13 results about "Screening programs" patented technology

This invention discloses a machine learning model integrating oral microbiome and clinical features and its application in predicting sarcopenia at high altitudes. The method targets high-altitude populations residing at altitudes >3500 meters, collecting oral microbiome 16S rRNA sequencing data, clinical features, and lifestyle data. Core predictive factors are selected through adaptive preprocessing and elastic network regularized regression, and a classification model is constructed using logistic regression. To address the sample imbalance problem in high-altitude areas, this scheme introduces a synthetic balanced sampling strategy based on target distribution doubling; simultaneously, Platt Scaling is used for two-layer probability calibration, combined with a dynamic threshold optimization mechanism based on F1-Score to improve discrimination accuracy. This invention is the first to integrate oral microbiome shaped by the high-altitude environment (such as…)… Selenomonas , Veillonella (etc.) are incorporated into the predictive model. Experiments show that the model achieves an AUC of 0.868 on the independent test set and has advantages such as being completely non-invasive, low-cost, and highly interpretable. This invention provides an efficient early screening program for sarcopenia in resource-scarce high-altitude areas.

To provide a new technique for allowing only an invited person who has been examined to invite a human resource.SOLUTION: A personnel registration system 0 for registering personnel, the personnel registration system including a storage unit, a reception unit, an examination determination unit, and a personnel registration unit, the storage unit storing examination information for examining whether to invite personnel, the personnel registration system according to claim 1, wherein the acceptance unit accepts invitee information of an invitee who is to invite a personnel member, the examination determination unit determines whether to allow the invitee to invite the personnel member based on the invitee information and examination information, and the personnel registration unit registers a candidate to be invited by the invitee who is permitted to invite the personnel member based on a result of the determination.SELECTED DRAWING: Figure 1

The invention provides a method for exporting NC programs in batches based on CATIA. The method comprises the steps of judging document types, checking PP Table, selecting an output mode, obtaining a program object set, screening program objects, extracting or initializing post-processing information, operating an interface and storing settings, extracting and recording attribute data, outputting APT and converting the APT into the NC programs. The effects that the NC programs are output in batches through one-time setting and accurate tool information of the NC program heads are guaranteed are achieved, when the NC programs are output again, the setting information can be reused, the output efficiency of the machining programs can be remarkably improved, and the quality risk can be reduced.

The present invention improves efficiency of data extraction.　A processing unit (12) receives a designated number of pieces of data to be extracted from among a plurality of pieces of data each indicating a point in an N-dimensional space (20) (where N is an integer of 1 or greater). The processing unit (12) divides the N-dimensional space (20) into a first number of areas. For each of the first number of areas, the processing unit (12) performs a selection process for selecting one piece of data out of pieces of data from among the plurality of pieces of data which are present in the area. The processing unit (12) determines whether or not the total number of pieces of selected data is the same as the designated number. When the total number is not the same as the designated number, the processing unit (12) changes the number of areas partitioning the N-dimensional space (20) to a second number different from the first number, and performs the selection process.

The invention relates to an integrated multimodal artificial intelligence platform designed to function as an autonomous hospital system providing end-to-end health prevention, screening, diagnosis, treatment optimization, and longitudinal digital-twin-based monitoring. The platform introduces a closed-loop clinical architecture that continuously analyzes heterogeneous patient data including radiology, pathology, genomics, laboratory findings, longitudinal clinical records, wearable streams, and environmental exposures. A multimodal transformer (MT-X) generates a unified patient-specific representation, enabling high-precision diagnostic and prognostic inference. A novel Autonomous Screening Interval Generator (ASIG) dynamically determines individualized screening schedules based on calibrated risk models and temporal disease-evolution forecasting. A Digital Twin Engine (DTE) simulates tumor progression, metastasis probability, toxicity trajectories, and therapy response. An Adaptive Therapy Optimization Engine (ATOE), based on reinforcement learning, identifies optimal treatment strategies tailored to patient biology and system-level constraints. The invention is industrially applicable to hospitals, centers, national screening programs, tele-networks, and Al-enabled health systems. The integrated nature of the invention, the closed-loop framework, and the combination of digital-twin simulation with intelligent screening and therapy design constitute a substantial improvement beyond conventional medical Al solutions.

