Hospital digital library retrieval and resource sharing system and method

Abstract

The invention relates to a hospital digital library and resource sharing system and method. According to retrieval content information, a first retrieval result is obtained from a shared digital library, and a third retrieval result is obtained from a shared identity book list library of the shared digital library; acquiring a second retrieval result from a private identity book list library of the hospital library according to the retrieval content information and the retrieval identity information; fusing the first retrieval result, the second retrieval result and the third retrieval result to obtain a user retrieval result and the shared information; and sending the shared information to the shared identity book list library. According to the retrieval result of the hospital digital library, the diagnosis and treatment calendar of the patient, the knowledge structure of the medical staff of the hospital and the resources of other hospital digital libraries are considered at the same time, and the resources of the hospital digital libraries are shared on the premise that copyright, privacy and the like are not invaded.

Description

Technical Field

[0001] The invention belongs to the technical field of information retrieval, and in particular relates to a hospital digital library and resource sharing system and method. Background Art

[0002] Digital library is a kind of distributed information system. In order to meet the clinical and scientific research needs of medical staff, many hospitals have built hospital digital libraries (referred to as hospital libraries). However, on the one hand, the current search results of hospital digital libraries only consider the search speed, search accuracy and search comprehensiveness, without considering the diagnosis and treatment history of patients in the hospital and the knowledge structure of medical staff in the hospital; on the other hand, the current search results of hospital digital libraries do not consider the resources of other hospital digital libraries, and due to copyright, personal digital information protection (medical staff, patients) and other reasons, hospital digital libraries do not share resources with each other. Summary of the invention

[0003] In order to solve at least one technical problem proposed by the present invention, the present invention proposes a hospital digital library retrieval and resource sharing method, wherein the hospital library communicates with at least one shared digital library, and the method comprises:

[0004] Acquire a first search result from the shared digital library according to the search content information and acquire a third search result from a shared identity book list library of the shared digital library; the shared identity book list library is constructed based on shared information of an associated hospital library associated with the shared digital library, the shared information including user search results;

[0005] Obtaining a second search result from a private identity book list library of the hospital library according to the search content information and the search identity information, wherein the private identity book list library is constructed based on medical staff-related book data and case data; the medical staff-related book data includes academic book data and academic book data;

[0006] The user search result is obtained by integrating the first search result, the second search result and the third search result and shared to the shared digital library.

[0007] In order to solve at least one technical problem raised by the present invention, the present invention also proposes a hospital digital library retrieval and resource sharing system, which includes at least one processor; and a memory storing instructions, which, when executed by at least one processor, implements the steps of the aforementioned method.

[0008] In order to solve at least one technical problem proposed by the present invention, the present invention further proposes a computer-readable storage medium having a computer program / instruction stored thereon, which implements the steps of the aforementioned method when the computer program / instruction is executed by a processor.

[0009] In order to solve at least one technical problem proposed by the present invention, the present invention further proposes a computer program product, including a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0010] The beneficial effects of the present invention are: on the one hand, the search results of the hospital digital library of the present invention take into account the medical records of the patients in the hospital and the knowledge structure of the medical staff of the hospital, so that the hospital, the medical staff and the patients can all benefit when improving the search performance and coverage of the hospital digital library; on the other hand, the search results of the hospital digital library of the present invention also take into account the resources of other hospital digital libraries, and the resources between hospital digital libraries are shared without infringing on copyright, privacy, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 Topological map of hospital library and shared digital library;

[0012] Figure 2 A flowchart of the hospital digital library retrieval and resource sharing method;

[0013] Figure 3 The topological diagram is when the shared digital library is the superior digital library and the associated hospital library is the hospital library of the same level;

[0014] Figure 4 The topological diagram is when the shared digital library is the superior digital library and the associated hospital library is the superior digital library;

[0015] Figure 5 The topological diagram when the shared digital library is a superior digital library and several hospital libraries at the same level;

[0016] Figure 6 is a schematic diagram of an ordered set of first search results;

[0017] Figure 7 is a schematic diagram of an ordered set of second search results;

[0018] Figure 8 is a schematic diagram of an ordered set of third search results;

[0019] Fig. 9 A schematic diagram of an ordered set of search results for the first user;

[0020] Fig.10A schematic diagram of an ordered set of search results for a second user;

[0021] Fig.11 Sorting matching results indicates intent;

[0022] Fig.12 This is a schematic diagram of the correction set;

[0023] Fig.13 A schematic diagram of the ordered set of search results for the second user (after correction);

[0024] Fig.14 Sorting matching results indicates intent;

[0025] Fig.15 This is a schematic diagram of the search results of related books with negative cases deleted. DETAILED DESCRIPTION

[0026] Digital library is a kind of distributed information system. In order to meet the clinical and scientific research needs of medical staff, many hospitals have built hospital digital libraries. However, on the one hand, the current search results of hospital digital libraries only consider the search speed, search accuracy and search comprehensiveness, without considering the diagnosis and treatment history of patients in the hospital and the knowledge structure of medical staff in the hospital; on the other hand, the current search results of hospital digital libraries do not consider the resources of other hospital digital libraries, and due to copyright, privacy and other reasons, hospital digital libraries do not share resources with each other.

