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Integrated medical resource consumption stratification in hospitalized patients:an Auto Triage Management model based on accurate risk,cost and length of stay prediction

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Science China(Life Sciences) 2022年第5期65卷 988-999页

作者： Qin Zhong Zongren Li Wenjun Wang Lei Zhang Kunlun He medical Big Data Research Center Chinese PLA General HospitalBeijing 100853China medical Artificial Intelligence Research Center Chinese PLA General HospitalBeijing 100853China Bio-engineering Research Center Chinese PLA General HospitalBeijing 100039China Department of Cardiology Fourth Medical Center of Chinese PLA General HospitalBeijing 100048China Key Laboratory of Ministry of Industry and Information Technology of Biomedical Engineering and Translational Medicine Chinese PLA General HospitalBeijing 100048China China-Australia Joint Research Center for Infectious Diseases School of Public HealthXi’an Jiaotong University Health Science CenterXi’an 710061China

Triage management plays important roles in hospitalized patients for disease severity stratification and medical burden analysis.Although progression risks have been extensively researched for numbers of diseases,other crucial indicators that reflect patients’economic and time costs have not been systematically studied.To address the problems,we developed an automatic deep learning based Auto Triage Management(ATM)Framework capable of accurately modelling patients’disease progression risk and health economic evaluation.Based on them,we can first discover the relationship between disease progression and medical system cost,find potential features that can more precisely aid patient triage in resource allocation,and allow treatment plan searching that has cured patients.Applying ATM in COVID-19,we built a joint model to predict patients’risk,the total length of stay(Lo S)and cost when at-admission,and remaining Lo S and cost at a given hospitalized time point,with C-index0.930 and 0.869 for risk prediction,mean absolute error(MAE)of 5.61 and 5.90 days for total Lo S prediction in internal and external validation data.

关键词： patient triage AutoML electronic medical records

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Assessing the Effectiveness of Strategies in US Birth Cohort Screening for Hepatitis C Infection

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Journal of Clinical and Translational Hepatology 2020年第1期8卷 25-41页

作者： Cynthia J.Tsay Joseph K.Lim Department of Internal Medicine Yale University School of MedicineNew HavenCTUSA Yale Liver Center Section of Digestive DiseasesYale University School of MedicineNew HavenCTUSA

Chronic hepatitis C infection in the USA is a highly morbid condition and current guidelines recommend one-time screening among the birth cohort(1945-1965).Understand-ing strategies to optimize screening can help inform future hepatitis C virus(HCV)screening guidelines.A focused literature search was performed using PubMed and manual abstract review from major hepatology conferences over the past 2 years.The search strategy involved using medical Subject Headings terms for hepatitis C,screening,birth cohort,baby boomers,and 1945-1965.The review was limited to data from the USA.A total of 327 articles were identified and 36 abstracts were included,with studies published between 2012-2019.Strategies including clinician education,electronic medical record alerts,reflex HCV RNA testing,point-of-care testing,multisite(outpatient,inpatient,emergency department,endoscopy suite)initiatives,direct patient solicitation,and utilization of non-physician providers have increased HCV screening rates.However,broad imple-mentation remains less than optimal.Barriers include lack of patient acceptance to screening and engagement in the HCV care cascade.The Veterans Affairs Healthcare System has achieved higher birth cohort screening rates through an integrated approach requiring high-level engagement by leadership and institutional commitment.Multiple strategies for increasing birth cohort screening have been successful,but overall rates of HCV screening remain low.These strat-egies can inform public health efforts to implement emerging national recommendations for expansion of HCV screening to all U.S.adults age 18 or older.

关键词： Hepatitis C Epidemiology HCV antibody Screening Birth cohort Baby boomers Care cascade electronic medical records

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Symptom network topological features predict the effectiveness of herbal treatment for pediatric cough

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Frontiers of Medicine 2020年第3期14卷 357-367页

作者： Mengxue Huang Jingjing Wang Runshun Zhang Zhuying Ni Xiaoying Liu Wenwen Liu Weilian Kong Yao Chen Tiantian Huang Guihua Li Dan Wei Jianzhong Liu Xuezhong Zhou Shanghai Traditional Chinese Medicine-Integrated Hospital Shanghai 200082China Institute of medical Intelligence School of Computer and Information TechnologyBeijing Jiaotong UniversityBeijing 100044China Guang'anmen Hospital China Academy of Chinese Medical SciencesBeijing 100053China Hubei Provincial Hospital of Traditional Chinese Medicine Wuhan 430061China Hubei Province Academy of Traditional Chinese Medicine Wuhan 430061China School of the Clinical Medicine College of Traditional Chinese Medicine Hubei University of Chinese MedicineWuhan 430061China

Pediatric cough is a heterogeneous condition in terms of symptoms and the underlying disease mechanisms.Symptom phenotypes hold complicated interactions between each other to form an intricate network structure.This study aims to investigate whether the network structure of pediatric cough symptoms is associated with the prognosis and outcome of patients.A total of 384 cases were derived from the electronic medical records of a highly experienced traditional Chinese medicine (TCM) physician.The data were divided into two groups according to the therapeutic effect,namely,an invalid group (group A with 40 cases of poor efficacy) and a valid group (group B with 344 cases of good efficacy).Several well-established analysis methods,namely,statistical test,correlation analysis,and complex network analysis,were used to analyze the data.This study reports that symptom networks of patients with pediatric cough are related to the effectiveness of treatment: a dense network of symptoms is associated with great difficulty in treatment.Interventions with the most different symptoms in the symptom network may have improved therapeutic effects.