The invention provides an artificial-intelligence–based platform for automated analysis of Pap smear slides. The system integrates preprocessing, dual deep learning models (CNN-Transformer and EfficientNet-LSTM), and reporting modules to classify cytological images into diagnostic categories including NILM, ASC-US, LSIL, HSIL, and SCC. The platform includes interpretability outputs, secure data management, and active learning capabilities, enabling scalable, accurate, and transparent cervical-cancer screening across diverse laboratory settings. The platform is suitable for implementation in clinical pathology laboratories, telemedicine networks, and population-level screening programs. It allows rapid, reproducible, and objective evaluation of cytology slides, improving throughput while reducing reliance on manual slide examination. The invention is deployable on local servers, private clouds, or public cloud infrastructures and is adaptable to various cytology specimens. Adoption of this system enhances early detection of precancerous lesions, reduces inter-observer variability, and facilitates integration with laboratory information systems. It also supports continuous learning and adaptation to evolving imaging protocols. The invention provides multiple advantages over existing methods: (1) Dual-model architecture combining CNN-Transformer and EfficientNet- LSTM ensures robust classification across both dense and sparse cellular regions. (2)Preprocessing and adaptive tiling improve feature extraction from variable-quality images. (3)Interpretability modules enhance clinician trust and facilitate regulatory compliance. (4) Active learning allows continuous improvement based on expert feedback. (5) Modular deployment supports both local laboratory and cloud-based operation. (6) Data security features meet international standards for privacy and encryption. (7) High scalability enables screening of large slide volumes without compromising accuracy. The invention provides a clinically relevant, efficient, and technologically advanced solution for automated cervical-cancer screening, applicable in diverse healthcare environments and adaptable to future cytology domains.

This application discloses a screening device and method, belonging to the field of testing. The screening device provided by this application includes: a power-on board and a chip under test (DUT); the power-on board includes a memory, a controller, and a test base, the memory being connected to the controller, and the controller being connected to the test base; the test base is connected to the DUT; the controller is used to acquire target screening information pre-stored in the memory and import the target screening information into the DUT via the test base; the target screening information includes a screening program and target screening conditions; the controller is also used to control the DUT to run the screening program, and during the running of the screening program, based on the target screening conditions, obtain the screening result of the DUT; wherein, the screening result is used to determine the grade of the DUT. This application is used for grade screening of chips under test.

The present invention relates to an artificial intelligence–driven platform designed for comprehensive genetic counseling, hereditary cancer risk assessment, and automated pedigree analysis. The invention integrates genomic data, clinical features, and multigenerational family history through advanced data modeling and machine learning algorithms to enable precise, scalable, and evidence-based genetic consultation. Traditional genetic counseling processes are labor-intensive, requiring manual pedigree construction and subjective evaluation of variant pathogenicity and familial inheritance. These limitations result in delayed risk stratification and inconsistent preventive recommendations. The disclosed platform overcomes these shortcomings by introducing an intelligent, interoperable system that automates the acquisition, normalization, and interpretation of heterogeneous genetic and clinical data to deliver real-time, individualized counseling outcomes. The system comprises five primary modules: (1) a data acquisition module, (2) a data processing and inference engine, (3) a pedigree generation and visualization unit, (4) a counseling and recommendation module, and (5) a secure cloud-based user interface. The data acquisition module receives and harmonizes multi-source inputs including genomic sequencing results, variant annotation files (such as VCF or BAM formats), patient demographics, electronic health records (EHRs), and family medical history collected via structured questionnaires or natural language processing (NLP) of unstructured clinical notes. The processing engine employs supervised and unsupervised machine-learning models trained on large-scale, anonymized datasets of hereditary cancer syndromes, enabling the prediction of gene-level pathogenicity, inheritance mode, and personalized disease susceptibility. The AI model calculates individualized hereditary risk scores, integrating polygenic risk factors and family aggregation metrics. The pedigree generation module automatically constructs interactive multigenerational family trees, highlighting affected members, carriers, and probable inheritance patterns using graph-based inference algorithms. This visualization facilitates intuitive understanding of familial transmission, carrier probability, and consanguinity. The counseling module translates computed risk profiles into actionable, evidence-based recommendations, aligned with international clinical guidelines such as NCCN, ACMG, and ESMO. These outputs include suggestions for confirmatory genetic tests, early screening programs, lifestyle modifications, and targeted preventive interventions. Reports are automatically generated for both clinicians and patients, promoting consistent and reproducible genetic counseling. The user interface operates as a secure, GDPR- and HIPAA- compliant digital platform accessible via web or API integration with hospital information systems. In certain embodiments, the platform supports federated learning across multiple institutions or countries, ensuring model improvement without direct data sharing, thereby preserving patient privacy and data sovereignty. In one embodiment, the system is validated across data cohorts from at least eight countries to ensure cross-population generalizability of its predictive models. The platform's modular design allows integration with additional AI-based oncology tools, digital pathology systems, and precision medicine workflows. Overall, the invention provides a robust and scalable technological infrastructure that transforms genetic counseling from a manual, expert-dependent process into a data-driven, automated, and globally interoperable service. By combining AI-based analytics, dynamic pedigree visualization, and standardized preventive guidance, the invention significantly enhances the accuracy, accessibility, and cost-effectiveness of hereditary cancer risk management.