[0027] Hospital libraries that do not consider resource sharing

[0028] These embodiments provide a hospital library search method, wherein the hospital library communicates with at least one superior digital library, and the method includes: obtaining a first search result from the superior digital library according to search content information; obtaining a second search result from an identity book list library of the hospital library according to the search content information and search identity information, wherein the identity book list library is constructed based on medical staff-related book data and case data; the medical staff-related book data includes academic book data and academic book data; and the user search result is obtained by merging the first search result and the second search result. Based on the above embodiments, a digital library platform is provided that is based on the current hospital resource situation and takes clinical needs into consideration. Since the search results take into account the diagnosis and treatment cases of patients in this hospital and the knowledge structure of the medical staff of this hospital, the hospital can benefit the hospital, medical staff and patients when improving the search performance and collection scope of the hospital digital library. The hospital does not have to blindly pursue search efficiency, search accuracy and search comprehensiveness, and does not need to waste medical funds (if a database that does not match the knowledge structure of the medical staff of this hospital is purchased, it is equivalent to the investment of the hospital in the library not being reflected in the patient service). The search results obtained by medical staff are more targeted and available (reduce information redundancy, such as the search results obtained by nurses, will not include some foreign books, books with high professional depth; the search results obtained by doctors will not include books that record poor treatment plans.), and patients can obtain more advanced treatment services. It can be seen that the hospital library of these embodiments cannot share data with the superior digital library, and between hospital libraries. The superior digital libraries of different hospital libraries may be different, so there are copyright issues when sharing resources, and the case data of different hospitals must be saved separately, so there are privacy issues when sharing resources.

[0029] Therefore, it is necessary to provide a hospital digital library retrieval and resource sharing method that can take into account the hospital's patient treatment history and the knowledge structure of the hospital's medical staff, while also enabling the hospital's digital libraries to share copyright and privacy compliant resources with each other.

[0030] Hospital libraries considering resource sharing

[0031] In some embodiments, a hospital digital library retrieval and resource sharing method is provided, such as Figure 1 , Figure 2 As shown, the hospital library 1 communicates with at least one shared digital library, and the method includes:

[0032] S1: obtaining a first search result from the shared digital library according to the search content information and obtaining a third search result from a shared identity book list library of the shared digital library; the shared identity book list library is constructed based on shared information of an associated hospital library associated with the shared digital library, and the shared information includes user search results;

[0033] S2: obtaining a second search result from a private identity book list library of the hospital library according to the search content information and the search identity information, wherein the private identity book list library is constructed based on medical staff-related book data and case data; the medical staff-related book data includes academic book data and academic book data;

[0034] S3: The first search result, the second search result and the third search result are integrated to obtain the user search result and shared to the shared digital library.

[0035] "Retrieval content information" refers to the information input by the user into the retrieval system. The modalities of retrieval content information include written (such as keywords) or spoken natural language signals (such as voice), pictures and video signals, etc. It can be a single-modal retrieval or a cross-modal retrieval. The latter is generally used in multimedia digital libraries.

[0036] "Search results" refers to the search results that meet the search requirements obtained by the user after the search tool or search system executes the search process, including titles, abstracts, image thumbnails, etc.

[0037] "Retrieval identity information" includes medical and nursing role information, medical and nursing education information, work experience information (such as clinical research papers published or guided during work, academic conferences attended), and other registration information that can distinguish the user's knowledge structure; the medical and nursing role information includes doctor identity information and nurse identity information. The hospital library retrieval system can collect retrieval identity information through the user registration form.

[0038] “Academic book data” refers to a book data set or book catalog data set that represents the knowledge structure of medical staff during their study period, obtained through computer search or manually sorted based on the academic information of medical staff, including but not limited to textbook data, degree theses and their citation data, etc. For example, the textbook data of Doctor B who graduated from University A with a master's degree in clinical medicine, the textbooks used by this class include Physiology (X Publishing House Y Edition), Internal Medicine (X Publishing House Y Edition), Surgery (X Publishing House Y Edition), Preventive Medicine (X Publishing House Y Edition), Neurology (X Publishing House Y Edition), Biochemistry and Molecular Biology (X Publishing House Y Edition), Pharmacology (X Publishing House Y Edition), Pathology (X Publishing House Y Edition), Pathophysiology (X Publishing House Y Edition), Diagnostics (X Publishing House Y Edition), Medical Microbiology (X Publishing House Y Edition), Traditional Chinese Medicine (X Publishing House Y Edition), Obstetrics and Gynecology (X Publishing House Y Edition), Histology and Embryology (X Publishing House Y Edition), Pediatrics (X Publishing House Y Edition), Advanced Mathematics for Medical Use (X Publishing House Y Edition), and Doctor-Patient Communication 》(Y edition of X Publishing House), Organic Chemistry (Y edition of X Publishing House), Medical Biology (Y edition of X Publishing House), Basic Chemistry (Y edition of X Publishing House), Medical Genetics (Y edition of X Publishing House), Medical Psychology (Y edition of X Publishing House), Anesthesiology (Y edition of X Publishing House), Internal Medicine (Y edition of X Publishing House), Surgery (Y edition of X Publishing House), Preventive Medicine (Y edition of X Publishing House), Neurology (Y edition of X Publishing House), Forensic Medicine (Y edition of X Publishing House), Medical Statistics (Y edition of X Publishing House), Ophthalmology (Y edition of X Publishing House), Clinical Epidemiology and Evidence-Based Medicine (Y edition of X Publishing House), Human Parasitology (Y edition of X Publishing House), Dermatology (Y edition of X Publishing House), Systematic Anatomy (Y edition of X Publishing House), Pathophysiology (Y edition of X Publishing House).

[0039] "Academic book data" refers to a book data set that represents the knowledge structure of medical staff during their working period, obtained through computer search or manually sorted based on the academic information of medical staff. The academic book data includes post-work paper data and its citation data, academic conference data, etc.

[0040] The "academic book data" and "academic book data" of the present invention are obtained using well-known computer technologies, such as data crawling (such as DFS, BFS crawlers, etc.), data screening, text description supplementation, data annotation, etc., to establish a data set that can be used in a digital library.

[0041] "Medical staff-related book data" refers to a data set that reflects the relationship between "retrieval identity information" and "book data" after data preprocessing by merging "academic book data" and "academic book data", which represents the sum of the knowledge structure of medical staff. The data preprocessing method includes one or more steps of data cleaning, data standardization, data normalization, category coding, feature selection, etc.

