488 results about "Dermatological diseases" patented technology

The invention provides application of UBR5 in preparation of drugs for treating pigmented skin diseases, and further the pigmented skin diseases comprise various types of pigmented nevus (mainly congenital pigmented nevus and megalous with the risk of malignant transformation). Various pigmented spots (mainly chloasma, freckles, Taitian nevus, post-inflammation hyperpigmentation and the like) and hypopigmentation / depigmentation spots (mainly leucoderma, post-inflammation hypopigmentation and the like). Experimental results show that UBR5 is highly expressed in disease tissues such as pigmented nevus. The UBR5 expression level and the melanogenesis ability are in significant positive correlation, targeted knockout / knockdown of UBR5 in melanocytes can significantly inhibit the expression level of melanogenesis related genes such as MITF, TRP1, TRP2, TYR and other proteins, the melanin content of melanocytes and tyrosinase activity, vice versa, and the melanogenesis ability of melanocytes after overexpression of UBR5 is significantly increased.

The invention provides a dermatoscope image segmentation method based on an attention mechanism and multi-scale information interaction, and belongs to the technical field of medical image segmentation. The technical problems that a traditional segmentation method is inaccurate in skin lesion area boundary recognition, insufficient in multi-scale feature extraction capacity and large in noise interference influence are solved. According to the technical scheme, the method comprises the following steps of 1, constructing a high-precision skin disease image data set; step 2, performing enhancement and standardization processing on the data set; 3, constructing a segmentation model based on an attention mechanism and multi-scale information interaction; 4, training the segmentation network by using the preprocessed data set, and optimizing the model performance by using a BCE-Dice combination loss function; and 5, inputting a test set to evaluate the performance of the model, and finally outputting an optimal segmentation result. The method has the advantages of being high in segmentation precision, high in boundary recognition capability and excellent in model robustness.

The invention discloses a skin focus segmentation method based on Mama edge information and an attention mechanism, and the method comprises the steps: S1, obtaining a data set, and dividing the data set; s2, connecting an encoder and a decoder in a jumping connection mode, and introducing edge information and an attention mechanism to construct an SMEANet network for skin focus segmentation; training parameters are set, and model training is carried out to obtain an optimal model; and S3, inputting the to-be-detected data into the Mama-based edge information and attention mechanism skin focus segmentation model to realize segmentation, and finally outputting a segmentation result. According to the segmentation method, the encoder and the decoder are connected in a jumping connection mode, edge information and an attention mechanism are introduced, the SMEANet network for skin focus segmentation is constructed, the accuracy of skin focus segmentation is improved, and therefore a more reliable basis is provided for clinical diagnosis.

The invention discloses an application of betulinic acid 28-O-beta-D-glucoside (BA-6 for short) in preparation of a medicine for preventing and treating skin inflammation. The problems that an existing medicine for treating dermatitis is limited in curative effect, slow in effect taking, multiple in side effect, high in long-term use risk, large in individual difference, high in treatment cost, likely to cause immunoreaction and the like are solved. The invention discloses application of BA-6 in prevention and treatment of atopic dermatitis, contact dermatitis, eczema, rash, psoriasis, lupus erythematosus, papule squamous skin disease, pityriasis rosea, seborrheic dermatitis, pemphigus, celestial abscess, acne, tinea corporis, impetigo, SAPHO syndrome, hidradenitis suppurativa, dermatitis caused by drugs, lichen planus, pityriasis rubra pilaris, vitiligo, prurigo nodularis, dermatitis caused by drugs, and the like for the first time. The traditional Chinese medicine composition can be used for treating skin diseases, systemic sclerosis, hidradenitis suppurativa, granulomatous skin diseases, vitiligo, dermatomyositis, chronic skin itch and alopecia areata, and has the technical progress of obviously improving skin erythema, papule, edema, scale, moss and ulceration symptoms.

Provided are methods and composition for treating skin barrier functions and associated disorders. Formulated compositions may be applied on human skin to maintain a desired skin surface pH over an extended period of time without irritating the skin. Maintaining the desired surface pH aids in treatment of eczema, in addition to other skin conditions.

