Dental triage and clinical risk assessment system
The dental triage system addresses inefficiencies in teledentistry by using AI and rule-based logic to objectively assess dental urgency and risk, dynamically routing patients to appropriate care, enhancing efficiency and early disease detection.
Patent Information
- Authority / Receiving Office
- DE · DE
- Patent Type
- Utility models
- Current Assignee / Owner
- Filing Date
- 2026-02-05
- Publication Date
- 2026-03-26
AI Technical Summary
Conventional teledentistry platforms lack structured and automated triage capabilities, relying on clinician judgment for case prioritization, leading to inconsistent and inefficient care routing, delayed identification of urgent dental conditions, and increased clinician workload.
A dental triage and clinical risk assessment system that integrates intelligence-based analytical processing and rule-based decision logic to generate quantified urgency scores and risk classifications, dynamically routing patients to appropriate care pathways through a combination of symptom questionnaires, image analysis, and standardized clinical decision rules.
The system reduces subjective triage, enables early detection of serious oral diseases, optimizes clinic efficiency, and improves patient satisfaction by objectively assessing urgency and risk, reducing clinician workload and ensuring timely care.
Smart Images
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Abstract
Description
Application area of the invention
[0001] Embodiments of the present invention relate to telemedicine systems for dental care and in particular a system for dental triage and clinical risk assessment. Description of the state of the art
[0002] Telemedicine systems for dentistry, commonly referred to as teledentistry, have been developed to enable remote dental care through digital interaction between patients and dentists. Teledentistry utilizes telecommunications and digital technologies for remote treatment, consultation, assessment, and treatment coordination. Using networked devices, telemedicine systems allow the exchange of dental information, including patient-reported symptoms, clinical images, and consultation data, between patients and dentists without requiring a physical visit. These technologies aim to improve access to dental care, support early assessment, and optimize continuity of care across diverse clinical and geographical settings.
[0003] Access to timely dental care is often limited by geographical factors, the availability of dentists, and the lack of effective early detection mechanisms. Delays in dental examinations can lead to otherwise treatable conditions developing into more serious illnesses, thus increasing patient risk and the burden on the healthcare system.
[0004] In recent years, telemedicine and teledentistry platforms have been introduced to improve access to dental services through remote communication between patients and dentists. Such platforms typically support video consultations, image sharing, and the recording of basic symptoms. While these approaches increase convenience, they largely lack structured and automated triage capabilities. Existing systems typically rely on the dentist's time, subjective assessments, and manual case prioritization, limiting the scalability and consistency of care.
[0005] Conventional teledentistry platforms offer limited image-based screening capabilities and typically require manual assessment by the clinician to determine priority and care direction. Furthermore, current platforms do not support automated pathway determination or adaptive learning based on clinical outcomes, resulting in continued reliance on clinician judgment for case prioritization, inefficient care routing, and limited scalability.
[0006] Consequently, reliance on manual review and unstructured assessment can lead to several challenges, including delays in identifying urgent dental cases, inefficient allocation of clinical resources, overcrowded emergency departments, and missed opportunities for the early detection of high-risk conditions. Such high-risk conditions may include, but are not limited to, oral cancers, acute dental or craniofacial infections, and rapidly progressing periodontal disease, where timely intervention is critical.
[0007] Furthermore, patient-reported dental symptoms are often multifactorial and can change over time, making accurate assessment difficult when symptoms are evaluated in isolation. While intraoral images can provide valuable clinical information, conventional teledentistry platforms do not systematically integrate visual indicators with structured symptom data within a standardized analytical framework. The lack of objective urgency assessment, integrated symptom analysis, and dynamic care routing mechanisms contributes to inconsistent triage outcomes and increased clinician workload.
[0008] Additionally, there is currently no widely deployed system that objectively quantifies dental urgency, integrates automated or intelligence-based symptom and image analysis, and dynamically routes patients to appropriate care pathways such as emergency referral, scheduled clinical consultation, teleconsultation, or guided self-care. Existing solutions offer only limited support for decision traceability, regulatory compliance, interoperability with electronic health records, and continuous learning based on confirmed clinical outcomes. Accordingly, there is a need for an improved dental triage and clinical risk assessment system that enables structured remote patient interactions, integrates symptoms and visual data, objectively assesses urgency and risk, supports automated care pathway routing, and provides compliance support.