[0042] "Case data" includes but is not limited to digital biochemical test reports, discharge records, imaging test reports, case records, emergency medical records, admission records, case surveys, case study reports, etc. The "case data" of the present invention can be directly obtained from a digital hospital system or obtained using machine learning technology. The digital hospital system includes but is not limited to a hospital information system (HIS), a telemedicine system (Tele medicine), an online business processing system (OLTP), a clinical information system (CIS), an online analytical processing system (OLAP) Internet system (Intranet / Internet), etc. Healthcare information technology refers to information and communication technology specifically used to handle or process medical or health data, such as ICT technology for medical simulation or medical data mining based on patient-specific data (such as electronic medical records). There is no report in the prior art on the combination of hospital digital libraries and healthcare information technology. In order to solve the technical problems of the present invention, multiple embodiments of the present application combine digital libraries with healthcare information technology.

[0043] "Fusion" refers to data fusion, which means using a computer to automatically analyze and synthesize the first search results, second search results and third search results obtained under certain criteria to decide on user search results that better match the user's knowledge structure.

[0044] Based on the above embodiments, on the one hand, the effect of hospital libraries that do not consider resource sharing is taken into account, which will not be repeated here. On the other hand, the shared identity book list library is constructed based on the shared information of the associated hospital library associated with the shared digital library, and the shared information includes the user search results of other users (not this hospital), and although the non-hospital user search results are generated based on the copyright data and privacy data of the non-hospital, the search results themselves do not touch on copyright privacy compliance issues. Therefore, these embodiments can take into account the diagnosis and treatment history of patients in this hospital and the knowledge structure of medical staff in this hospital, while also enabling the hospital digital library to share copyright privacy compliant resources with each other.

[0045] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also provided, combining Figure 3 , Figure 4As shown, the shared digital library is the superior digital library 2, and the associated hospital library is the hospital library 3 of the same level as the hospital library or the superior digital library 4 of the hospital library of the same level.

[0046] like Figure 3 , the hospital library 3 of the same level as the hospital library 1 is directly associated with the shared digital library 2 (the superior digital library 2). Figure 4 The hospital library 3 of the same level as the hospital library 1 is associated with the shared digital library 2 (superior digital library 2) through the superior digital library 4 of the hospital library 3 of the same level.

[0047] "Superior digital library" refers to a digital library whose retrieval system can perform combined retrieval on a large number of databases and display unified retrieval results. Taking university digital libraries as an example, they usually purchase a large number of shared databases (such as MedSci, Pubmed, CNKI, China Biomedical Literature Database (CBM), China Science Citation Database (CSCD), Wanfang Data, Duxiu Academic Search, Weipu Information, SuperStar Digital Library, TANet, PubChem, JSTOR, IEEE Xplore, EBSCOhost, ScienceDirect, SpringerLink, Web of Science, NSSD, etc.) or build several school databases (such as library collections). In order to improve retrieval efficiency, its retrieval system can perform combined retrieval on a large number of databases and display unified retrieval results; in the present invention, the retrieval system of the superior digital library is a known technology, such as the retrieval system of Chinese patent CN118170816A that obtains a target database combination by weight screening based on user retrieval history data. Compared with the university digital library, the affiliated hospital digital library is a subordinate digital library. The affiliated hospital digital library can obtain search results by accessing the university digital library interface instead of accessing the shared database interface, thus avoiding duplicate construction of digital libraries.

[0048] In these embodiments, Figure 3In the topological structure shown, although the hospital library 1 and the hospital library 3 of the same level have different superior digital libraries, they are both equipped with independent private identity book list libraries 5. For example, Doctor X is a user of the hospital library 1, and Doctor Y is a user of a hospital library 2 of the same level. If Doctor Y consults remotely with the hospital where Doctor X is located, the user search results of Doctor Y in a hospital library 2 of the same level can be shared with the superior digital library 2 of the hospital library 1 of Doctor X. After that, when Doctor X makes a query in the hospital library 1, his user search results can take into account the knowledge structure of Doctor Y. At present, the medical resources between hospitals, especially between hospitals in developed and underdeveloped areas, are unevenly allocated. Therefore, it is common for doctors in developed areas to participate in the consultation and training of doctors in underdeveloped areas through remote participation. In order to adapt to the changes in knowledge structure caused by the influence of doctors in other hospitals on doctors in this hospital, the search results of the hospital libraries in these embodiments can take into account the knowledge increments and knowledge focus points of doctors other than doctors in this hospital, and these knowledge increments and knowledge focus points can be mastered by doctors in this hospital through learning.

[0049] The advantage of considering the user search results of other hospital users in the hospital library's user search results is that it increases the impact of case data on user search results. Some small hospitals or new hospitals have less accumulated case data for certain diseases. Through this sharing method, the hospital can invite doctors with rich experience in treating these diseases to participate in consultation and training. Therefore, the doctor's user search results take into account the impact of a large amount of case data on the disease, which indirectly increases the impact of case data on the user search results of the hospital.

[0050] The information acquisition capabilities of county hospitals and provincial and ministerial hospitals are different. Only effective information acquisition can truly transform learning into benefits for patients. For example, county hospitals cannot understand some English documents. Even for provincial and ministerial hospitals, the amount of knowledge is different due to differences in doctors' academic qualifications, academics, and experience. These embodiments of the present invention take into account the effects of hospital libraries that do not consider resource sharing, and enable the hospital digital library to share copyright privacy compliant resources with each other, and can also save the cost of building digital libraries for small hospitals. For example, large hospitals share more user search results with small hospitals.

[0051] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also provided, combining Figure 5 As shown, the shared digital library is a superior digital library 2 and several hospital libraries 3 of the same level, and several hospital libraries 3 of the same level form the associated hospital library. The first search result is obtained from the superior digital library 2, and the third search result is obtained from the hospital libraries 3 of the same level.

[0052] In these embodiments, each hospital library at the same level includes shared libraries, which together constitute a shared identity book list library. The decentralized setting of the shared identity book list library enables resource sharing between hospital digital libraries in a wider network.

[0053] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also involved. The method for constructing the private identity book list library according to the medical staff associated book data and the case data comprises the following steps:

[0054] 1. Construct a medical staff-related book data set based on the medical staff-related book data;

[0055] 2. Construct a case-related book dataset based on the case data;

[0056] 3. The medical staff-associated book dataset and the case-associated book dataset are merged to obtain the private identity book list library.