The invention discloses a skin disease diagnosis method based on image recognition, and the method comprises the following steps: obtaining a to-be-detected skin image, and recording an equipment identifier; carrying out white balance correction, reflection suppression, hair suppression and scale normalization to generate a standardized image; positioning the focus to generate a focus mask; generating an enhanced view set in the focus mask by the enhanced view set according to the enhanced times and the enhanced view set; calculating a color invariant graph, a sign response graph and an artifact confidence graph, and synthesizing a potential energy field set according to a fusion weight; calculating a local structure tensor and generating a Riemannian metric matrix; constructing an improved Morse-Smal complex under a Riemannian metric matrix, carrying out cross-complex clustering on the critical point set to obtain a stable score, carrying out complex simplification to generate a stable Morse-Smal complex, and calculating the confidence coefficient of the cell boundary; and extracting structured feature vectors, diagnosing, judging and outputting disease categories, grading results and re-checking and marking. According to the invention, the anti-artifact and cross-device stability is improved.

The invention provides a skin lesion auxiliary detection method and system based on multi-modal information fusion, and belongs to the technical field of computer vision and application. The method comprises the following steps: firstly, acquiring and constructing bimodal data including a dermatoscope image and a text of a patient, and preprocessing the data; secondly, respectively adopting an improved convolutional neural network and a text coding model, and extracting deep and high-dimensional features from the skin disease image and the self-described text of the patient; afterwards, an improved symmetric gating cross attention fusion module is constructed, fine-grained interaction and alignment between visual and text features are realized through a bidirectional cross attention mechanism, and a gating unit is utilized to adaptively adjust a fusion weight; and finally, inputting the deeply fused multi-modal feature vector into a classifier to obtain a confidence score of each skin lesion type so as to provide reference for dermatologists. According to the method, the diagnosis accuracy, robustness and interpretability are synergistically improved, and the method has great clinical application value.

The invention belongs to the technical field of medical image and big data analysis, and provides an automatic skin disease diagnosis method and system based on a multi-modal big language model, and the method comprises the steps: obtaining a dermatoscope diagnosis report of a historical patient, and extracting an original image and a diagnosis text in the dermatoscope diagnosis report; constructing a multi-modal large language model, wherein the multi-modal large language model comprises a visual encoder, a linear projection layer and a large language model; training the multi-modal large language model; obtaining an external medical knowledge base, extracting text information in the external medical knowledge base, and constructing a vector database based on the text information; in response to an input image and a query text of a user, N vectors with the highest similarity are retrieved in the vector database according to the query text, the retrieved vectors are decoded into a text, and the text and the query text jointly construct complete prompt word input; and based on the input image and cue word input, obtaining a final dermatoscope diagnosis report by using the trained multi-modal large language model. The diagnosis report is automatically generated.

The invention belongs to the technical field of image recognition, and particularly relates to a skin disease classification recognition system based on deep learning, which comprises a skin image acquisition module, a skin image preprocessing module, a skin state classification module and a state classification optimization module, according to the system, a skin state recognition model is constructed, and a multi-head self-attention mechanism is introduced, so that skin state differences can be distinguished; local features are extracted through a space exploration CNN block, an AssemFormer block learns a global dependency relationship, the local features and the global features are fused, and a lesion mode can be understood; scale variant attention blocks are used for highlighting skin features of suspected lesion areas, Monte Carlo attention blocks are used for carrying out random sampling pooling calculation on feature representation, attention map enhancement blocks are used for generating attention maps, skin state categories are output, and skin state prediction labels are generated for each skin image, so that skin lesion details can be highlighted; quantitative reference is provided for medical staff, and skin state judgment is effectively assisted.

The invention relates to the technical field of intelligent medical assistance, in particular to a skin disease treatment electrode positioning system based on potential distribution. The system comprises a potential gradient severe region identification module, a lesion minimum surrounding region identification module, a similar potential region grouping module, an optimal electrode position prediction module, an electric field distribution calculation module, a sweat gland dense region identification module, an optimal electrode placement point screening module, an enhanced feature generation module and a final electrode position determination module. By fusing multi-source information such as skin surface potential distribution, lesion geometric characteristics, tissue conductivity, historical treatment data and the like, systematic optimization is performed on electrode positioning in skin disease treatment, the effectiveness of electrode stimulation is maximized on the premise of ensuring the treatment safety, and the treatment efficiency is improved. An accurate electrode placement scheme is provided for treatment of different types of skin diseases, and the method is suitable for accurate determination of the electrode placement position in electrical stimulation treatment.

