can be set based on various factors, such as the risk level of the information item (e.g., high risk, medium risk, low risk), its order of appearance in the genetic testing report, its relevance to specific diseases or symptoms of concern to the user, or the user's historical review behavior data. The purpose is to ensure that, when initiating the review process, the most important or urgent potential anomaly items for the user are presented first. "Determining potential anomaly items to be reviewed" means that, according to the aforementioned preset priority rules, the system selects one or a group of items from all unreviewed potential anomaly items that best meet the current review priority, as the first items the user needs to focus on in this review process. The "adjusting the report display area" refers to the system changing the display layout, scroll position, and zoom level of the gene testing report to clearly present potential anomalies to be reviewed within the user's field of vision. The purpose is to directly guide the user's visual focus to the target item. The "highlighting the potential anomalies to be reviewed in the display area" can be understood as using visual emphasis techniques, such as changing the background color, adding highlighted borders, flashing effects, or enlarging fonts or icons, to make the potential anomalies to be reviewed more prominent in the report display area, thereby strongly attracting the user's attention. The purpose is to ensure that the user can quickly identify and focus on the system-recommended items to be reviewed, effectively initiating the review process.

[0112] Through the aforementioned technical solution, this application can significantly improve the efficiency and accuracy of gene testing report review. Specifically, by introducing priority rules to identify potential abnormal items to be reviewed, the system can intelligently guide the user's attention to the most critical or urgent information, avoiding blindly searching through a large amount of information and thus greatly saving review time. Simultaneously, by adjusting the report display area and highlighting target items, it ensures that users do not miss important potential abnormal information, effectively reducing the risk of misdiagnosis and treatment decisions due to oversight. This targeted guidance mechanism not only optimizes the user experience but also further strengthens the practical application effect of information omission risk indication, making the gene testing report review process more efficient, accurate, and reliable.

[0113] The following is a specific example to illustrate this.

[0114] Suppose a user sees a prompt on their genetic testing report displaying "You have 3 high-risk potential abnormality entries that have not been reviewed." When the user clicks on this prompt, the system receives a trigger signal. At this point, the system will make a judgment based on preset priority rules. For example, these priority rules might be set as follows: first review all entries marked "high-risk," then "medium-risk," and finally "low-risk"; within the same risk level, reviews are conducted according to the order in which the entries appear in the report. Based on this rule, the system first identifies the first high-risk entry in the report as the potential abnormality entry to be reviewed. Subsequently, the system automatically adjusts the report display area, for example, by smoothly scrolling to move the entry to be reviewed to the center of the screen. Once the entry is in the center of the field of view, the system applies a pulsed highlight border to it and slightly adjusts its background color temperature to make it visually stand out from the surrounding content. Through this series of operations, the user's attention is directly and forcefully guided to this specific high-risk entry, thus efficiently initiating the review process for this unreviewed potential abnormality entry. The user can immediately begin reviewing the most critical information without having to manually search for it.

[0115] In a further embodiment of this application, the step of responding to the trigger signal of the guidance information and determining the potential abnormal entries to be reviewed from the unreviewed potential abnormal entries according to a preset priority rule preferably includes:

[0116] In response to the trigger signal of the guidance information, the unexamined potential abnormal entries are divided into at least one group according to the type corresponding to the risk mark;

[0117] Based on the order in which the potential abnormal entries appear in the gene testing report, the potential abnormal entries within each group are sorted.

[0118] All groups are sorted according to the priority level of the type corresponding to the risk marker to form a group review sequence;

[0119] Based on the group review sequence and the order of potential anomalies within each group, the potential anomalies to be reviewed are determined sequentially.

[0120] The risk markers mentioned here can be understood as identifiers of the risk level or nature of specific information items in a genetic testing report. For example, they can include various types such as "high-risk variant," "medium-risk variant," "low-risk variant," "abnormal drug sensitivity," and "risk of genetic diseases." Grouping potential abnormal items with the same risk marker type together helps to centrally manage and review similar risks.

[0121] After grouping, the system sorts the potential abnormal items within each group according to their order of appearance in the genetic testing report. This sorting method aims to follow the user's natural reading habits, allowing for a more coherent review of information of the same risk type, following its original layout order within the report, thereby improving the consistency of the review and the user experience.