[0057] These embodiments are described below in conjunction with Table 1.

[0058] Table 1 Data and data set element attributes

[0059]

[0060]

[0061] Furthermore, “constructing a medical staff-related book data set based on medical staff-related book data” includes the following steps:

[0062] 1.1 Obtain the hospital's educational and academic data;

[0063] The educational background data includes the educational background information (school, major, year of admission, etc.) of all current and historical medical staff of the hospital, and multiple educational backgrounds of each medical staff are entered into multiple pieces of educational background information; for example, XXX, a neurosurgeon, studied clinical medicine (undergraduate) at University A in 1996 and studied neurosurgery (master) at University B in 2002, which is recorded as two pieces of educational background information: {XXX-1, University A, clinical medicine, 1996}, {XXX-2, University B, neurosurgery, 2002}.

[0064] The academic data includes the academic information of all current and historical medical staff of the hospital (published papers, published books, conference papers, etc.), and the same academic resume of different medical staff may be recorded as multiple pieces of academic information; for example, Doctor XXX and Doctor YYY jointly published Paper S in 2010, which is recorded as two pieces of academic information: {XXX, Paper S}, {YYY, Paper S}.

[0065] 1.2 Based on the deduplicated academic information of medical personnel, obtain academic book data representing the knowledge structure of medical personnel during their study period by computer search or manually organize; based on the deduplicated academic information of medical personnel, obtain academic book data representing the knowledge structure of medical personnel's academic research by computer search or manually organize;

[0066] For example, continuing with the previous example, XXX neurosurgeon studied clinical medicine (undergraduate) at A University in 1996, and YYY cardiac surgeon has the same first degree as XXX neurosurgeon, then the search system only needs to search for books related to "1996 A University Clinical Medicine (undergraduate)" (deduplicated academic information).

[0067] For example, continuing with the previous example, since Doctor XXX and Doctor YYY jointly published Paper S in 2010, the search system only needs to use the relevant citation books of "Paper S" (without duplicate academic information).

[0068] 1.3 After cleaning the academic book data, the data is standardized and the educational background impact factor is given to obtain the academic-related book data set. After cleaning the academic book data, the data is standardized and the academic resume impact factor is given to obtain the academic-related book data set.

[0069] The educational background impact factor α is determined according to the number of times the book is repeated; for example, continuing the previous example, the relevant books of "Clinical Medicine Major (Undergraduate) of A University in 1996" include M books. Since XXX neurosurgeon and YYY cardiac surgeon have both studied M books, the impact value of the educational background impact factor α of M books is increased. For another example, continuing the previous example, the physical diagnosis doctor studied medical imaging major (undergraduate) of C University in 1989, and its relevant books also include M books, then the impact value of the educational background impact factor α of M books is increased.

[0070] The academic resume impact factor β is also determined according to the number of times the book is repeated; for example, continuing the previous example, for example, the search system needs to search for the relevant citation book "Paper T" with "Paper S" (without duplicate academic information). Since XXX neurosurgeon and YYY cardiac surgeon have both paid attention to Paper T, the impact value of the academic resume impact factor β of Paper T is increased. For another example, continuing the previous example, if "Paper O" published by a physical diagnosis doctor cites "Paper T", the impact value of the academic resume impact factor β of "Paper T" is increased.

[0071] 1.4 After deduplication, the academic qualification-related book dataset and the academic qualification-related book dataset are merged to obtain a medical staff-related book dataset. In a specific embodiment, as shown in Table 1, the merged academic qualification-related book dataset can simultaneously represent the relationship between the academic qualification, academic qualification and books of the medical staff of the hospital.

[0072] Furthermore, “constructing a case-related book dataset based on case data” includes the following steps:

[0073] 2.1 Obtain case data from a digital hospital system, and extract high-level semantic information from the case data to obtain empirical data;

[0074] The experience data includes all the experience information (medical care plans, medical care results, etc.) of the hospital in which all the medical staff of the hospital currently and historically participated in the diagnosis and treatment, and multiple cases of each patient include multiple pieces of experience information. The digital hospital system includes but is not limited to hospital information system (HIS), telemedicine system (Tele medicine), online business processing system (OLTP), clinical information system (CIS), online analytical processing system (OLAP) Internet system (Intranet / Internet), etc. When extracting high-level semantic information, well-known feature extraction techniques are used, including but not limited to clustering algorithms (such as K-MEANS), natural language processing (NPL), machine learning (Machine Learning, ML), etc.

[0075] For example, patient a with cervical spondylosis visited the orthopedics department of the hospital in 2001 and was treated by doctor b. His case data includes case records, imaging test reports, biochemical test reports, case study reports, etc. The extracted high-level semantic information of patient a is {b, doctor, treatment plan (vertebral artery type cervical spondylosis; dizziness and headache, partial blood stasis should be treated with blood stasis removal, meridian dredging, dampness removal and liver calming; Xuefu Zhuyu Decoction treatment; treatment results (basically normal; evaluation of spinal cord function status of patients with cervical spondylosis (40-point method); I. Upper limb function is basically normal; II. Lower limb function is basically normal; III. Sphincter function is basically normal; VI. Limb sensation is basically normal; V. Band sensation is basically normal}.