[0009] Interoperability and adaptive learning capabilities to improve the efficiency, safety and accessibility of dental care.
[0010] Therefore, the present invention offers a dental triage and clinical risk assessment system that uses a combination of intelligence-based analytical processing and rule-based clinical decision logic to generate quantified urgency points, determine risk levels, and dynamically direct patients to appropriate care pathways, thereby eliminating subjective triage in teledentistry, reducing the workload of clinicians, preventing delays in emergency care, enabling early detection of serious oral diseases, and improving clinic efficiency and patient satisfaction. SUMMARY OF THE INVENTION
[0011] Embodiments of the present invention relate to a dental triage and clinical risk assessment system. The system comprises a first user device configured to receive patient-related dental information for remote dental evaluation. The system also includes a first user interface on the first user device configured to guide patient interaction by presenting structured symptom questionnaires, image acquisition instructions, and status notifications. The system further includes a communication network connected to the first user device and configured to securely transmit patient-related dental information and control signals.The system also includes a processing unit connected to the first user device via the communication network and configured to perform automated dental triage and clinical risk assessment through coordinated data analysis, decision logic, and routing operations. The processing unit includes a data acquisition module configured to receive patient-related dental information from the first user device. It also includes a data preprocessing module configured to validate, normalize, and structure the received dental information for analytical processing.The processing unit also includes a triage intelligence module configured to analyze structured dental information to generate a quantified urgency score and risk classification level using combined analytical logic. The processing unit also includes a decision support module configured to assign the urgency score and risk classification level to a recommended dental care pathway. Finally, the processing unit includes a care navigation module configured to generate routing instructions corresponding to an emergency referral or a scheduled consultation.
[0012] Teleconsultation or automated guidance. The processing unit also includes a learning and analysis module configured to update internal analytical parameters based on confirmed clinical results. The system also includes a storage unit connected to the processing unit and configured to store patient data, analytical results, priority scores, routing decisions, and outcome feedback for continuous system operation. The system also includes a second user device connected to the processing unit via the communication network and configured to receive triage outputs and treatment pathway recommendations.The system also includes a second user interface on the second user device, configured to display risk indicators, urgency points, patient data summaries, and override controls for interaction with the clinician.
[0013] In accordance with one embodiment of the present invention, the first user device further comprises an image acquisition unit configured to support standardized intraoral image acquisition by providing camera positioning instructions, lighting adjustment prompts, and image validation requests to ensure consistent image framing and quality suitable for automated analytical processing.
[0014] In accordance with one embodiment of the present invention, the first user interface further comprises a symptom timeline module configured to record temporal variations of the conditions reported by the patient.
[0015] In accordance with one embodiment of the present invention, the communication network further comprises a secure encryption layer configured to protect the transmission of patient-related dental information.
[0016] In accordance with one embodiment of the present invention, the processing unit further comprises a symptom correlation machine configured to map multiple symptom inputs across different data fields.
[0017] In accordance with one embodiment of the present invention, the processing unit further comprises an image feature extraction module configured to identify visual dental indicators from image data.
[0018] In accordance with one embodiment of the present invention, the image feature extraction module further comprises a lesion boundary detection sub-module configured to identify and outline contours of abnormal oral tissue regions within the acquired image data to assist clinical risk analysis.
[0019] In accordance with one embodiment of the present invention, the triage intelligence module further comprises a rule evaluation submodule configured to apply predefined clinical thresholds by comparing structured symptom patterns and extracted image features with stored decision rules to determine urgency categorization and escalation conditions.
[0020] In accordance with one embodiment of the present invention, the triage intelligence module further comprises a probability ranking sub-module configured to generate ordered probability values for dental conditions.
[0021] In accordance with one embodiment of the present invention, the decision support module further comprises an explainability mapping submodule configured to link analytical outputs with interpretable clinical indicators.
[0022] In accordance with one embodiment of the present invention, the care navigation module further comprises an appointment coordination sub-module configured to interact with external scheduling systems.
[0023] In accordance with an embodiment of the present invention, the care navigation module further comprises an emergency escalation sub-module configured to initiate priority alerts by generating real-time notification signals and routing instructions to specific emergency care points when the urgency score exceeds a defined critical threshold.
[0024] In accordance with one embodiment of the present invention, the learning and analysis module further comprises a result verification sub-module configured to receive diagnostic results confirmed by clinicians.
