With the booming development of medical information technology and computer science, the medical services industry is gradually transiting from information technology to intelligence. The medical knowledge graph plays an important role in intelligent medical applications such as knowledge questions and answers and intelligent diagnosis, and is a key technology for promoting wise medical care and the basis for intelligent management of medical information. In order to fully exploit the great potential of knowledge graphs in the medical field, this paper focuses on five aspects: inter-drug relationship discovery, assisted diagnosis, personalized recommendation, decision support and intelligent prediction. The latest research progress on medical knowledge graphs is introduced, and relevant suggestions are made in light of the current challenges and problems faced by medical knowledge graphs to provide reference for promoting the wide application of medical knowledge graphs.
Pattern Recognition, Automated ; Medical Informatics

To increase efficiency of automated leucocyte pattern recognition using lower feature dimensions, a novel inter-class distinctive feature selection method for chromatic leucocyte images was proposed based on attribute hierarchical relationship. According to the attribute constraints in formal concept analysis, we established a knowledge representation and discovery method based on the hierarchical optimal diagram by defining attribute value and visual representation of optimized hierarchical relationship. It was applied to human peripheral blood leucocytes classification and 12 distinctive attributes were simplified from 60 inter-class attributes, which contributes significantly to reduced feature dimensions and efficient inter-class feature classification. Compared with the classical experimental data, the inter-class distinctive feature selection method based on hierarchical optimal diagram was proved to be usable and effective for six leucocyte pattern recognition.
Humans ; Leukocytes ; classification ; Pattern Recognition, Automated

A new fogging disinfection method was evaluated as a means of disinfecting ward rooms and operating theaters. A temporary room was established where the disinfection effect of fogging was examined. Based on the results, an automatic fogging disinfection unit was developed. This unit was then used in the disinfection of operating theaters, where its safety and effectiveness were examined. To evaluate the results of disinfection, bacterial culture tests were performed on the floor, walls and other areas of the operating theater, and the number of colony forming units was used as an index of effectiveness. Benzalkonium chloride, alkyldiaminoethylglycine, sodium hypochlorite, glutaral and acidic electrolytic water were used for the operating theaters. The average disinfection effect was 90% or better for all disinfectants, except acidic electrolytic water. The newly developed automatic fogging disinfection unit enables safe and effective disinfection, and may be suitable for disinfecting ward rooms and operating theaters.
Disinfection ; Pulmonary evaluation ; Unit ; Automated ; Water

The image segmentation method we use for leucocytes is based on image distance transformation, combining the region and edge approach, taking full advantage of image information. According to the shape, texture and color appearance of cells, we select 22 feature values and measure them. The classifier is designed on the statistical classification. A test for recognizing 831 leucocytes in 560 images shows that the classification accuracy is 96%. Clinical experts confirm this system; for it can automatically recognize leucocytes by pattern recognition technique, and it is demonstrably valid in practice.
Algorithms ; Artificial Intelligence ; Humans ; Leukocytes ; cytology ; Pattern Recognition, Automated ; methods

OBJECTIVETo construct a high performance open source software engine based on IBM SPLASH algorithm for later research on pattern discovery.

METHODSGpat, which is based on SPLASH algorithm, was developed by using open source software.

RESULTSGNU Pattern (Gpat) software was developped, which efficiently implemented the core part of SPLASH algorithm. Full source code of Gpat was also available for other researchers to modify the program under the GNU license.

CONCLUSIONGpat is a successful implementation of SPLASH algorithm and can be used as a basic framework for later research on pattern recognition in biological sequences.