[0076] 2.2 Experience book data representing the knowledge structure of the medical staff's clinical experience obtained by computer search based on the deduplicated experience information of the medical staff or by matching with the medical staff-related book data set;

[0077] For example, continuing the previous example, the search system uses "vertebral artery type cervical spondylosis; dizziness and headache, partial blood stasis should be treated with blood stasis, meridians, dampness and liver; Xuefu Zhuyu Decoction", "treatment results (basically normal; evaluation of spinal cord function status of patients with cervical spondylosis (40-point method); I. Upper limb function is basically normal; II. Lower limb function is basically normal; III. Sphincter function is basically normal; VI. Limb sensation is basically normal; V. Band sensation is basically normal" as search text to crawl related book information;

[0078] For another example, continuing with the previous example, the matching system "Vertebral artery type cervical spondylosis; dizziness accompanied by headache, partial blood stasis should be treated with blood stasis, unblocking meridians, removing dampness and calming the liver; Xuefu Zhuyu Decoction for treatment", "Treatment results (basically normal; Assessment of spinal cord function status of patients with cervical spondylosis (40-point method); I. Upper limb function is basically normal; II. Lower limb function is basically normal; III. Sphincter function is basically normal; VI. Limb sensation is basically normal; V. Girdle sensation is basically normal" are used as reference texts for semantic matching with the book abstract text information of the medical staff associated book dataset.

[0079] 2.3 After data cleaning, the experience book data is standardized and given a work experience impact factor to obtain the case-related book data set;

[0080] The work experience influence factor γ is determined according to the number of times the book is repeated; for example, continuing the previous example, the books related to doctor b’s “basically normal” patient a’s high-level semantic information include N books, and the books related to doctor b’s “basically normal” patient c’s high-level semantic information also include N books. Since both patient a and patient c benefit from doctor b’s study of N books, the influence value of the work experience influence factor γ of the N books is increased. For another example, continuing the previous example, the books related to doctor b’s “basically normal” patient a’s high-level semantic information include N books, and the books related to doctor d’s “basically normal” patient medical staff associated book data set also include N books. Since both patient a and patient c benefit from the hospital’s doctors (doctor b, doctor d)’s study of N books, the influence value of the work experience influence factor γ of the N books is increased. In addition, the “abnormal” doctor’s experience information on the diagnosis and treatment of patients will be included in the case-irrelevant book data set.

[0081] Furthermore, “merging the medical staff-related book dataset and the case-related book dataset to obtain the private identity book list library” includes the following steps:

[0082] 3.1 Obtain the medical staff-related book dataset and case-related book dataset;

[0083] 3.2 The medical staff-associated book dataset and the case-associated book dataset are merged to obtain the private identity book list library.

[0084] In a specific embodiment, the greater the influence value of the education background influence factor α, the academic resume influence factor β, and the work experience influence factor γ on a certain book, the higher the ranking of the book in the identity book list library. However, the present invention does not limit the way in which the education background influence factor α, the academic resume influence factor β, and the work experience influence factor γ affect the ranking. Any technology that adjusts the way in which the ranking is affected, such as by introducing weights and machine learning, is within the scope of the present invention.

[0085] In the above embodiment, the patients of a hospital are fixed, and the information that a hospital can obtain from the digital library is fixed. Some of this information is wrong, and some is useful. The construction of the identity book list library fully reflects the relationship between the identity (education, academic, experience) of the medical staff of a hospital and the books. The identity book list library of the present invention is the knowledge graph of the medical staff and the case knowledge graph of the hospital. In order to optimize the matching results, any known knowledge graph construction technology is within the selection scope of the present invention.

[0086] In some other embodiments of the present invention, a hospital digital library retrieval and resource sharing method is also involved, and the shared information also includes academic-related book data sets or their subsets, academic-related book data sets or their subsets, and case-related book data sets or their subsets.

[0087] In these embodiments, referring to Table 1, it can be seen that the academic degree-related book data set, the academic-related book data set, and the case-related book data set have all removed the names of medical staff and patient information, and their elements are all summary information of data and do not include the full text. Therefore, hospital digital libraries can share these data sets to improve resource sharing efficiency. For example, the shared information between the hospital digital libraries of multiple affiliated hospitals of a certain university may include academic degree-related book data sets, academic-related book data sets, and case-related book data sets. Furthermore, as needed, only partial subsets of the academic degree-related book data sets, academic-related book data sets, and case-related book data sets can be shared to make resource sharing more flexible.

[0088] In some other embodiments of the present invention, which also relates to a hospital digital library search and resource sharing method, the first search result, the second search result, and the third search result are all ordered sets;

[0089] The method of fusing the first search result, the second search result and the third search result is:

[0090] Calculate the intersection of the first search result and the ordered set of the second search result;

[0091] Calculate the intersection of the ordered sets of the first search result and the third search result;

[0092] The union of the intersection of the ordered sets of the first search result and the second search result and the intersection of the ordered sets of the first search result and the third search result is calculated.

[0093] An “ordered set of search results” refers to a data structure such as a table or array that is a combination of ordered search results (data / elements).

[0094] "Intersection" means that the elements of the intersection (search results) belong to both the first search result ordered set and the second search result ordered set, or belong to both the first search result ordered set and the third search result ordered set, and the elements of the aforementioned intersection are also ordered.

[0095] Combine the following Figures 6 to 9 The above embodiment is further described. Figure 6 As shown, the first search result ordered set 10 is recorded as {A, B, C, D, E, F, G, H, I}, including 9 ordered search results 11, each of which includes a title 12 and an abstract 13. Figure 7 As shown, the second search result ordered set 20 is recorded as {A, B, o, p, E, F, q, r, i}, including 9 search results 21 arranged in order, each of which includes a title 22 and an abstract 23. Figure 8 As shown, the third search result ordered set 30 is recorded as {H, B, u, p, E, w, Z, X, y}, including 9 search results 31 arranged in order, each search result 31 including a title 32 and an abstract 33. Fig. 9 As shown, the ordered set 40 of the first user's search results is the union of the intersection of the aforementioned two sets ({A, B, E, F}, {H, B, E}), recorded as {A, H, B, E, F}, including 5 ordered search results 41, each search result 41 includes a title 42 and an abstract 43.

[0096] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also provided, and the method further comprises the following steps:

[0097] S4: Calculate the relative complement of the second search result ordered set in the first search result ordered set to generate a second user search result ordered set. The first user search result ordered set is outputted before the second user search result ordered set. The second user search result ordered set is outputted after removing duplicate values ​​with the first user search result ordered set.