[0025] In accordance with one embodiment of the present invention, the learning and analysis module further comprises a model weight adjustment submodule configured to update analytical parameters based on result feedback.
[0026] In accordance with one embodiment of the present invention, the storage unit further comprises a segmented data repository configured to store image data, symptom data, and analytical outputs separately.
[0027] In accordance with one embodiment of the present invention, the processing unit further comprises a compliance logging module configured to record the traceability of decisions.
[0028] Data is stored by saving time-stamped analytical inputs, results of rule evaluation, derivations of urgency points, and selection of care pathways for audit and regulatory review purposes.
[0029] In accordance with one embodiment of the present invention, the processing unit further comprises a population analytics module configured to aggregate anonymized triage trends by statistically processing stored urgency points, risk classifications, and care pathway selection results to perform longitudinal pattern analysis.
[0030] In accordance with one embodiment of the present invention, the processing unit further comprises a modular deployment module configured to support cloud-based or local execution environments.
[0031] In accordance with one embodiment of the present invention, the processing unit further comprises an interoperability module configured to exchange data with electronic patient records (EMR).
[0032] Another embodiment of the present invention relates to a dental triage and clinical risk assessment method.
[0033] The method involves receiving patient-related dental information via a first user device, while patient interaction is guided through a first user interface that presents structured symptom questionnaires, image acquisition instructions, and status notifications.
[0034] The method also includes the transmission of patient-related dental information and control signals via a communication network to a processing unit.
[0035] The method also includes the acquisition of patient-related dental information within the processing unit through a data acquisition module.
[0036] The method also includes the validation, normalization and structuring of patient-related dental information through a data preprocessing module for analytical processing.
[0037] The method also includes the analysis of structured dental information by a triage intelligence module to generate a quantified urgency point and risk classification level using combined analytical logic that integrates symptom patterns and extracted visual indicators.
[0038] The method also includes the assignment of the urgency point and the risk classification level to a recommended dental care pathway by a decision support module.
[0039] The method also includes the generation of routing instructions by a nursing navigation module, corresponding to appropriate emergency referrals, scheduled consultations, teleconsultations, or automated guidance.
[0040] The method also includes updating internal analytical parameters through a learning and analysis module based on confirmed data.
[0041] Clinical outcomes. The invention also includes storing patient data, analytical results, urgency assessments, routing decisions, and outcome feedback in a storage unit for continuous system operation. The invention also includes transmitting triage outputs and treatment pathway recommendations via the communication network to a second user device. The invention also includes displaying risk indicators, urgency assessments, patient data summaries, and override controls via a second user interface for interaction with the clinician. BRIEF DESCRIPTION OF THE DRAWINGS
[0042] In order to understand in detail how the aforementioned features of the present invention are to be understood, a more precise description of the invention summarized above can be given by reference to embodiments, some of which are illustrated in the accompanying drawings. It should be noted, however, that the accompanying drawings only illustrate typical embodiments of this invention and therefore should not be considered limiting in scope, since the invention may also allow for other equally effective embodiments.
[0043] The invention described herein will be better understood from the following description with reference to the drawings, in which: Fig. a block diagram of a dental triage and clinical risk assessment system is illustrated according to an embodiment of the present invention; Fig. illustrates a step-by-step process for implementing the dental triage and clinical risk assessment system, according to an embodiment of the present invention; and Fig. A flowchart for a dental triage and clinical risk assessment procedure of the invention is illustrated.
[0044] It should be noted that the accompanying figure is intended to present illustrations of exemplary embodiments of the present disclosure. This figure is not intended to limit the scope of the present disclosure. It should also be noted that the accompanying figure is not necessarily drawn to scale. DETAILED DESCRIPTION OF THE INVENTION
[0045] The following detailed description presents numerous specific details to provide a thorough understanding of the embodiment of the invention. As illustrative or exemplary embodiments, specific embodiments in which the invention can be practiced are described in sufficient detail to enable those skilled in the art to practice the disclosed embodiments. However, it will be obvious that the embodiments of the invention can be practiced with or without these specific details. In other cases, generally known methods and components have not been described in detail in order to avoid unnecessarily obscuring aspects of the embodiments of the invention.
[0046] The following detailed description is therefore not to be understood in a limiting sense, and the scope of the present invention is defined by the appended claims and their corresponding provisions. The terms "comprising," "including," "having," and similar terms are synonymous and are used inclusively, in an open manner, and do not exclude additional elements, features, actions, operations, etc. Likewise, the term "or" is used in its inclusive sense (and not in its exclusive sense), so that, for example, when used to join a list of elements, the term "or" means one, some, or all of the elements in the list.