The invention provides a multi-enhancement semi-supervised medical image classification method based on a dynamic threshold value, and the method comprises the steps: obtaining a labeled image and a non-labeled image based on a skin disease image data set, building an initial semi-supervised image classification model through the labeled image and the non-labeled image based on deep learning, and carrying out the classification of the initial semi-supervised image. Respectively processing and merging the images with the labels and the images without the labels, obtaining a loss function based on a merging result, optimizing the initial semi-supervised image classification model based on the loss function to obtain a target semi-supervised image classification model, and evaluating and adjusting the target semi-supervised image classification model based on a performance evaluation index to obtain a target semi-supervised image classification model. The accuracy and generalization ability of the skin lesion image classification model are improved, and the dependence on large-scale manual annotation data is reduced by designing an effective learning mechanism, so that the annotation cost is reduced, the training efficiency is improved, the robustness of the model to the image data distribution change is enhanced, and the stable and consistent classification performance is kept.

The invention discloses a natural component composition for conditioning skin micro-ecology, a preparation method of the natural component composition and application of the natural component composition in skin care products for children. The composition comprises a synergistic combination of a sphingomonas fermentation product extract, a haematococcus pluvialis extract rich in astaxanthin, an abelmoschus esculentus fruit extract rich in polysaccharides, and a yeast / zinc fermentation product. The present invention provides improvements in astaxanthin in terms of chemical stability and transdermal permeability. The composition aims to enhance the immature skin barrier, provide a good effect, and support the healthy development of skin microecology, thereby solving the unique physiological needs of children's skin. The invention also describes a preparation method of the composition and application of the composition in cosmetics for children and dermatological products.

The invention relates to the technical field of medical artificial intelligence and computer vision, in particular to a skin disease feature recognition method based on image processing, and the method comprises the following steps: S1, obtaining multi-modal data of a skin lesion region, including an RGB image, a thermal imaging image and a patient medical history text; s2, performing illumination correction, noise suppression and lesion region segmentation on the image data; the skin disease feature recognition system based on image processing comprises the following contents: a multispectral image acquisition module supporting synchronous acquisition of visible light, infrared and depth data; in the using process of the method and system, the diagnosis efficiency and accuracy of medical staff can be improved, the medical staff can be effectively assisted to analyze and confirm the type of the illness state, and meanwhile the doctor seeing efficiency of the medical staff can be effectively improved.

The invention discloses an intelligent skin disease recognition system and screening method based on image features, and relates to the technical field of artificial intelligence. Skin disease image data are collected and uploaded to the labeling system, and label labeling is completed through assistance of professional doctors. The constructed skin disease data set covers dermatoscope type data and clinical shot image data. Performing data enhancement, standardization, normalization and image size unified adjustment on the labeled data, and inputting the data into a deep learning model for training; a deep neural network DCSNeXt model suitable for skin disease image feature recognition is designed and constructed, a special classifier is designed according to data categories, and model training and performance testing are carried out on the two types of data; a plurality of existing common image recognition models are further used for carrying out training testing on the data set, and the performance of the data set is compared with the performance of a DCSNeXt model on a test set; in addition, two types of skin disease image data in related literatures in recent two years are collected, and a model with good performance is selected to carry out label-free prediction analysis on the skin disease image data. According to the invention, intelligent characterization analysis of dermatoscope and clinically shot dermatosis images can be realized, technical support is provided for feature extraction and classification of dermatosis images, the method can be widely applied to the fields of dermatology department clinical auxiliary analysis, telemedicine and medical teaching, and development of dermatosis intelligent analysis is promoted.

The invention provides a skin disease auxiliary evaluation system and device, a storage medium and a program product, and relates to the technical field of edge computation.The skin disease auxiliary evaluation system is deployed on a terminal device and comprises a feature extraction module, a feature extraction module and an evaluation module, obtaining semantic feature information corresponding to a disease description text in the skin disease information and image feature information corresponding to an affected part image in the skin disease information; the feature fusion module is used for associating the semantic feature information with the image feature information based on a cross attention mechanism to generate first multi-mode fusion feature information of the skin disease to be evaluated; and the large language model evaluation module is used for generating an evaluation result corresponding to the to-be-evaluated skin disease through a first large language model based on the first multi-mode fusion feature information.

