16 results about "Symptom improvement" patented technology

The invention discloses an internal medicine drug curative effect evaluation method based on big data analysis of an electronic health record, and the method comprises the steps: extracting basic health data, diagnosis and treatment time sequence data and drug intervention data from the electronic health record, and carrying out the time-space alignment to generate a dynamic feature set; subgroups are obtained based on disease typing standard hierarchical clustering, and historical data and real world data are fused through transfer learning to construct a subgroup curative effect reference matrix; collecting data after medication in real time, and generating an evaluation vector containing short-term physiological response, middle-term symptom improvement and long-term prognosis risk through deep learning; dynamically matching the evaluation vector with the reference matrix, and introducing an individual weight coefficient to correct deviation; taking the deviation correction value as input, constructing a self-adaptive evaluation model through reinforcement learning, and performing iterative optimization; and generating an individualized report containing the curative effect level, the medication suggestion and the risk early warning, and quantifying the curative effect level through a fuzzy comprehensive evaluation method. According to the method, individual differences are accurately captured, full-cycle dynamic evaluation is realized, and the curative effect evaluation accuracy and the clinical decision-making efficiency are improved.

The invention relates to the technical field of data processing, and discloses a hydrocephalus correlation analysis method and system based on multi-dimensional data. The method comprises the steps that a feature matrix is generated by obtaining and standardizing hydrocephalus multi-dimensional data, after the matrix is discretized, an association rule mining algorithm is adopted to extract an association mode, a rule set is obtained in combination with knowledge graph verification, data clusters are divided based on mahalanobis distance clustering, mixed effect time sequence model fitting parameters are established for all the clusters, and a mixed effect time sequence model is obtained. And calculating a target sample attribution cluster and predicting a symptom improvement trajectory and a confidence interval. According to the method, automatic integration, credible association rule extraction, precise subtype division and individualized symptom trajectory prediction of the multi-dimensional data of the hydrocephalus patient are realized.

The invention provides an application of beta-1, 3 / alpha-1, 3-glucan in preparation of a medicine for treating or / and preventing chronic rhinitis. The beta-1, 3 / alpha-1, 3-glucan disclosed by the invention is used for treating or / and preventing chronic rhinitis, is remarkable in symptom improvement, high in safety and wide in application range, can be used for chronic rhinitis patients with different severity degrees, and provides a new choice for long-term management of chronic rhinitis.

The invention relates to the technical field of skin care products, in particular to a composition with a synergistic effect of resisting acnes and photo-thermal damage and application. The composition is prepared from the following components: rhodomyrtus tomentosa fruit extract, dendrobium nobile stem extract, tephros glauca seed extract, verbascin root extract and cocoa seed fat, and the five components are synergistically regulated and controlled to synchronously realize dual effects of improving acne and relieving photo-thermal induced aging signs; through a multi-target and multi-layer action mechanism, collaborative intervention is performed from four key pathological links of regulating micro-ecological imbalance, blocking inflammation cascade reaction, repairing physical and biological barriers and neutralizing oxidative stress, a collaborative intervention network aiming at acne generation and photo-thermal aging is constructed, and the comprehensive effect from symptom improvement to root protection is achieved.

The present disclosure relates to compositions and methods for treating a maladapted stress response involving the corticotropin-releasing factor receptor subtype 2 (CRFR2), such as myalgic encephalomyelitis / chronic fatigue syndrome or an impairment of the musculoskeletal or the nervous system, resulting in measurable symptom improvement.

The invention discloses a microbial marker for treating irritable bowel on the basis of coprophilous fungus transplantation and a screening method of the microbial marker. The microbial marker is prepared from the following components: Butyrimonas faecalis, Odoribacter laneus, Parabacteroides verdea, Bacteroides eggerii, Phocaeia massiformis, Phocaeia dorrei, Phocaeia vulgaris, Bacteroides nordii, Phocaeia viscera, Muriaceae bacteria, Clostridium fesum, Saccharomyces cerevisiae, Saccharomyces cerevisiae, Saccharomyces cerevisiae, Saccharomyces cerevisiae, Saccharomyces cerevisiae, Saccharomyces cerevisiae, Saccharomyces cerevisiae, Saccharomyces Through metagenome sequencing and a machine learning algorithm, the key microbial markers significantly related to intestinal stress symptom improvement in the coprophilous fungus transplantation treatment process are screened out, and a scientific basis and a standardized scheme are provided for coprophilous fungus transplantation treatment of irritable bowel.