关键词： pediatric cough complex network symptoms traditional Chinese medicine electronic medical records

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Comparative visual analytics for assessing medical records with sequence embedding

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Visual Informatics 2020年第2期4卷 72-85页

作者： Rongchen Guo Takanori Fujiwara Yiran Li Kelly M.Lima Soman Sen Nam K.Tran Kwan-Liu Ma Department of Computer Science Beihang UniversityBeijingChina Department of Computer Science University of CaliforniaDavisUnited States Department of Pathology and Laboratory Medicine University of CaliforniaDavisUnited States Department of Surgery University of CaliforniaDavisUnited States

Machine learning for data-driven diagnosis has been actively studied in medicine to provide better healthcare.Supporting analysis of a patient cohort similar to a patient under treatment is a key task for clinicians to make decisions with high confidence.However,such analysis is not straightforward due to the characteristics of medical records:high dimensionality,irregularity in time,and sparsity.To address this challenge,we introduce a method for similarity calculation of medical records.Our method employs event and sequence embeddings.While we use an autoencoder for the event embedding,we apply its variant with the self-attention mechanism for the sequence embedding.Moreover,in order to better handle the irregularity of data,we enhance the self-attention mechanism with consideration of different time intervals.We have developed a visual analytics system to support comparative studies of patient records.To make a comparison of sequences with different lengths easier,our system incorporates a sequence alignment method.Through its interactive interface,the user can quickly identify patients of interest and conveniently review both the temporal and multivariate aspects of the patient records.We demonstrate the effectiveness of our design and system with case studies using a real-world dataset from the neonatal intensive care unit of UC Davis.

关键词： electronic medical records Event sequence data Autoencoder Self-attention Sequence similarity Visual analytics

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Secure and Efficient Data Storage and Sharing Scheme Based on Double Blockchain

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Computers, Materials & Continua 2021年第1期66卷 499-515页

作者： Lejun Zhang Minghui Peng Weizheng Wang Yansen Su Shuna Cui Seokhoon Kim College of Information Engineering Yangzhou UniversityYangzhou225127China School Math&Computer Science Quanzhou Normal UniversityQuanzhou362000China Division of Computer Science University of AizuAizu–Wakamatsu9658580Japan Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and TechnologyAnhui UniversityHefei230601China medical College of Yangzhou University Yangzhou225001China Department of Gynecology and Obstetrics Affiliated Hospital of Yangzhou UniversityYangzhouChina Department of Computer Software Engineering Soonchunhyang UniversityAsanKorea

In the digital era,electronic medical record(EMR)has been a major way for hospitals to store patients’medical data.The traditional centralized medical system and semi-trusted cloud storage are difficult to achieve dynamic balance between privacy protection and data sharing.The storage capacity of blockchain is limited and single blockchain schemes have poor scalability and low throughput.To address these issues,we propose a secure and efficient medical data storage and sharing scheme based on double blockchain.In our scheme,we encrypt the original EMR and store it in the cloud.The storage blockchain stores the index of the complete EMR,and the shared blockchain stores the index of the shared part of the EMR.Users with different attributes can make requests to different blockchains to share different parts according to their own permissions.Through experiments,it was found that cloud storage combined with blockchain not only solved the problem of limited storage capacity of blockchain,but also greatly reduced the risk of leakage of the original EMR.Content Extraction Signature(CES)combined with the double blockchain technology realized the separation of the privacy part and the shared part of the original EMR.The symmetric encryption technology combined with Ciphertext-Policy Attribute-Based Encryption(CP–ABE)not only ensures the safe storage of data in the cloud,but also achieves the consistency and convenience of data update,avoiding redundant backup of data.Safety analysis and performance analysis verified the feasibility and effectiveness of our scheme.

关键词： Cloud storage blockchain electronic medical records access control data sharing privacy

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Classification of metabolic-associated fatty liver disease subtypes based on TCM clinical phenotype

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Gastroenterology & Hepatology Research 2023年第1期5卷 6-12页

作者： Chenxia Lu Hui Zhu Mingzhong Xiao Xiaodong Li Department of Hepatology Hubei Key Laboratory of the theory and application research of liver and kidney in traditional Chinese medicineHubei Provincial Hospital of Traditional Chinese MedicineWuhan 430061China Affiliated Hospital of Hubei University of Chinese Medicine Wuhan 430061China Hubei Province Academy of Traditional Chinese Medicine Wuhan 430074China The Clinical medical College of Traditional Chinese Medicine Hubei University of Chinese MedicineWuhan 430065China