Various implementations of the invention relate to a silicon-embedded multi-spectral lidar system and method for non-invasive, remote monitoring of pathological conditions of an individual. The system integrates multiple laser sources, photodetectors, and a processing module onto a silicon chip, enabling the capture and analysis of spatial, spectral, scattering and temporal data from a target subject (e.g., individual). By utilizing lidar signals at various wavelengths, various implementations of the invention detect three-dimensional (“3D”) surface and subsurface features such as micro-movements, vascular patterns, pigmentation changes, and tissue differences and / or irregularities. Machine learning algorithms process this information from the lidar to identify and classify abnormalities, enabling applications such as heart rate and respiration monitoring, eye movement tracking for neurological and mental health assessment, and detection of pathological skin conditions like cancer. Various implementations of the invention operate in real-time, adapt to environmental conditions, and support dynamic monitoring over time, thereby providing a comprehensive, non-contact solution for diagnostics and telemedicine, for example. Various implementations of the invention may comprise a compact silicon chip form factor suitable for portable and / or hand-held, scalable health monitoring applications across diverse environments.

The invention relates to the technical field of animal cub culture, in particular to an animal cub culture device for animal husbandry veterinarians, which comprises a culture box, a transparent door plate slidably connected to the culture box, a hollow plate inserted into the culture box, an excrement groove hung at the rear end of the culture box, a diversion groove formed in the lower end in the culture box, and a discharge groove formed in the rear wall of the culture box. The driving assembly is located in the incubator and comprises two movable blocks, the upper ends of the movable blocks are fixedly connected with push blocks, a guide rail is fixedly arranged on the top face of the upper end of the incubator, the upper ends of the two push blocks are slidably connected with the guide rail, and the outer walls of the two sides of each movable block are communicated with a plurality of nozzles. The flushed and disinfected area is dried through hot air, the cleaning effect of excrement of the cubs is improved, excrement residues are reduced, bacterium breeding is reduced, a healthy environment is provided for cub culture, and the morbidity of diarrhea, skin diseases and the like of the cubs is reduced.

The invention relates to the technical field of immunodetection, and discloses a bovine nodular skin disease virus chimeric antigen and application thereof in an ELISA (enzyme-linked immuno sorbent assay) detection kit. According to the chimeric antigen, a gene of a dominant region of a bovine nodular skin disease virus antigen is selected to design a chimeric antigen gene, meanwhile, sequence optimization is performed, a chemical synthesis method is used for synthesizing a coding gene of the chimeric antigen of the bovine nodular skin disease virus, and then the chimeric antigen is obtained in a prokaryotic expression mode. An ELISA antibody detection kit developed on the basis of the chimeric antigen has extremely high sensitivity and specificity, can rapidly and specifically detect bovine nodular skin disease virus antibodies in serum, is suitable for monitoring and checking the nodular skin diseases of cattle in large-scale breeding, and has relatively high practical value.

The invention discloses a skin lesion image segmentation method and device based on deep learning, and belongs to the technical field of medical image processing and computer vision. The method comprises the following steps: acquiring a skin lesion image data set, and preprocessing the skin lesion image data set; constructing an RMS-Unet model based on the improved U-net network, wherein the model comprises a residual structure-convolution module, a channel-space attention module, a feature fusion module and a multi-scale convolution module; and training the RMS-Unet model by using the skin lesion image data set, and performing skin lesion image segmentation by using the trained RMS-Unet model. The RMS-Unet model adapts to the diversity and complexity of the skin lesion image by solving the problem of noise interference in the skin lesion image and the inherent induction deviation of a segmentation task, and effectively improves the segmentation precision of the complex skin lesion image while the parameter quantity and the model complexity are not remarkably increased.

The invention provides a compound of formula (I)wherein:A, B, C, D, W, X, Y and Z are each independently selected from H and OH;or a salt thereof;for use in the treatment and / or prevention of a skin condition in a subject, wherein the compound of formula (I) or salt thereof is administered topically. The invention further provides topical compositions of a compound of formula (i) and processes for the preparation of said compositions.