[0122] Based on this, the system sorts all groups according to the priority level corresponding to the risk markers to form a group review sequence. The priority levels can be preset; for example, the group corresponding to "high-risk variants" can be set to the highest priority, followed by "medium-risk variants," "drug sensitivity abnormalities," etc. By prioritizing the groups, the system ensures that users can review the most critical or urgent potential anomalies first.

[0123] Ultimately, the system will determine the potential anomalies to be reviewed sequentially based on the group review sequence and the order of potential anomalies within each group. This means that the review process will first proceed according to the priority order of the groups, and within each group, the potential anomalies will be reviewed according to the order in which they appear in the report.

[0124] Through the above technical solution, the solution of this application can provide users with a structured and logically clear review path, which significantly improves the efficiency and accuracy of gene testing report review.

[0125] The following is a specific example to illustrate this.

[0126] Suppose a genetic testing report contains multiple unreviewed potential abnormal entries, which are classified into three categories based on their risk markers: "high-risk variants", "medium-risk variants", and "drug sensitivity abnormalities".

[0127] First, the system responds to the trigger signal of the guidance information and divides these unreviewed potential abnormal entries into three groups according to their risk labeling type: Group A (high-risk variants), Group B (medium-risk variants) and Group C (drug sensitivity abnormalities).

[0128] Next, within each group, for example, in group A, if multiple high-risk variant entries exist, they will be sorted according to the order in which they appear in the genetic testing report. Similarly, entries in groups B and C are also sorted according to the order in which they appear in the report.

[0129] The system then sorts the three groups according to a preset priority level. For example, "high-risk variants" are given the highest priority, followed by "medium-risk variants," and then "abnormal drug sensitivity." The resulting group review sequence is: Group A - Group B - Group C.

[0130] Ultimately, the system will determine the potential anomalies to be reviewed sequentially based on this grouped review sequence and the order within each group. This means that users will first be guided to review all high-risk variants in group A, presented in their original order in the report; after group A is reviewed, the medium-risk variants in group B will be reviewed sequentially, and finally the drug sensitivity anomalies in group C. This orderly review process ensures that users can systematically and efficiently process all potential anomalies in the report.

[0131] It is worth mentioning that, in a further embodiment of this application, the step of adjusting the report display area to highlight the potential abnormal entries to be reviewed in the display area, so as to initiate the review process for unreviewed potential abnormal entries, preferably includes:

[0132] Dynamically calculate the visibility score of potential anomalies to be reviewed in the current display interface;

[0133] The report display area is dynamically adjusted based on the visibility score, and the potential abnormal items to be reviewed are guided to the center of the visual field of the report display area through smooth scrolling and visual transition effects.

[0134] After the potential abnormal item to be reviewed enters the central area of ​​the field of view, a pulsed highlight border and background color temperature adjustment are applied to the potential abnormal item to make it stand out and initiate the review process for the unreviewed potential abnormal item.

[0135] The dynamic calculation of the visibility score of potential anomaly items to be reviewed in the current display interface refers to the system's comprehensive evaluation of the visibility and noticeability of an item in the user's field of vision based on factors such as the item's position, size, occlusion status, and contrast with surrounding elements within the current display area. For example, an item that is completely obscured or located at the edge of the screen will have a lower visibility score, while an item located in the center of the screen and not obscured will have a higher visibility score. This score aims to quantify the visual salience of an item in the current interface.

[0136] The system dynamically adjusts the report display area based on the visibility score. Through smooth scrolling and visual transition effects, it guides the potential anomaly items to be reviewed to the center of the report display area. This can be understood as the system intelligently adjusting the report's scrolling position and display ratio based on its current visibility score after identifying the potential anomaly items. Smooth scrolling refers to the report content moving continuously and gradually, avoiding sudden screen jumps to reduce user visual discomfort. Visual transition effects can include fade-in / fade-out, scaling, or gradients, making the process of items moving from off-center positions to the center of the field of vision more natural and smooth. The center of the field of vision typically refers to the central part of the display screen, which is the area where the user's vision is most easily focused.