The invention discloses an rTMS electrical stimulation dose quantification method. The method comprises the following steps: obtaining brain structure information, neuron characteristic information and a clinical diagnosis result of a target patient; based on the clinical diagnosis result, determining the type stage of the disease of the target patient; based on the type stage of the disease of the target patient, matching with a disease brain region electrical stimulation library to obtain electrical stimulation parameters; determining a first electrical stimulation dosage of the target patient based on the brain structure information, the neuron characteristic information and the electrical stimulation parameters; performing treatment based on the first electrical stimulation dosage, and inputting symptom improvement condition data, neural electrophysiological index data and iconography index data of the target patient obtained by monitoring in the treatment into a prediction model to obtain a second electrical stimulation dosage; the prediction model is obtained by training based on sample data and a corresponding electrical stimulation dose label result. According to the invention, the electrical stimulation dosage can be accurately matched with each patient, and the treatment effect is improved.

The invention discloses a dialogue type disease diagnosis method based on large language model feedback, the method combines a reinforcement learning module and an expert feedback module, the expert feedback module comprises a dynamic symptom attention mechanism, interaction record management and Prompt construction, the dynamic symptom attention mechanism dynamically distributes weight for each symptom, and the interaction record management is performed on the interaction record management and Prompt construction; the model is helped to focus on key symptoms, so that diagnosis accuracy is improved, interaction record management uses a historical record retrieval method to extract 10 most similar records from the interaction history of a user, the decision basis of the reinforcement learning model is further enhanced, Prompt construction is combined with system prompt, example prompt and current prompt, and the accuracy of diagnosis is improved. The large language model is guided to generate accurate score feedback in medical reasoning, and finally the accuracy and stability of a disease diagnosis system are improved. The method can effectively cope with challenges of scarcity symptoms and complex symptom combinations, help the model focus on key symptoms, and improve symptom query strategies.

Described herein are proteases of any of SEQ ID NOs: 6-14 or a proteolytically active variant thereof with greater than 85%, 90%, 95% or 98% sequence identity thereto, wherein the proteolytically active variant cleaves a peptide of SEQ ID NO: 17 at QP|QL to provide peptides of any of SEQ ID NOs. 18-24. Also described are compositions such as pharmaceutical compositions, food supplements, and food products including the proteases. Further described are methods of treating a disorder associated with gluten intolerance by administering to a subject in need thereof an effective amount of the proteases. Also included are methods of testing a subject suspected of having gluten intolerance or gluten sensitivity by administering a composition including a protease for a period of time, then assessing symptom improvement in the subject.

The application provides a nested verification method and device based on multi-modal signals, equipment and a storage medium. The method comprises the following steps: collecting a first multi-modal physiological signal of an acupoint of a current batch of subjects before treatment and a second multi-modal physiological signal of the acupoint after treatment, and generating a treatment information set; selecting a frequency with the smallest signal change in the treatment information set as a core frequency, calculating a treatment effect of the current batch of subjects according to a signal representation value under the core frequency; obtaining a signal change amplitude of a target acupoint under the core frequency, and calculating a correlation coefficient between the signal change amplitude and a clinical symptom improvement degree; and generating an acupoint state judgment result of the current batch of subjects after treatment according to the signal change amplitude, the treatment effect and the correlation coefficient. The application can provide an effective systematic method for verifying the nested relationship among the acupoint, the meridian and the zang-fu organ.

The invention relates to the technical field of medical artificial intelligence and acupuncture treatment, and discloses an acupuncture treatment scheme optimization method based on medical artificial intelligence. According to the method, multi-dimensional physiological status indexes are analyzed and generated by collecting electronic medical records of patients and wearable equipment data, and a preliminary treatment prescription is generated by fusing acupuncture literature data. And analyzing an acupuncture point and parameter combination mode in the prescription by using a deep learning model, quantitatively evaluating contribution degrees of all elements, and optimizing and generating a final prescription in combination with historical treatment data of a patient. In clinical treatment, real-time feedback data are continuously collected, the corresponding relation between treatment parameters and symptom improvement is established, stimulation parameters are dynamically adjusted according to the corresponding relation, and closed-loop optimization is formed. According to the invention, quantitative intelligent optimization of the acupuncture treatment scheme and personalized dynamic fine adjustment in the treatment process are realized.