A medical skin lesion segmentation method based on a multi-scale feature matrix yoke belongs to the technical field of image processing, and comprises the following steps: 1, carrying out preprocessing such as denoising on a skin lesion image, obtaining a plurality of image features by using a gray level co-occurrence matrix method, and constructing a three-dimensional multi-scale image feature matrix; 2, carrying out yoke transformation on the three-dimensional multi-scale characteristic matrix to construct a multi-scale characteristic matrix yoke according with the characteristics of a yoke process; 3, modeling a two-dimensional Markov random field model, and creating an energy function based on a multi-scale feature matrix yoke; and 4, performing post-processing operations such as morphology on the obtained result. According to the method, the features obtained from the gray-level co-occurrence matrix are constructed into the three-dimensional multi-scale feature matrix yoke, and the new Markov random field energy function is constructed on the basis, so that a better segmentation effect can be obtained.

The invention provides systems and methods for diagnosing and treating an inflammatory skin disease in a patient. The described methods may be used for longitudinal monitoring of the development, progression, or regression of a skin disease including lupus, psoriasis, atopic dermatitis, and systemic sclerosis (scleroderma) condition in a patient, in response to a therapy administered for the condition.

The invention relates to a traditional Chinese medicine lotion for treating infantile eczema and a preparation method thereof. The traditional Chinese medicine lotion is prepared from the following raw materials in parts by weight: 20-40 parts of honeysuckle, 20-40 parts of cortex dictamni, 25-35 parts of cicada slough, 10-20 parts of raw mint, 13-23 parts of scutellaria baicalensis, 85-95 parts of vine of multiflower knotweed, 25-35 parts of fructus forsythiae, 22-32 parts of fried fructus aurantii, 25-35 parts of dandelion and 13-23 parts of raw liquorice. The traditional Chinese medicine composition follows the medication principle of monarch, minister, assistant and guide of traditional Chinese medicines, and the honeysuckle and the cortex dictamni in the formula are compatible to serve as monarch drugs. The cicada slough, the mint and the scutellaria baicalensis are compatible and are used as ministerial drugs. And the four raw materials including the vine of multiflower knotweed, the fructus forsythiae, the fructus aurantii and the dandelion are compatible and are used as adjuvant drugs. And liquorice is used as a conductant drug for harmonizing the medicines. The medicinal materials are combined to achieve the effects of dispelling wind, clearing heat, removing dampness and relieving itching, and the traditional Chinese medicine composition is suitable for various skin diseases such as urticaria, eczema, insect bite inflammation and allergic dermatitis caused by wind-heat rheumatism of children and infants, does not relapse after being treated, and avoids the side effects that many complications occur after hormone medicines are used for a long time and the skin diseases are prone to relapse after medicine withdrawal.

The invention belongs to the technical field of pet products, and particularly discloses a novel anthelmintic based on fipronil drops, which can effectively reduce the bacterial or fungal infection caused by parasites on the body surface or skin of pets by combining the antibacterial effects of fipronil, citronella extract and tripterygium wilfordii. The fipronil can quickly kill parasites, the citronella extract can further reduce breeding and contact of the parasites through a repelling effect, so that the overall effect of the medicine is accelerated, the citronella extract further reduces the secondary infection risk caused by the parasites by inhibiting growth of bacteria, and the tripterine further reduces the secondary infection risk caused by the parasites by inhibiting pathogenic microorganisms of skin. Through the synergistic effect of multiple components, the development of drug resistance of parasites to a single component can be reduced.

The present invention relates to an antimicrobial and healing formulation for skin, designed to effectively target and treat skin conditions such as acne caused by Cutibacterium acnes, cold sore lesions due to the herpes simplex virus, and superficial wounds. This unique formulation combines antimicrobial agents, plant extracts and essential oils in specific proportions in order to exert a synergistic action, enhancing their individual efficacy in the treatment of skin conditions and promoting skin healing. The innovative formulation composed of niaouli (Melaleuca viridiflora) essential oil and tea tree (Melaleuca alternifolia) essential oil, chlorhexidine digluconate, Hamamelis virginiana extract, panthenol, glycerol, and propylene glycol. Each ingredient has been selected for its proven pharmacological properties and its synergistic potential. The formulation works in concert to reduce microbial load, alleviate inflammation, and accelerate skin healing, while providing a gentle and effective application.