[0137] Once a potential anomaly item to be reviewed enters the central area of ​​the user's field of vision, a pulsed highlight border and background color temperature adjustment are applied to make the item stand out, thus initiating the review process for the unreviewed item. The pulsed highlight border refers to displaying a periodically flashing or brightness-changing border around the potential anomaly item to attract the user's attention. This flashing is not continuous but occurs at a certain frequency and duration to avoid eye strain. Background color temperature adjustment involves changing the color temperature of the background area around the potential anomaly item (e.g., from a cool tone to a warm tone, or vice versa) to create visual contrast and further highlight the item. For example, the background color temperature can be adjusted to a warm tone that contrasts with the main content of the report, making the potential anomaly item more visually striking. The aim is to ensure that the user can quickly and comfortably notice and begin reviewing the potential anomaly item through multiple visual cues.

[0138] Through the aforementioned technical solutions, this application can significantly improve the efficiency and review experience of users in focusing on potential abnormal items in gene testing reports. Specifically, through intelligent visibility assessment and smooth visual guidance, users can focus their attention on key information in a more natural and comfortable way, avoiding visual fatigue or information omissions caused by abrupt interface changes. In addition, the combination of pulsed high-brightness borders and background color temperature adjustment provides strong visual cues for potential abnormal items without interfering with the overall reading experience, ensuring their prominence in complex report content.

[0139] The following is a specific example to illustrate this.

[0140] Suppose a user is reviewing a genetic testing report, and the system has identified several unreviewed potential anomalies based on risk markers and interaction data. When the user triggers a guided message to begin the review process, the system first identifies one potential anomaly to be reviewed, such as a gene mutation associated with a high-risk disease.

[0141] The system dynamically calculates the visibility score of the gene mutation entry in the current display interface. If the entry is currently located at the bottom of the screen and is partially obscured, its visibility score will be lower. Based on this score, the system will initiate an adjustment to the report display area. Specifically, the report content will scroll upwards with a smooth animation, accompanied by a slight background fade-in / fade-out visual transition, gradually moving the gene mutation entry to the center of the report display area.

[0142] Once the gene mutation entry is fully visible in the center of the field of view, the system immediately applies visual enhancements. For example, a soft, bright blue border (pulsating highlight border) appears around the entry, flashing approximately once per second. Simultaneously, the color temperature of the background area surrounding the entry is slightly adjusted to a warm yellow hue that contrasts with the main report content (background color temperature adjustment). These visual effects work together to make the gene mutation entry stand out prominently in the entire report interface, effectively drawing the user's attention to it and prompting them to begin a detailed review of this potentially abnormal entry. After the user completes the review, the entry is marked as reviewed, and the system will continue to guide the user to review the next potentially abnormal entry.

[0143] In a specific embodiment of this application, the step of applying a pulsed highlight border and adjusting the background color temperature to the potential abnormal item after it enters the central area of ​​the field of view to make the potential abnormal item stand out and initiate the review process for the unreviewed potential abnormal item preferably includes:

[0144] After the potential abnormal item to be reviewed enters the central area of ​​the field of view, the ambient light intensity information of the current display device and the user's physiological state indicators are obtained.

[0145] Based on the ambient light intensity information and physiological state indicators, the user's current visual comfort index is calculated;

[0146] Based on the visual comfort index, the flashing frequency and brightness of the pulsed high-brightness border, as well as the hue and intensity of the background color temperature adjustment, are dynamically adjusted.

[0147] Applying an adjusted pulsed highlight border and background color temperature adjustment to the potential anomaly entries makes them stand out, thereby initiating the review process for unreviewed potential anomalies.

[0148] The acquisition of ambient light intensity information for the current display device refers to the real-time detection of the brightness level of the user's environment using a built-in light sensor or an externally connected ambient light sensor. For example, the light intensity information will be higher in a bright office environment, while it will be lower in a dimly lit room. The purpose is to provide environmental parameters for subsequent visual comfort calculations. The user's physiological state indicators can be understood as biological data reflecting the user's current level of visual fatigue, concentration, or sensitivity to light. For example, data such as pupil size and blink frequency can be obtained through eye-tracking devices, or indicators such as heart rate variability and brain wave frequency can be obtained through heart rate sensors or EEG sensors. These indicators can indirectly reflect the user's visual comfort and attention level. The purpose is to provide individual user parameters for subsequent visual comfort calculations. Calculating the user's current visual comfort index based on the ambient light intensity information and physiological state indicators involves using the acquired ambient light intensity information and physiological state indicators as input, and comprehensively evaluating the user's current visual comfort level through a preset algorithm model (e.g., based on machine learning models or expert system rules). Based on the visual comfort index, dynamically adjusting the flashing frequency and brightness of the pulsed highlight border, as well as the hue and intensity of the background color temperature adjustment, means that when the visual comfort index is low, the system can reduce the flashing frequency and brightness of the pulsed highlight border and adjust the background color temperature to make it softer (e.g., warmer tone, reduced intensity) to reduce eye strain. Conversely, when the visual comfort index is high, the flashing frequency and brightness can be appropriately increased, and the background color temperature adjusted to enhance the prompting effect. The purpose is to ensure that the highlighting effect achieves optimal guidance and user comfort under different conditions.