The invention discloses a compound infantile antipyretic double-layer suppository and a preparation method thereof, and relates to the technical field of pharmaceutical preparations, the compound infantile antipyretic double-layer suppository is composed of a quick release layer and a slow release layer, the quick release layer comprises 150-180g / 1000 paracetamol, 4-6g / 1000 artificial bezoar, 10-20g / 1000 sustained release layer, 10-20g / 1000 sustained release layer, 10-20g / 1000 sustained release layer and 10-20g / 1000 sustained release layer. The sustained release layer comprises 40-60g / 1000 pieces of rhizoma et radix baphicacanthis cusiae extract powder and 40-60g / 1000 pieces of acetaminophen, biphase drug release is achieved through the hydrophilic and hydrophobic difference of a bilayer matrix, the onset time can be shortened, the continuous fever abatement time can be prolonged, and the symptom improvement rate of a patient is greatly increased.

The invention relates to the technical field of medical AI, in particular to an intelligent management system for medication compliance of heart failure patients, which comprises an intelligent medicine box, wearable equipment and an electronic health record module, acquires basic information of the patients in real time, constructs an evaluation module, extracts medication behaviors, vital signs and historical records in a cloud database, and stores the medication behaviors, vital signs and historical records in the cloud database. Personalized medication education data is pushed through an intelligent platform, the medication compliance rate, the vital sign trend and symptom improvement data of a patient are integrated in animation, image-text and interactive game forms, the patient is incentive through milestone awards, and treatment confidence enhancement and active report problem proportion statistics are obtained. The problems that the medication data of the heart failure patient is not comprehensively collected in real time, the compliance risk is difficult to accurately assess, the medication education lacks individuation, follow-up management is not graded according to the risk, social support lacks, and treatment feedback is not visual and poor in excitation, so that the medication compliance of the patient is low are solved.

The present disclosure relates to compositions and methods for treating autism spectrum disorder (ASD) by restoring an ASD patient's gut microbiota. These methods can be used with ASD patient with or without ongoing gastrointestinal symptoms. Provided here is a method for ASD treatment in a subject in need thereof comprising or consisting essentially of administering a therapeutic composition comprising a fecal microbe or a fecal microbiota preparation to the subject. Also provided here is a method comprises administering an antibiotic to a human subject; subjecting the human subject to a bowel cleanse; and administering purified fecal microbiota to the human subject. Further provided are evaluation and quantitative characterization of patient symptom improvements upon treatment described here.

The invention discloses a microbial marker for treating Crohn's disease based on coprophilous fungus transplantation and a screening method of the microbial marker. The microbial marker comprises the following components: Dialister insight, Roseburia intestinae, Parabacteroides verdeae, Bacteroides caccae, Blauria obeum, Bacteroides intestinae, Paraprevotella, and a combination of the Bacteroides cactinae, and further comprises the following components in parts by weight: 1, 1, 2, 3, 4, 5, 6, 7, 7, 8, 8, 8, 9, 10, 12, 13, 13, 13, 14, 16, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17, 17 According to the invention, through metagenome sequencing and a machine learning algorithm, the key microbial marker which is significantly related to the symptom improvement of the Crohn's disease in the coprophilous fungus transplantation treatment process is screened out, and a scientific basis and a standardized scheme are provided for coprophilous fungus transplantation treatment of the Crohn's disease.

The present application belongs to the technical field of coffee products, and particularly relates to a coffee composition for relieving anxiety and a preparation method thereof. Coffee beans, eucommia extract, oyster polypeptide powder, xylitol and sorbitol are mixed, wherein the eucommia extract and the oyster polypeptide are homologous and bioactive peptide raw materials, which can inhibit the overactivation of the hypothalamus-pituitary-adrenal (HPA) axis, reduce the abnormal secretion of adrenocorticotropic hormone releasing hormone and cortisol, and make the high cortisol level in the chronic anxiety state return to normal. On the other hand, the active ingredients are easily absorbed by the human body, which can not only supplement nutrients and repair nerve cell membranes, but also regulate the calcium homeostasis of nerve cells, effectively relieving the symptoms such as palpitation and hand tremor accompanying anxiety. Therefore, the above raw materials can relieve anxiety from the two dimensions of "root regulation + symptom improvement" without drug dependence, and have high safety.