The utility model discloses a kind of mudification ore screening devices, it is related to screening equipment technical field, including support and the bottom plate of fixed connection in support bottom, the output end of first motor is fixedly connected with first rotating rod, the end of first rotating rod is fixedly connected with connecting rod, the lower side of connecting rod is movably connected with transmission rod, the side of transmission rod away from connecting rod is movably connected with U-shaped piece, the inner wall of both sides of support is movably connected with upper movable bolt, deflection rod is movably connected on support, the inner side of both sides lower movable bolt is fixedly connected with screening box, in the utility model, by the mutual transmission of connecting rod, transmission rod, U-shaped piece, so that screening box is shaken and screened, then under the action of first screening groove and second screening groove, to carry out sufficient screening to mudification ore, and then obtain higher quality finished product, avoid the screening program of prior art only once, screening effect is poor, reduce the finished product quality after mudification ore screening, and easily cause the problem of jam.

This invention provides an automatic crab sorting device, comprising: a base, a sorting box, a vision scanner, a control end, and a feeding end. The upper end of the base determines the position of the sorting box, and the upper end of the sorting box is connected to the vision scanner. The control end is located on the outer side of the feeding end, and the feeding end is connected to one end of the sorting box. This invention improves upon the sorting box by allowing the load-bearing conveyor shaft to transport crabs normally through the movable cavity of the box. Then, combined with an automated sorting program, a pusher pushes the crabs into the loading structure. Once the loading box is full, it can be pulled out directly, detaching from the assembly block, thus achieving quick disassembly or subsequent linear re-push-in. This avoids the difficulty of removing and sorting crabs after a full load, which is a problem with traditional methods that rely on strong, fixed components. Furthermore, the weight of the loading box can be monitored in real time, triggering alarms and requiring replacement.

The present disclosure is a screening procedure that allows for the identification of inhibitors of cell envelope protease (CEP) in pathogenic bacteria by the use of lactic acid bacteria (LAB). In some embodiments, a screening platform can be used to screen a library of compounds, thereby generating a high throughput assessment of drug candidates, and it has been demonstrated by example that a single screening of 6808 compounds identifies 20 CEP inhibiting compounds of Lactococcus lactis.

The invention discloses an intelligent subject screening system for clinical trials, and relates to the technical field of clinical trials, and the system comprises a subject screening management end which comprises a research target making module, a selection standard making module and a screening program module; the subject screening execution end comprises a subject collection module, a subject screening module and a standard exclusion module, and the standard exclusion module is used for formulating an exclusion standard after determining subjects meeting conditions so as to exclude subjects not suitable for participating in research; the subject screening server side comprises a subject selection module, a subject informed agreement module and a supervision tracking module, the subject selection module is used for selecting subjects meeting selection standards to participate in research according to screening results, and the subject informed agreement module is used for determining that the subjects know agreement research content; and the supervising and tracking module is used for supervising and tracking the subject according to the research plan. The method has the effect of reducing the screening difficulty of the subjects.