[0149] This application's solution incorporates the perception of ambient light intensity and user physiological state indicators, and calculates a visual comfort index based on this, thereby achieving dynamic adaptive adjustment of the pulsed highlight border and background color temperature parameters. When the ambient light is too strong or too weak, or when the user shows signs of visual fatigue, the system can intelligently adjust the intensity and form of the highlight effect, avoiding the problems of excessive visual stimulation or insufficient prompting effect that may result from fixed parameters. For example, in dimly lit environments, the system will reduce the brightness and flicker frequency of the highlight border and use a softer background color temperature to prevent strong light from stimulating the user's eyes; while when the user's attention is not focused, the system may appropriately enhance the highlight effect to more effectively attract the user's attention. This dynamic adjustment mechanism ensures that, under any circumstances, potentially abnormal items are highlighted in a way most suitable for the user's visual perception, thereby significantly improving the effectiveness of guidance information and user experience.

[0150] Through the above technical solution, this application can intelligently adjust the highlighting effect of potential abnormal items in the gene testing report according to real-time ambient lighting conditions and the user's physiological state. This not only effectively avoids the problems of visual fatigue or poor prompting effect that may be caused by traditional fixed highlighting parameters, but also significantly improves the user's visual comfort and concentration when reviewing the report.

[0151] The following is a specific example to illustrate this.

[0152] Suppose a user is reviewing a genetic testing report. The system first obtains information about the current ambient light intensity through the display device's built-in light sensor and obtains the user's heart rate variability data as a physiological state indicator through a connected smart bracelet. Specifically, if the system detects low ambient light intensity (e.g., the user is using the device at night) and the user's heart rate variability data indicates possible fatigue, the system calculates a low visual comfort index. Based on this index, the system dynamically adjusts the flashing frequency of the pulsed highlight border, reducing it from the default of 2 times per second to 1 time per second, while adjusting the border brightness from 100% to 70%. Furthermore, the background color temperature is adjusted to a warmer tone (e.g., from the default 6500K to 5000K) and its intensity is reduced to make the background color appear softer. Conversely, if the system detects moderate ambient light intensity and the user's physiological state indicators show good mental well-being, the system calculates a higher visual comfort index. At this point, the system may maintain or slightly increase the flashing frequency and brightness of the highlighted borders, and adopt a clearer background color temperature to ensure that potential abnormal entries can be effectively and comfortably observed in normal environments. Through this dynamic adjustment, the system can provide the most suitable visual guidance regardless of the user's environment or physiological state, ensuring that the user can efficiently and comfortably review the key information in the genetic testing report.

[0153] Please refer to Figure 2 This application also discloses a visualization system 200 for gene testing reports, including:

[0154] The acquisition module 210 is used to acquire user interaction data on information items and risk markers for information items on the gene testing report interface;

[0155] The indication module 220 is used to determine unreviewed potential abnormal entries based on the risk markers and the interaction behavior data, and to generate an information omission risk indication based on the unreviewed potential abnormal entries;

[0156] The guidance module 230 is used to provide guidance information based on the information omission risk indication to make the user pay attention to the unexamined potential abnormal entries;

[0157] The recording module 240 is used to record potentially abnormal items that the user has been guided to pay attention to via the guidance information as reviewed items.

[0158] The recognition module 250 is used to recognize the decision commands issued by the user;

[0159] The verification module 260 is used to verify whether there are any unreviewed potential abnormal entries in the gene testing report after receiving a user-triggered instruction representing the final diagnosis and treatment decision.

[0160] The interrupt module 270 is used to interrupt the instruction and present a prompt interface for the user to choose to continue the decision or return to view if there is a potential unexamined abnormal entry.