[0047] References within the specification to “an embodiment”, “an embodiment”, “elaborations” or “one or more embodiments” are intended to indicate that a particular feature, structure or property described in connection with the embodiment is included in at least one embodiment of the present invention.
[0048] Although the terms first, second, etc., can be used here to describe different elements, these elements should not be restricted by these terms. These terms are generally used only to distinguish one element from another and do not denote any order, rank, quantity, or importance, but merely serve to differentiate one element from another. Furthermore, the terms "a" and "an" here do not denote a restriction of the set, but rather indicate the presence of at least one of the elements mentioned.
[0049] The conditional language used here, such as “may”, “could”, “is allowed”, “e.g.” and similar terms, unless expressly stated otherwise or understood differently in context, is generally intended to convey that certain embodiments include certain features, elements and / or steps, while other embodiments do not.
[0050] Disjunctive language such as the expression "at least one of X, Y, Z", unless explicitly stated otherwise, is generally understood in context to mean that an element, term, etc., can be either X, Y, or Z, or any combination thereof.
[0051] (e.g., X, Y and / or Z). Thus, such a disjunctive language is generally not intended to, and should not imply, that certain embodiments require at least one of X, at least one of Y, or at least one of Z to be present in each case.
[0052] The following brief definition of terms applies throughout the entire present invention.
[0053] The terms "determine," "measure," "evaluate," "assess," "analyze," and "analyze" can be used interchangeably here to refer to any form of measurement and include determining whether an element is present or not (e.g., detection). These terms can encompass both quantitative and qualitative determinations. The evaluation can be relative or absolute.
[0054] Fig. Figure 100 shows a block diagram of a dental triage and clinical risk assessment system according to an embodiment of the present invention.
[0055] The dental triage and clinical risk assessment system 100 can include a first user device 102, a first user interface 104, a communication network 110, a processing unit 112, a storage unit 154, a second user device 158 and a second user interface 160.
[0056] The first user device 102 is configured to receive patient-related dental information for remote dental assessment. The first user device 102 allows a patient to interact with the system 100 by providing structured symptom information, capturing visual dental data, and receiving system-generated prompts and notifications, thus facilitating a preliminary dental evaluation without the need for an in-person clinical visit.
[0057] In one embodiment of the present disclosure 102, the first user device 102 also enables a patient to upload radiographic images, intraoral photographs and video data under dental conditions for remote evaluation.
[0058] In one embodiment of the present disclosure, the first user device 102 may comprise a smartphone, a laptop, a tablet, a personal computer, a smart wearable device and any other network-enabled electronic device capable of receiving user input, capturing dental-related visual data and communicating via a communication network 110 to enable remote dental assessment and triage.
[0059] In one embodiment of the present disclosure, the first user device 102 further comprises an imaging unit 108 configured to support standardized intraoral images.
[0060] Capture is achieved by providing camera positioning instructions, lighting alignment prompts, and capture validation requests to ensure consistent image framing and quality suitable for automated analytical processing. The image capture unit 108 is configured to capture intraoral photographs and intraoral videos.
[0061] The first user interface 104 within the first user device 102 is configured to guide the patient's interaction by presenting structured symptom questionnaires, image acquisition instructions, and status notifications.
[0062] In one embodiment of the present disclosure, the first user device 102 comprises the first user interface 104 in the form of a mobile or web-based application configured to facilitate structured interaction between the patient and the system 100.
[0063] In one embodiment of the present disclosure, the first user interface 104 further comprises a symptom timeline module 106, which is configured to record temporal variations of the conditions reported by the patient.
[0064] The communication network 110 is connected to and configured with the first user device 102 to securely transmit patient-related dental information and control signals.
[0065] In one embodiment of the present disclosure, the communication network 110 can be both wired and wireless.
[0066] In one embodiment of the present disclosure, the communication network can include Wi-Fi, Bluetooth, Ethernet, mobile networks such as 2G, 3G, 4G and 5G, wide area network (WAN), local area network (LAN), virtual network (VAN), serial communication protocols and universal serial bus (USB) interfaces for input / output connectivity.