[0098] “The relative complement of the second search result ordered set in the first search result ordered set” means that the elements of the relative complement belong to the first search result ordered set but not to the second search result ordered set.

[0099] "The first user's ordered set of search results is outputted before the second user's ordered set of search results" means that in the matching result sorting table presented to the user, the search results (data / elements) in the first user's ordered set of search results are ranked first, while the search results (data / elements) in the second user's ordered set of search results are ranked later.

[0100] "Matching result ranking table" refers to a visual form presented to the user through a human-computer interaction interface (GUI), including a single-modal matching result ranking table and a mixed-modal matching result ranking table. Among them, for traditional digital libraries, it is usually a single-modal matching result ranking table, such as a ranking table of excerpt information of digitized journals, dissertations or books. For multimedia digital libraries, it is usually a mixed-modal matching result ranking table, such as a mixed ranking of journals, papers or books with videos. The way in which the aforementioned matching result ranking table presents data belongs to known technology.

[0101] Combine the following Figures 6 to 11 These embodiments are further described. Figure 6 As shown, the first search result ordered set 10 is recorded as {A, B, C, D, E, F, G, H, I}, including 9 ordered search results 11, each of which includes a title 12 and an abstract 13. Figure 7 As shown, the second search result ordered set 20 is recorded as {A, B, o, p, E, F, q, r, i}, including 9 search results 21 arranged in order, each of which includes a title 22 and an abstract 23. Figure 8 As shown, the third search result ordered set 30 is recorded as {H, B, u, p, E, w, Z, X, y}, including 9 search results 31 arranged in order, each search result 31 including a title 32 and an abstract 33. Fig. 9 As shown, the ordered set 40 of the first user's search results is the union of the intersection of the aforementioned two sets ({A, B, E, F}, {H, B, E}), recorded as {A, H, B, E, F}, including 5 ordered search results 41, each search result 41 includes a title 42 and an abstract 43.

[0102] like Fig.10As shown, the second user search result ordered set 50 is the relative complement of the second search result ordered set in the first search result ordered set, recorded as {C, D, G, H, I}, and includes 5 search results 51 arranged in order, each search result 51 includes a title 52 and an abstract 53. Fig.11 As shown, in the matching result sorting table 60, the retrieval results (data / elements) in the first user retrieval result ordered set {A, H, B, E, F} are ranked higher, while the retrieval results (data / elements) in the second user retrieval result ordered set {C, D, G, I} after removing the duplicate value {H} are ranked lower.

[0103] Based on the above embodiment, the technical effect of making the search results obtained by medical staff more targeted and available is retained based on the first user search result ordered set, and the user's in-depth browsing needs for the superior digital library are guaranteed based on the second user search result ordered set.

[0104] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also provided, and the method further comprises the following steps:

[0105] S5: Calculate the relative complement of the first search result ordered set in the second search result ordered set to generate a revised set;

[0106] S6: Based on the element relationship between the revised set and the second user search result ordered set, adjust the order of the search results in the second user search result ordered set.

[0107] “Calculating the relative complement of the first search result ordered set in the second search result ordered set” means that the elements of the relative complement belong to the second search result ordered set but do not belong to the first search result ordered set.

[0108] "The correlation between the revised set and the ordered set of the second user's search results" refers to the correlation between the elements (search results) in the two sets, specifically the correlation between the titles and abstracts. The algorithm for determining the correlation between the titles and abstracts of the two search results is a known technology. For example, the ordered set of the second user's search results includes "Epidemiology (9th edition) published by People's Medical Publishing House", and the revised set includes "Epidemiology (8th edition) published by People's Medical Publishing House". The two are only different in version and have a high similarity. For another example, the ordered set of the second user's search results includes "Cell Biology (4th edition) published by Higher Education Press", and the search results in the revised set include nursing books such as "Introduction to Nursing (5th edition)" and "Surgical Nursing (7th edition)", and the two have a low similarity.

[0109] Combine the following Figures 6 to 10 , Figures 12-14 These embodiments are further described. Figure 6 As shown, the first search result ordered set 10 is recorded as {A, B, C, D, E, F, G, H, I}, including 9 ordered search results 11, each of which includes a title 12 and an abstract 13. Figure 7 As shown, the second search result ordered set 20 is recorded as {A, B, o, p, E, F, q, r, i}, including 9 search results 21 arranged in order, each search result 21 including a title 22 and an abstract 23. Figure 8 As shown, the third search result ordered set 30 is recorded as {H, B, u, p, E, w, Z, X, y}, including 9 search results 31 arranged in order, each search result 31 including a title 32 and an abstract 33. Fig. 9 As shown, the first user search result ordered set 40 is the union of the intersection of the above two sets ({A, B, E, F}, {H, B, E}), recorded as {A, H, B, E, F}, including 5 ordered search results 41, each search result 41 includes a title 42 and an abstract 43. Fig.10 As shown, the second user search result ordered set 50 is the relative complement of the second search result ordered set in the first search result ordered set, recorded as {C, D, G, H, I}, and includes 5 search results 51 arranged in order, each search result 51 includes a title 52 and an abstract 53. Fig.12 As shown, the modified set 70 is the relative complement of the first search result ordered set in the second search result ordered set, recorded as {o, p, q, r, i}, including 5 ordered search results 71, each search result 71 including a title 72 and an abstract 73. In this embodiment, the total relevance score of each search result of the second user search result ordered set {C, D, G, H, I} and each search result of the modified set {o, p, q, r, i} is calculated. First, the search result C is respectively calculated with the search result o, the search result p, the search result q, the search result r, and the search result i for the total similarity score, recorded as {Co, Cp, Cq, Cr, Ci}->{34 points, 65 points, 28 points, 96 points, 18 points}->C total score: 241 points. Then the total similarity scores of D, G, H, and I are obtained in turn, which are: D total score: 414 points; G total score: 119 points; H total score: 208 points; I total score: 239 points. like Fig.13 As shown, the second user search result ordered set (corrected) 50' is formed by adjusting the order of the search results of the second user search result ordered set {C, D, G, H, I}, recorded as {D, C, I, H, G}, and each search result 51' includes a title 52' and an abstract 53'. Fig.14As shown, in the matching result sorting table 80, the retrieval results (data / elements) in the ordered set of retrieval results of the first user {A, H, B, E, F} are ranked higher, and the retrieval results (data / elements) in the ordered set of retrieval results of the second user (after correction) after removing the duplicate value {H} {D, C, I, G} are ranked lower.