[0161] It should be emphasized that the system proposed in this application, through modular design, concretizes the above-mentioned method steps into hardware, software, or hardware-software combination entities that can work independently or collaboratively.

[0162] The acquisition module 210 can be configured to acquire user interaction data and risk markers for information items on the gene testing report interface by listening to user interface events, reading sensor data, or parsing log files. For example, the acquisition module can be a script integrated into a browser plugin to capture mouse hover and click events and associate these event data with preset risk markers for information items in the report.

[0163] The indication module 220 can be an analysis program running on a server or client side, used to receive data provided by the acquisition module and, based on preset algorithm logic, determine which information items belong to unreviewed potential abnormal items, thereby generating an information omission risk indication. For example, the indication module can identify high-risk items with low attention based on a risk assessment model.

[0164] The guidance module 230 can be a user interface rendering component used to present visual cues at specific locations in the report display area based on the information omission risk indication generated by the indication module, and to respond to user actions to initiate the review process. For example, the guidance module can display a floating warning bar at the top of the report, which, when clicked, automatically jumps to the first unreviewed item.

[0165] The logging module 240 can be a database service or a local storage component used to persistently store the status information of reviewed entries, ensuring that users can maintain the review progress across different sessions or on different devices.

[0166] The recognition module 250 can be an event listener configured to continuously monitor specific operations on the user interface, such as click events of buttons like "Submit Diagnosis," "Generate Report," or "Save and Exit." When the user triggers these preset decision instructions through mouse clicks, keyboard input, or touch operations, the recognition module can accurately capture and parse these instructions. In a preferred implementation, the recognition module can be a simple button click event handler; when the user clicks a button representing the final diagnostic decision, the module recognizes the corresponding instruction. The purpose of the recognition module is to ensure that the system can accurately capture the timing of the user's intention to make a final decision, thereby triggering subsequent verification processes and providing a foundation for ensuring the accuracy of diagnostic decisions.

[0167] The verification module 260 can be a backend service or client script that is called before the user submits the final decision. It is used to traverse the review status of all information entries in the current report and determine whether there are any potential abnormal entries that have not been reviewed.

[0168] Interrupt module 270 can be a user interface control component that, when the verification module finds an unreviewed item, is responsible for intercepting the user's decision command and popping up a prompt dialog box, providing options to continue the decision or return to view.

[0169] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0170] The above description is merely an embodiment of this application and is not intended to limit the scope of protection of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of protection of this application.

Claims

1. A method for visualizing a gene testing report, characterized in that, Includes the following steps: Acquire user interaction data on information items and risk markers for information items on the genetic testing report interface; Based on the risk markers and the interaction behavior data, unreviewed potential anomaly entries are identified, and an information omission risk indication is generated based on the unreviewed potential anomaly entries. Based on the information omission risk indication, provide guidance information to draw the user's attention to the unreviewed potential anomalies; Potentially abnormal entries that users have been guided to pay attention to via the aforementioned guidance information will be recorded as reviewed. Upon receiving a user-triggered instruction representing the final diagnosis and treatment decision, check the gene testing report for any unreviewed potential abnormal entries; If any unexamined potential anomalies are found, the instruction is interrupted and a prompt interface is displayed, allowing the user to choose whether to continue the decision or return to view the previous content.

2. The method for visualizing a gene testing report according to claim 1, characterized in that, The interactive behavior data includes a attention duration parameter that characterizes the user's attention to information items. The attention duration parameter is determined based on pointer hover time obtained by listening to pointer device events or gaze focusing time obtained by processing eye-tracking sensor data.

3. The method for visualizing a gene testing report according to claim 2, characterized in that, The step of determining unreviewed potential anomaly entries based on the risk markers and the interaction behavior data, and generating an information omission risk indication based on the unreviewed potential anomaly entries, includes: Based on the risk markers, potential abnormal entries are identified from the information entries, and the duration of user attention to potential abnormal entries is obtained based on the interaction behavior data. Determine whether the attention duration parameter meets the condition of being less than the dynamically adjusted attention duration threshold; Add potential anomalies that meet the above conditions to the set of items to be reviewed; Based on the set of items to be reviewed, the information omission risk indication is generated.