[0067] In one embodiment of the present disclosure, the communication network 110 further comprises a secure encryption layer configured to protect the transmission of patient-related dental information.
[0068] The processing unit 112 is connected to the first user device 102 via the communication network 110 and configured to perform automated dental triage and clinical risk assessment through coordinated data analysis decision logic and routing operations. The processing unit 112 comprises several modules, including a data acquisition module 114, a data preprocessing module 116, and a triage intelligence module.
[0069] 124, a decision support module 130, a nursing navigation module 134 and a learning and analysis module 144.
[0070] In one embodiment of the present disclosure, the processing unit 112 may comprise a microprocessor, a microcontroller, a central processing unit (CPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or any combination thereof.
[0071] The data acquisition module 114 is configured to receive patient-related dental information from the first user device 102.
[0072] The data preprocessing module 116 is configured to validate, normalize, and structure the received dental information for analytical processing.
[0073] The Triage Intelligence Module 124 is configured to analyze structured dental information to generate a quantified clinical urgency score and assign an appropriate risk classification level using combined analytical logic.
[0074] In one embodiment of the present disclosure, the triage intelligence module 124 calculates the quantified clinical urgency score using a proprietary scoring algorithm configured to assign a Dental Urgency Index (DUI) based on the analytical evaluation of several clinical severity parameters. The proprietary scoring algorithm processes patient-reported symptom data and associated risk information, including pain intensity, swelling progression, severity of bleeding, fever indicators, trauma history, and immunocompromised status, and applies weighted analytical logic to generate the DUI, which represents a relative level of dental urgency.
[0075] In one embodiment of the present disclosure, the risk classification level may include stratified categories that encompass critical, urgent, routine, and preventive conditions.
[0076] In one embodiment of the present disclosure, the triage intelligence module 124 can apply a combination of AI-based learning models, statistical inference techniques, and predefined clinical decision rules to assess severity, progress indicators, and escalation conditions associated with identified dental conditions.
[0077] In one embodiment of the present disclosure, the triage intelligence module 124 further comprises a rule evaluation submodule 126 which is configured to apply predefined rules.
[0078] Clinical thresholds are determined by comparing structured symptom patterns and extracted image features with stored decision rules to determine urgency categorization and escalation conditions.
[0079] In one embodiment of the present disclosure, the triage intelligence module 124 further comprises a probability ranking submodule 128 configured to generate ordered probability values for dental conditions.
[0080] In one embodiment of the present disclosure, the processing unit 112 further comprises an image feature extraction module 118, which is configured to identify visual dental indicators from image data.
[0081] In one embodiment of the present disclosure, the extracted features include ulcer margins, asymmetry, presence of exudate, changes in gingival color, and suspicious lesions.
[0082] In one embodiment of the present disclosure, the image feature extraction module 118 further comprises a lesion boundary detection submodule 120, which is configured to identify and outline contours of abnormal oral tissue regions within the acquired image data to assist clinical risk analysis.
[0083] In one embodiment of the present disclosure, the processing unit 112 further comprises a symptom analysis engine 122 which is configured to map multiple symptom inputs across different data fields.
[0084] Decision Support Module 130 is configured to map the urgency score and risk classification level to a recommended dental care pathway. Decision Support Module 130 applies predefined clinical mapping rules and threshold criteria to link the urgency score and risk classification level generated by Triage Intelligence Module 124 to standardized care options, thereby determining whether a patient requires emergency intervention, expedited clinical assessment, routine scheduling, teleconsultation, or automated guidance. Decision Support Module 130 also ensures consistency, safety, and traceability of triage outcomes by acting as a rule-based clinical decision level suitable for clinician review and override.
[0085] In one embodiment of the present disclosure, the decision support module 130 further comprises a traceability submodule 132, which is configured to link analytical outputs with interpretable clinical indicators. The decision support module 130 can generate an explanation map that assigns the urgency score and risk classification.
[0086] with contributing symptoms, extracted visual indicators and applied clinical rules, thereby enabling a transparent interpretation and review of triage outputs by a clinician via the second user interface 160.
[0087] The Nursing Navigation Module 134 is configured to generate routing instructions that correspond to appropriate emergency referrals, scheduled consultations, teleconsultations, or automated guidance. The Nursing Navigation Module 134 generates actionable routing instructions that align with the recommended dental care pathway determined by the Decision Support Module 130. The Nursing Navigation Module 134 initiates appropriate workflows, including generating emergency referral notifications, facilitating appointment scheduling, enabling the initiation of teleconsultations, or providing automated patient guidance.