[0110] Based on the above embodiment, the technical effect of making the search results obtained by medical staff more targeted and available is retained based on the first user search result ordered set, and the user's in-depth search needs for the superior digital library are guaranteed based on the second user search result ordered set.

[0111] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also provided, wherein:

[0112] Splitting the first search result ordered set into a plurality of first search result ordered subsets;

[0113] Splitting the second search result ordered set into a plurality of second search result ordered subsets;

[0114] The intersection of the first search result ordered subset and the second search result ordered subset corresponding to the search result is calculated to generate a first user search result ordered subset.

[0115] "The first ordered set of search results splitting" is based on the Set Partitioning technology. According to the number n (of search results (elements) presented in the sorted table of matching results on each page of the user's search device, and the number m (of search results (elements) of the first ordered set of search results for this search, the first ordered set of search results is split into m / n rounded up (pieces). For example, a user's search device is a desktop computer, and its sorted table of matching results on each page can present 15 search results (elements). The first ordered set of search results for a certain search includes 144 search results (elements). Then the first ordered set of search results is split into 10 first ordered subsets of search results. For another example, a user's search device is a mobile phone, and its sorted table of matching results on each page can present 9 search results (elements). The first ordered set of search results for a certain search includes 144 search results (elements). Then the first ordered set of search results is split into 16 first ordered subsets of search results.

[0116] "Splitting of the second ordered set of search results" is also based on the Set Partitioning technology. According to the number n of search results (elements) presented in the matching result sorting table on each page of the user's search device, and the number m of search results (elements) of the second ordered set of search results in this search, the second ordered set of search results is split into m / n (rounded up).

[0117] "Calculate the corresponding intersection of the first ordered subset of search results and the second ordered subset of search results" means taking the intersection of a first ordered subset of search results and a second ordered subset of search results (1 to 1), or taking the intersection of a first ordered subset of search results and multiple second ordered subsets of search results (1 to many).

[0118] In the above embodiment, when the data volume of the first search result ordered set and the second search result ordered set is large, the sets are divided into subsets and then the intersection operation is performed, which greatly reduces the processing time. Among them, when an ordered subset of the first search result is corresponding to multiple ordered subsets of the second search result, the ordered subset of the second search result is given priority to present the elements that meet the conditions in advance as much as possible. For example, there are 7 ordered subsets of the first search result and 16 ordered subsets of the second search result. According to the 1-to-2 relationship, 14 elements of the ordered subset of the second search result can be used to take the intersection, while according to the 1-to-1 relationship, only 7 elements of the ordered subset of the second search result can be used to take the intersection. The former gives priority to the ordered subset of the second search result.

[0119] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also provided, wherein the method further comprises the following steps:

[0120] The relative complement of the second ordered subset of search results in the corresponding ordered subset of the first search results is calculated to generate a second user ordered subset of search results, and the first user ordered subset of search results is outputted in priority to the second user ordered subset of search results.

[0121] In the above embodiment, the difference from the previous embodiment of "the relative complement of the second search result ordered set in the first search result ordered set" is that the elements of the relative complement of the previous embodiment consider all elements that belong to the first search result ordered set but do not belong to the second search result ordered set. The elements of the relative complement of this embodiment only consider the elements that belong to the first search result ordered set but do not belong to the second search result ordered set in each page of the matching result sorting table, which can reduce the amount of calculation when the amount of data is large.

[0122] In some other embodiments of the present invention, a hospital digital library search and resource sharing method is also provided, wherein the method further comprises the following steps:

[0123] Calculating the relative complement of the first ordered subset of the search results in the second ordered subset of the search results to generate a modified subset;

[0124] Based on the correlation between the modified subset and a plurality of the second user search result ordered subsets including the corresponding second user search result ordered subsets, the order of the search results in the second user search result ordered subsets is adjusted.

[0125] In the above embodiment, the difference from the previous embodiment "based on the element relationship between the modified set and the second user search result ordered set" is that the elements of the relative complement set in the previous embodiment consider all elements that belong to the second search result ordered set but do not belong to the first search result ordered set. The elements of the relative complement set in this embodiment only consider the elements of the matching result sorting table on each page, which can reduce the amount of calculation when the amount of data is large.

[0126] In some other embodiments of the present invention, a hospital digital library retrieval and resource sharing method is also involved, which constructs a case-independent book data set based on the case data, and deletes the search results that are identical to the case-independent book data set in the ordered set of search results of the second user.

[0127] "Constructing a case-independent book data set based on case data" means constructing a data set based on negative case data (such as medical accident cases) and the book data that matches it.

[0128] In the above embodiment, the probability of medical staff obtaining wrong information is reduced. Fig.15 As shown in the figure, if the associated book of a negative case is "Guidelines for Diagnosis, Treatment and Rehabilitation of Cervical Spondylosis"

[0129] (2018), then the search results containing “Guidelines for Diagnosis, Treatment and Rehabilitation of Cervical Spondylosis” (2018) are deleted from the ordered set of search results of the second user, but “Guidelines for Diagnosis, Treatment and Rehabilitation of Cervical Spondylosis” 2016, “Guidelines for Diagnosis, Treatment and Rehabilitation of Cervical Spondylosis” 2017, “Guidelines for Diagnosis, Treatment and Rehabilitation of Cervical Spondylosis” 2019, and “Guidelines for Diagnosis, Treatment and Rehabilitation of Cervical Spondylosis” 2022 are still retained.