The invention discloses a medical image segmentation method and device, equipment and a medium, and relates to the technical field of medical image segmentation, and the method comprises the steps: obtaining to-be-processed population data; the population data to be processed comprises multiple groups of skin lesion images, the skin lesion images comprise candidate key point sets, and each group of candidate key point sets is used for representing a boundary region of the skin lesion image; preprocessing each group of candidate key point sets to obtain a boundary diagram containing a boundary region; processing the boundary image and the corresponding skin lesion image through a trained image segmentation model, and outputting an image segmentation result; the image segmentation model comprises an encoder, a fusion module and a decoder; the encoder comprises a lightweight dynamic fusion module, a local edge guiding module and an attention module which are connected in sequence. According to the method, the parameter quantity is reduced while the model segmentation precision is ensured, the method can be conveniently deployed on edge equipment such as a mobile terminal and portable equipment, and the real-time performance of image segmentation processing is improved.

The invention discloses a percutaneous barrier function evaluation method and system based on precise temperature and humidity control. The method comprises the steps that S1, an individualized skin barrier baseline model containing daytime fluctuation characteristics and temperature and humidity sensitivity parameters and a baseline database are constructed; s2, executing an environment adaptability evaluation scheme through dynamic temperature and humidity spectrum scanning; s3, multi-dimensional skin physiological parameters are collected, a static parameter set and a dynamic parameter set are distinguished, and data standardization is achieved through dynamic baseline subtraction and cross-parameter interference compensation by adopting a physiological constraint type data correction algorithm based on a skin physiological relevance matrix; s4, integrating the standardized parameters to calculate a comprehensive barrier function index; and S5, predicting a barrier function trend. The system comprises a precise environment control module, a multi-parameter acquisition module, an intelligent analysis module, a data storage and interaction module and a central processing module, the accuracy and comprehensiveness of percutaneous barrier function evaluation can be improved, and technical support is provided for skin health management, skin disease diagnosis and treatment and the like.

The present invention relates to a composition comprising a mixture of exosomes derived from different cells, as an active ingredient and use thereof. More specifically, the present invention relates to a composition for treating skin diseases and / or improving skin conditions, comprising, as an active ingredient, mixed exosomes or fused exosomes in which natural killer cell-derived exosomes and mesenchymal stem cell-derived exosomes are mixed or fused. The composition according to the present invention exhibits an excellent cell proliferation effect and the effect of promoting collagen production, and thus can be effectively used as not only a cosmetic material for improving skin conditions, such as by reducing skin wrinkles, regenerating wounds, and increasing elasticity, but also a pharmaceutical material for preventing or treating skin diseases such as atopic dermatitis.

The invention discloses application of METTL1 as a target spot in preparation of a medicine for treating erythema squamous skin diseases, relates to the field of biological medicines, provides a new scheme for treatment of erythema squamous skin diseases, especially psoriasis and atopic dermatitis, relieves inflammatory response of psoriasis or atopic dermatitis by inhibiting expression of METTL1, and provides a new application of METTL1 as a target spot in preparation of medicines for treating erythema squamous skin diseases, especially psoriasis and atopic dermatitis. And erythema, scales and skin thickness are reduced.

The invention belongs to the technical field of traditional Chinese medicine, and particularly relates to a traditional Chinese medicine decoction for treating vitiligo and a preparation method thereof.The traditional Chinese medicine decoction for treating vitiligo is prepared from ten medicinal materials including notopterygium root, divaricate saposhnikovia root and the like according to the core pathogenesis of vitiligo rheumatism stagnated heat syndrome, the brand new theory of treating both black and white diseases and both black and white diseases is creatively provided, and on the basis of the theory, the traditional Chinese medicine decoction for treating vitiligo is prepared into the traditional Chinese medicine decoction for treating vitiligo. White spots and surrounding deepened skin are brought into systematic conditioning for the first time, the formula is compatible with black and white medicine pairs, black is used for treating white, white is used for treating black, overall conditioning and two-way adjustment are achieved, the white spots can recover to the normal skin color, and due to the innovative application of the two groups of black and white medicine pairs (wine-processed rhizoma chuanxiong, radix angelicae sinensis, radix rehmanniae preparata and radix paeoniae alba) in the formula, black is used for treating white, white is used for treating black, and two-way adjustment is achieved. And meanwhile, the clinical piebald skin disease symptom is also eliminated, so that the white spots recover to the normal skin color.