[0088] In one embodiment of the present disclosure, the nursing navigation module 134 further comprises an appointment coordination sub-module 136 which is configured to interact with external planning systems.
[0089] In one embodiment of the present disclosure, the nursing navigation module 134 further comprises an emergency escalation sub-module 138 configured to initiate priority notifications by generating real-time notification signals and routing directives to specific emergency care destinations when the urgency value exceeds a defined critical threshold.
[0090] In one embodiment of the present disclosure, the processing unit 112 further comprises a compliance logging module 140 configured to record decision traceability data by storing time-stamped analytical inputs, rule evaluation results, urgency value derivations, and supply route selections for audit and regulatory purposes.
[0091] In one embodiment of the present disclosure, the processing unit 112 further comprises an interoperability module 142 which is configured to exchange data with electronic patient records (EMR).
[0092] The Learning and Analysis Module 144 is configured to update internal analytical parameters based on confirmed clinical outcomes. The Learning and Analysis Module 144 analyzes discrepancies between predicted urgency scores, risk classifications, and actual clinical findings to refine assessment weights, thresholds, and probabilities.
[0093] Associations that improve triage accuracy, consistency, and system performance over time while adhering to predefined safety constraints.
[0094] In one embodiment of the present disclosure, the learning and analysis module 144 further comprises a result verification submodule 146, which is configured to receive diagnostic results confirmed by clinicians.
[0095] In one embodiment of the present disclosure, the learning and analysis module 144 further comprises a model weight adjustment submodule 148, which is configured to update analytical parameters based on result feedback.
[0096] In one embodiment of the present disclosure, the processing unit 112 further comprises a population analysis module 150 configured to aggregate anonymized triage trends by statistically processing stored urgency scores, risk classifications, and care progress results across multiple patient records to perform longitudinal pattern analysis.
[0097] In one embodiment of the present disclosure, the processing unit 112 further comprises a modular deployment module 152 that is configured to support cloud-based or local execution environments.
[0098] The storage unit 154 is connected to and configured with the processing unit 112 to store patient data, analytical results, urgency scores, routing decisions, and outcome feedback for continuous system operation.
[0099] In one embodiment of the present disclosure, the storage unit 154 further comprises a segmented data repository 156 configured to store image data, symptom data, and analytical outputs separately. The segmented data repository 156 enables controlled access, efficient retrieval, and independent lifecycle management of different data categories, thereby supporting data integrity, data protection, regulatory compliance, and optimized analytical processing. The segmented data repository 156 further facilitates selective updating, auditing, and anonymization of stored records without cross-contamination between raw clinical inputs and derived analytical results.
[0100] The second user device 158 is connected to the processing unit 112 via the communication network 110 and configured to receive triage outputs and recommendations for care pathways.
[0101] In one embodiment of the present disclosure, the second user device 158 may comprise a smartphone, a laptop, a tablet, a personal computer or a smart portable device.
[0102] and any other network-enabled electronic device capable of receiving and communicating triage outputs, clinical risk information, urgency points, patient data summaries and recommended treatment pathways via the 110 communication network, for the purpose of clinician-assisted remote dental assessment and triage.
[0103] The second user interface 160 is integrated into the second user device 158 and is configured to display risk information, urgency scores, patient data summaries, and override controls for clinician interaction. The second user interface 160 can also present explanatory indicators associated with triage outputs and provide override controls that allow clinicians to review, modify, confirm, or escalate system-generated triage and routing decisions.
[0104] In one embodiment of the present disclosure, the second user device 158 comprises the second user interface 160 in the form of a mobile or web-based application configured to facilitate structured interaction between the clinician and the system 100.
[0105] In one embodiment of the present disclosure, the system 100 is implemented as a kiosk-based dental screening station for use in public or clinical settings. The kiosk-based embodiment includes an integrated user interface, an image acquisition unit, and a communication module configured to guide users through symptom input and image acquisition, transmit collected data to the processing unit 112, and display triage results or referral instructions in real time.
[0106] Fig. illustrates a step-by-step process 200 for the execution of the dental triage and clinical risk assessment system 100, according to an embodiment of the present invention.
[0107] In step 202, the first user device receives 102 patient-related dental pieces of information for remote assessment.