[0130] Some other embodiments of the present invention also involve a hospital digital library retrieval and resource sharing method, wherein the correlation between the revised set and the ordered set of search results of the second user is recorded each time the search is performed, and the high-frequency and low-correlation search results in the revised set are used to generate an ordered set of candidate books for the hospital library.

[0131] In the above embodiment, "high-frequency and low-correlation search results in the revised set" refers to search results (elements) that appear multiple times in the ordered set of search results of the second user, but each time have a low correlation with the revised set. The books corresponding to these search results are books that the medical staff of this hospital are interested in, but are not included in the corresponding database of the superior digital library. Therefore, the ordered set of candidate books for the hospital library can serve as a reference for the hospital to improve the scope of the hospital digital library in the future.

[0132] The implementation and functional operation of the subject matter described in this specification can be implemented in the following: digital electronic circuits, tangibly implemented computer software or firmware, computer hardware, including the structures disclosed in this specification and their structural equivalents, or a combination of more than one of the above. The implementation of the subject matter described in this specification can be implemented as one or more computer programs, that is, one or more modules of computer program instructions encoded on one or more tangible non-transitory program carriers, for being executed by a data processing device or controlling the operation of a data processing device. Computer programs (which may also be referred to or described as programs, software, software applications, modules, software modules, scripts or codes) can be written in any form of programming language, including compiled languages ​​or interpreted languages ​​or declarative languages ​​or procedural languages, and computer programs can be expanded in any form, including as independent programs or as modules, components, subroutines or other units suitable for use in a computing environment. Computer programs may, but do not necessarily, correspond to files in a file system. Programs may be stored in a portion of a file that stores other programs or data, for example, one or more scripts stored in the following: in a markup language document; in a single file dedicated to a related program; or in multiple collaborative files, for example, files storing one or more modules, subroutines or code portions. A computer program can be deployed to be executed on one computer or on multiple computers that are located at one site or distributed across multiple sites and interconnected by a communication network.

Claims

1. A hospital digital library search and resource sharing method, wherein the hospital library communicates with at least one shared digital library, characterized in that: The method comprises: Acquire a first search result from the shared digital library according to the search content information and acquire a third search result from a shared identity book list library of the shared digital library; the shared identity book list library is constructed based on shared information of an associated hospital library associated with the shared digital library, the shared information including user search results; Obtaining a second search result from a private identity book list library of the hospital library according to the search content information and the search identity information, wherein the private identity book list library is constructed based on medical staff-related book data and case data; the medical staff-related book data includes academic book data and academic book data; The user search result is obtained by integrating the first search result, the second search result and the third search result and shared to the shared digital library.

2. The hospital digital library search and resource sharing method according to claim 1, characterized in that: The shared digital library is a superior digital library, and the hospital library of the same level as the hospital library is associated with the shared digital library directly or through the superior digital library of the hospital library of the same level.

3. The hospital digital library search and resource sharing method according to claim 1, characterized in that: The shared digital library is a superior digital library and several hospital libraries of the same level, and the several hospital libraries of the same level form the associated hospital library. The first search result is obtained from the superior digital library, and the third search result is obtained from the hospital libraries of the same level.

4. The hospital digital library search and resource sharing method according to any one of claims 1 to 3, characterized in that: The method for constructing the private identity book list library according to the medical staff associated book data and the case data comprises the following steps: Constructing a medical staff-associated book data set according to the medical staff-associated book data; Constructing a case-related book data set based on the case data; The medical staff-associated book dataset and the case-associated book dataset are merged to obtain the private identity book list library.

5. The hospital digital library search and resource sharing method according to claim 4, characterized in that: Constructing a medical staff-related book dataset based on the medical staff-related book data includes the following steps: Obtain the hospital's educational and academic data; Based on the deduplicated academic information of the medical staff, use computer search or manual sorting to obtain academic book data representing the knowledge structure of the medical staff during their study period; based on the deduplicated academic information of the medical staff, use computer search or manual sorting to obtain academic book data representing the knowledge structure of the medical staff's academic research; After cleaning the academic book data, the data is standardized and the educational background impact factor is given to obtain the academic-related book data set. After cleaning the academic book data, the data is standardized and the academic resume impact factor is given to obtain the academic-related book data set. The academic qualification-related book dataset and the academic-related book dataset are combined after deduplication to obtain the medical staff-related book dataset.

6. The hospital digital library search and resource sharing method according to claim 5, characterized in that: Constructing a case-related book dataset based on case data includes the following steps: Acquire case data from a digital hospital system, and extract high-level semantic information from the case data to obtain empirical data; Experience book data representing the knowledge structure of the medical staff's clinical experience obtained by computer search based on the deduplicated experience information of the medical staff or by matching with the medical staff-related book data set; After data cleaning, the experience book data is standardized and given a work experience impact factor to obtain the case-related book data set.

7. The hospital digital library search and resource sharing method according to claim 6, characterized in that: The steps of fusing the medical staff-related book dataset and the case-related book dataset to obtain the private identity book list library include: Obtain the medical staff-related book dataset and case-related book dataset; The medical staff-associated book dataset and the case-associated book dataset are merged to obtain the identity book list library.

8. The hospital digital library search and resource sharing method according to claim 7, characterized in that: The shared information also includes academic qualification-related book datasets or their subsets, academic-related book datasets or their subsets, and case-related book datasets or their subsets.

9. The hospital digital library search and resource sharing method according to claim 1, characterized in that: The first search result, the second search result and the third search result are all ordered sets; the method for fusing the first search result, the second search result and the third search result is: Calculate the intersection of the first search result and the ordered set of the second search result; Calculate the intersection of the ordered sets of the first search result and the third search result; The union of the intersection of the ordered sets of the first search result and the second search result and the intersection of the ordered sets of the first search result and the third search result is calculated.

10. A hospital digital library retrieval and resource sharing system, characterized in that: The system comprises at least one processor; and a memory storing instructions, which, when executed by the at least one processor, implement the steps of the method according to any one of claims 1 to 9.

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