To explore the methods of the explicitation of implicit knowledge and the construction of knowledge graph on moxibustion in medical case records of ZHOU Mei-sheng's Jiusheng. The medical case records data of Jiusheng was collected, the frequency statistic was analyzed based on Python3.8.6, complex network analysis was performed using Gephi9.2 software, community analysis was performed by the ancient and modern medical case cloud platform V2.3.5, and analysis and verification of correlation graph and weight graph were proceed by Neo4j3.5.25 image database. The disease systems with frequency≥10 % were surgery, ophthalmology and otorhinolaryngology, locomotor, digestive and respiratory systems. The diseases under the disease system were mainly carbuncle, arthritis, lumbar disc herniation and headache. The commonly used moxibustion methods were fumigating moxibustion, blowing moxibustion, direct moxibustion and warming acupuncture. The core prescription of points obtained by complex network analysis included Yatong point, Zhiyang(GV 9), Sanyinjiao(SP 6), Dazhui(GV 14), Zusanli(ST 36), Lingtai(GV 10), Xinshu(BL 15), Zhijian point and Hegu(LI 4), which were basically consistent with high-frequency points. A total of 6 communities were obtained by community analysis, corresponding to different diseases. Through the analysis of correlation graph, 13 pairs of strong association rule points were obtained. The correlation between Zhiyang(GV 9)-Dazhui(GV 14) and Yatong point-Lingtai(GV 10) was the strongest. The acupoints with high correlation with Yatong point were Zhiyang(GV 9), Lingtai(GV 10), Dazhui(GV 14), Zusanli(ST 36) and Sanyinjiao(SP 6). In the weight graph of the high-frequency disease system, the relationship of the first weight of the surgery system disease was fumigating moxibustion-carbuncle-Yatong point, and the relationship of the first weight of the ophthalmology and otorhinolaryngology system disease was blowing moxibustion-laryngitis-Hegu (LI 4). The results of correlation graph and weight graph are consistent with the results of data mining, which can be used as an effective way to study the knowledge base of moxibustion diagnosis and treatment in the future.
Humans ; Moxibustion ; Carbuncle ; Pattern Recognition, Automated ; Acupuncture Therapy ; Acupuncture Points

How to recognize and diagnose heart diseases, as one of the most frequent issues, is a serious problem. ECG automation recognition is not only the target of medicine, but also the work of computer science. In this paper, the approaches to ECG recognition are reviewed, and their characters are analyzed. With the background of wearable wireless ECG monitor, on the basis of experts' experience in ECG recognition, the imagery thinking-based new method, in which morphology parameters are considered, is presented.
Algorithms ; Electrocardiography ; methods ; Humans ; Pattern Recognition, Automated ; Signal Processing, Computer-Assisted

In this paper, an image mosaic algorithm based on feature points was proposed by making a study of the image mosaic methods and the characteristics of pathological image. Points of interest were firstly extracted by Moravec operator in this method, and the corresponding feature matches of the original images were achieved by correlation coefficient. The parameters of affine transformation were calculated by the matching feature points, and weighted average method was used to fuse images. The experimental results show that, as for the pathological image with translation and rotation, the algorithm can extract the matching feature points accurately and realize the image seamless mosaic.
Algorithms ; Image Enhancement ; methods ; Image Processing, Computer-Assisted ; methods ; Pathology ; methods ; Pattern Recognition, Automated ; methods

The parts of system automatically detecting the standard 12-synchronous-lead ECG (electrocardiograms) signal based on personal computer is introduced in this paper. The object-oriented programming method is adopted based on Windows System. We put forward methods to analyze QRS complex wave, P wave, T wave and ST fragment. In this paper the techniques such as ECG signal preprocessing, cardio wave parameters detecting and wave pattern cognizing are discussed too. Furthermore we use wavelet transform technique to analyze the wave pattern and get sound effect.
Algorithms ; Electrocardiography ; instrumentation ; methods ; Humans ; Pattern Recognition, Automated ; Signal Processing, Computer-Assisted ; Software

The chaos of heart rate variance (HRV) is identified by surrogate data method in this paper. Firstly, the main principle of chaotic identification is introduced, in which the median absolute error (MAE) of one-step prediction for HRV is set as the statistic. The algorithm is checked with a known chaotic system response and a colored noise signal. Then, some typical healthy and unhealthy HRVs are analyzed with the method of surrogate data, and some characteristic parameters from this method are compared.
Algorithms ; Heart Rate ; physiology ; Humans ; Nonlinear Dynamics ; Pattern Recognition, Automated ; Signal Processing, Computer-Assisted