[0108] At step 204, the first user interface presents 104 structured symptom questionnaires, instructions for image capture, and status notifications.
[0109] In step 206, the communication network 110 securely transmits patient-related dental information and control signals.
[0110] At step 208, the processing unit 112 accepts dental information transmitted via the communication network 110.
[0111] In step 210, the data acquisition module 114 captures patient-related dental information within the processing unit 112.
[0112] In step 212, the data preprocessing module 116 validates, normalizes and structures the dental information.
[0113] In step 214, the triage intelligence module 124 generates a quantified urgency score and a risk classification level.
[0114] In step 216, the decision support module 130 determines a recommended dental care pathway.
[0115] In step 218, the care navigation module 134 creates routing instructions for appropriate dental care.
[0116] In step 220, the learning and analysis module updates 144 internal analytical parameters based on confirmed clinical results.
[0117] In step 222, the storage unit 154 stores the analytical results of the patient data, urgency scores and routing decisions.
[0118] In step 224, the second user device 158 and the second user interface 160 present triage outputs, risk information and controls for clinicians.
[0119] Fig. Figure 300 shows a flowchart for a dental triage and clinical risk assessment method according to an embodiment of the present invention.
[0120] Method 300 may include the following steps.
[0121] In step 302, patient-related dental information is received via a first user device 102, while patient interaction is guided via a first user interface 104, which presents structured symptom questionnaires, image acquisition instructions, and status notifications.
[0122] In step 304, the patient-related dental information and control signals are transmitted via a communication network 110 to a processing unit 112.
[0123] In step 306, the patient-related dental information is recorded within the processing unit 112 by a data acquisition module 114.
[0124] In step 308, the patient-related dental information is validated, normalized and structured for analytical processing by a data preprocessing module 116.
[0125] In step 310, the structured dental information is analyzed by a triage intelligence module 124 to generate a quantified urgency score and a risk.
[0126] Classification level using combined analytical logic that integrates symptom patterns and extracted visual indicators.
[0127] In step 312, the urgency score and risk classification level are assigned to a recommended dental care pathway by a decision support module 130.
[0128] Step 314 involves the generation of routing instructions by a supply navigation module 134, corresponding to an emergency referral, a scheduled consultation, a teleconsultation, or automated guidance.
[0129] In step 316, internal analytical parameters are updated by a learning and analysis module 144 based on confirmed clinical results.
[0130] Step 318 involves storing patient data, analytical results, urgency scores, routing decisions, and result feedback in a storage unit 154 for continuous system operation.
[0131] At step 320, triage outputs and recommendations for supply routes are transmitted through the communication network 110 to a second user device 158.
[0132] At step 322, risk indicators, urgency scores, patient data summaries and override controls are displayed through a second user interface 160 for interaction with the clinician.
[0133] In one embodiment of the present disclosure, the second user interface 160 asynchronously captures the clinician's override actions and confirmed diagnostic results, which are processed by the result verification submodule 146 to validate clinical accuracy before analytical parameter updates are triggered by the model weight adjustment submodule 148 within the learning and analysis module 144.
[0134] In the optimal operating mode of the present invention, the dental triage and clinical risk assessment system 100 is deployed as a network-connected teledentistry platform accessible to patients and clinicians via their respective user devices. In a real-world deployment, a patient initiates a remote dental assessment by accessing the system 100 via the first user device 102 and running a mobile or web-based application, which constitutes the first user interface 104. The first user interface 104 guides the patient through structured symptom questionnaires, records the progression of symptoms over time, and assists in capturing intraoral images or radiographic data using standardized image acquisition instructions, lighting cues, and validation prompts to ensure clinically usable visual input. Upon completion of data entry, the patient's dental information, including...
[0135] Symptom data, images and associated metadata are securely transmitted through the 110 communication network to the 112 processing unit.
[0136] The data acquisition module 114 receives the transmitted information and forwards it to the data preprocessing module 116, which validates the completeness of the data, normalizes symptom values, structures inputs into predefined analytical formats, and prepares visual data for automated analytical processing.
[0137] The preprocessed visual data are then analyzed by the Image Feature Extraction Module 118 to identify clinically relevant visual dental indicators, including structural anomalies, lesions, discolorations or tissue irregularities, and to generate extracted visual features for subsequent analysis.
[0138] Following feature extraction, the symptom correlation engine 122 associates the extracted visual indicators with structured, patient-reported symptom parameters across multiple data fields to identify co-occurrence patterns and temporal relationships that indicate the severity of dental risk.