4. The method for visualizing a gene testing report according to claim 3, characterized in that, The attention duration threshold is dynamically adjusted based on the average attention duration required to effectively review different categories of information items in the user's historical operation information.

5. The method for visualizing a gene testing report according to claim 1, characterized in that, The step of providing guidance information to draw the user's attention to the unreviewed potentially abnormal entries based on the information omission risk indication includes: Based on the aforementioned information omission risk indication, count the number of potentially abnormal entries that have not been reviewed in the current gene testing report; At a predetermined location in the report display area, guidance information containing the number of entries is presented. This guidance information is configured to initiate a review process for potentially problematic entries that have not been reviewed in response to user actions.

6. The method for visualizing a gene testing report according to claim 5, characterized in that, The step of presenting guidance information containing the number of items at a predetermined location in the report display area, the guidance information being configured to initiate a review process for unreviewed potentially problematic items in response to user actions, includes: At a predetermined location in the report display area, guiding information containing the number of items is presented; In response to the trigger signal of the guidance information, potential abnormal entries to be reviewed are determined from the unreviewed potential abnormal entries according to preset priority rules; Adjust the report display area to highlight the potential anomalies to be reviewed, thereby initiating the review process for unreviewed potential anomalies.

7. The method for visualizing a gene testing report according to claim 6, characterized in that, The step of responding to the trigger signal of the guidance information and determining the potential anomaly entries to be reviewed from the unreviewed potential anomaly entries according to a preset priority rule includes: In response to the trigger signal of the guidance information, the unexamined potential abnormal entries are divided into at least one group according to the type corresponding to the risk mark; Based on the order in which the potential abnormal entries appear in the gene testing report, sort the potential abnormal entries within each group; All groups are sorted according to the priority level of the type corresponding to the risk marker to form a group review sequence; Based on the group review sequence and the order of potential anomalies within each group, the potential anomalies to be reviewed are determined sequentially.

8. The method for visualizing a gene testing report according to claim 6, characterized in that, The step of adjusting the report display area to highlight the potential anomalies to be reviewed, thereby initiating the review process for unreviewed potential anomalies, includes: Dynamically calculate the visibility score of potential anomalies to be reviewed in the currently displayed interface: The report display area is dynamically adjusted based on the visibility score, and the potential abnormal items to be reviewed are guided to the center of the visual field of the report display area through smooth scrolling and visual transition effects. After the potential abnormal item to be reviewed enters the central area of ​​the field of view, a pulsed highlight border and background color temperature adjustment are applied to the potential abnormal item to make it stand out and initiate the review process for the unreviewed potential abnormal item.

9. The method for visualizing a gene testing report according to claim 8, characterized in that, The step of applying a pulsed highlight border and adjusting the background color temperature to the potential anomaly item after it enters the central area of ​​the field of view to make the potential anomaly item stand out and initiate the review process for unreviewed potential anomalies includes: After the potential abnormal item to be reviewed enters the central area of ​​the field of view, the ambient light intensity information of the current display device and the user's physiological state indicators are obtained. Based on the ambient light intensity information and physiological state indicators, the user's current visual comfort index is calculated; Based on the visual comfort index, the flashing frequency and brightness of the pulsed high-brightness border, as well as the hue and intensity of the background color temperature adjustment, are dynamically adjusted. Applying an adjusted pulsed highlight border and background color temperature adjustment to the potential anomaly entries makes them stand out, thereby initiating the review process for unreviewed potential anomalies.

10. A visualization system for gene testing reports, characterized in that, include: The acquisition module is used to acquire user interaction data on information items and risk markers for information items on the genetic testing report interface; The indication module is used to determine unreviewed potential abnormal entries based on the risk markers and the interaction behavior data, and to generate an information omission risk indication based on the unreviewed potential abnormal entries; The guidance module is used to provide guidance information based on the information omission risk indication to make the user pay attention to the unreviewed potential abnormal entries; The recording module is used to record potentially abnormal items that the user has been guided to pay attention to via the guidance information as having been reviewed. The recognition module is used to recognize the decision commands issued by the user; The verification module is used to verify whether there are any unreviewed potential abnormal entries in the gene testing report after receiving a user-triggered instruction that represents the final diagnosis and treatment decision. The interrupt module is used to interrupt the instruction and present a prompt interface for the user to choose to continue the decision or return to view if there are unexamined potential abnormal entries.

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