[0139] The processed data is then analyzed by the Triage Intelligence Module 124, which represents the core analytics engine of System 100.
[0140] In its best mode, the Triage Intelligence Module 124 applies a hybrid analytical framework that combines artificial intelligence-based models with predefined clinical decision rules to assess the severity of symptoms, progress indicators, extracted visual features, and patient risk factors.
[0141] Using a proprietary evaluation algorithm, the Triage Intelligence Module 124 calculates a quantified clinical urgency value in the form of a dental urgency index and assigns a corresponding risk classification level, such as critical, urgent, routine or preventive.
[0142] The rule assessment submodule 126 enforces predefined clinical thresholds and escalation criteria, while the probability ranking submodule 128 generates ordered probability values for potential dental conditions.
[0143] Following the determination of urgency and risk, the decision support module 130 receives the urgency value and the risk classification level and assigns them to a recommended dental care pathway by using standardized, rule-based clinical assignment logic.
[0144] This classification determines whether the patient should be referred to an emergency referral, an expedited in-person consultation, a scheduled appointment, a teleconsultation, or automated self-help guidance.
[0145] The decision support module 130 also generates explainability assignments that link the triage result with contributing symptoms, visual indicators and applied rules to enable transparency and interpretability for clinicians.
[0146] The recommended supply route is then operationalized by this.
[0147] The nursing navigation module 134 generates actionable routing instructions that correspond to the specified path. In real-world deployment, this can include initiating emergency escalation alerts via the emergency escalation sub-module 138, coordinating appointment scheduling via the appointment coordination sub-module 136, enabling teleconsultation workflows, or providing automated guidance to the patient via the first user interface 104. These routing actions can involve interfaces with external scheduling systems, notification services, or clinical platforms.
[0148] Triage outputs, care pathway recommendations, and supporting explanatory data are transmitted to the second user device 158, which a clinician accesses via the second user interface 160. The second user interface 160 presents summaries of patient data, risk information, urgency points, and recommended actions, while providing override controls that allow the clinician to review, modify, confirm, or escalate system-generated decisions. Clinician-confirmed diagnoses and outcomes are captured via the outcome verification submodule 146 and fed back into the learning and analytics module 144.
[0149] The learning and analytics module 144 updates internal analytical parameters via the model weight adjustment submodule 148 based on confirmed clinical outcomes, thereby improving triage accuracy over time. All patient data, analytical results, urgency points, routing decisions, and outcome feedback are securely stored in the storage unit 154, with image data, symptom data, and analytical outputs managed in a segmented data repository 156. In parallel, the compliance logging module 140 records time-stamped decision traceability data to support audit, regulatory review, and clinical governance requirements.
[0150] In large-scale deployments, the population analytics module 150 aggregates anonymized triage trends across multiple patients to support longitudinal analyses and healthcare planning. In best-case mode, the system 100 is deployed via the modular deployment module 152 in cloud-based, on-premises, or hybrid environments and interacts with electronic health records (EHRs) via the interoperability module 142, enabling seamless integration into existing dental infrastructures. Through this coordinated operational flow, the present invention provides automated, objective, explainable, and scalable dental triage and clinical risk assessment in real-world teledentistry environments. In the absence of a conflict, the embodiments described in the present disclosure and the features in the embodiments may be combined interchangeably.The foregoing descriptions are merely specific implementations of the present disclosure and are not intended to limit the scope of protection of the present disclosure. Any variation or substitution that is readily apparent to a person knowledgeable in the field, within the technical scope disclosed in the present disclosure, falls within the scope of protection of the present disclosure. Therefore, the scope of protection of the present disclosure is subject to the scope of protection of the claims.
[0151] The foregoing descriptions of specific embodiments of the present technology have been presented for illustrative and descriptive purposes. They are not intended to be exhaustive or to limit the present technology to the forms precisely disclosed, and obviously many modifications and variations are possible in light of the above teaching. The embodiments have been selected and described to best explain the principles of the present technology and its practical application, in order to enable other skilled persons to make the best possible use of the present technology and various embodiments with different modifications suitable for the intended specific use.It is understood that various omissions and substitutions of equivalents may be considered as circumstances suggest or make expedient, but such are intended to cover the application or implementation without deviating from the spirit or scope of the claims of the present technology.