Objective:To classify the subtypes of metabolic-associated fatty liver disease(MAFLD)and provide new insights into the heterogeneity of MAFLD.Methods:electronic medical records(EMR)of MAFLD diagnosed in accordance with the diagnostic criteria of Hubei Provincial Hospital of Traditional Chinese Medicine from 2016-2020 were included in the study.for physical annotation,and the data on each clinical phenotype was normalized according to corresponding aspirational standards.The MAFLD heterogeneous medical record network(HEMnet)was constructed using sex,age,disease diagnosis,symptoms,and Western medicine prescriptions as nodes and the co-occurrence times between phenotypes as edges.K-means clustering was used for disease classification.Relative risk(RR)was used to assess the specificity of each phenotype.Statistical methods were used to compare differences in laboratory indicators among subtypes.Results:A total of patients(12,626)with a mean age of 55.02(±14.21)years were included in the study.MAFLD can be divided into five subtypes:digestive diseases(C0),mental disorders and gynecological diseases(C1),chronic liver diseases and decompensated complications(C2),diabetes mellitus and its complications(C3),and immune joint system diseases(C4).Conclusions:Patients with MAFLD experience various symptoms and complications.The classification of MAFLD based on the HEMnet method is highly reliable.

关键词： metabolic-associated fatty liver disease electronic medical records disease classification heterogeneous medical record network disease heterogeneity

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Translation in Data Mining to Advance Personalized Medicine for Health Equity

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Intelligent Information Management 2016年第1期8卷 9-16页

作者： Estela A. Estape Mary Helen Mays Elizabeth A. Sternke School of Health Professions Medical Sciences Campus-University of Puerto Rico San Juan PR USA School of Health Professions and the Puerto Rico Clinical and Translational Research Consortium Medical Sciences Campus-University of Puerto Rico San Juan PR USA

Personalized medicine is the development of “tailored” therapies that reflect traditional medical approaches with the incorporation of the patient’s unique genetic profile and the environmental basis of the disease. These individualized strategies encompass disease prevention and diagnosis, as well as treatment strategies. Today’s healthcare workforce is faced with the availability of massive amounts of patient- and disease-related data. When mined effectively, these data will help produce more efficient and effective diagnoses and treatment, leading to better prognoses for patients at both the individual and population level. Designing preventive and therapeutic interventions for those patients who will benefit most while minimizing side effects and controlling healthcare costs requires bringing diverse data sources together in an analytic paradigm. A resource to clinicians in the development and application of personalized medicine is largely facilitated, perhaps even driven, by the analysis of “big data”. For example, the availability of clinical data warehouses is a significant resource for clinicians in practicing personalized medicine. These “big data” repositories can be queried by clinicians, using specific questions, with data used to gain an understanding of challenges in patient care and treatment. Health informaticians are critical partners to data analytics including the use of technological infrastructures and predictive data mining strategies to access data from multiple sources, assisting clinicians’ interpretation of data and development of personalized, targeted therapy recommendations. In this paper, we look at the concept of personalized medicine, offering perspectives in four important, influencing topics: 1) the availability of “big data” and the role of biomedical informatics in personalized medicine, 2) the need for interdisciplinary teams in the development and evaluation of personalized therapeutic approaches, and 3) the impact of electronic medical record systems and clinical data wareh

关键词： Data Mining electronic medical records Translation Personalized Medicine Biomedical Informatics Heath Equity Healthcare Workforce

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Mobile EMR Use for Epidemiological Surveillance on a medical Service Trip in Honduras: A Pilot Study

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E-Health Telecommunication Systems and Networks 2016年第1期5卷 1-7页

作者： Christopher J. Dainton Charlene H. Chu Grand River Hospital Kitchener Canada University of Toronto Toronto Canada

Rationale: medical treatment on short-term primary care medical service trips (MSTs) is generally symptom-based and supplemented by point-of-care testing. This pilot study contributes to the effective planning for such austere settings based on predicted symptomology. Objective: We aimed to prospectively document the epidemiology of patients seen during two low-resource clinics on a MST in Honduras and apply predefined case definitions adapted from guidelines used by international healthcare organizations (e.g. World Health Organization). Methods: An observational design was used to track the epidemiology during two clinics on an MST in Limon, Honduras in March 2015. The QuickChart mobile electronic medical record (EMR) application was piloted to document diagnoses according to predefined case definitions. Results: The most commonly diagnosed syndromes were upper respiratory complaints (20.19%), nonspecific abdominal complaints (20.19%), general pain (15.38%), hypertension (9.62%), pruritus (6.73%), and asthma/ COPD (4.81%). The case definitions accounted for 94% of all complaints and diagnoses on the brigade. Discussion: The distribution of common patient diagnoses on this MST was similar to that which had been reported elsewhere. The use of broader symptom-based case definitions for epidemiologic surveillance could also facilitate the syndromic management of patients seen on MSTs, and improve the consistency of treatment offered. Conclusion: Case definitions for common syndromes on primary care MSTs may be a feasible method of standardizing patient management. Preliminary use of the QuickChart EMR was acceptable for documentation of epidemiology in the field. Further study is necessary to investigate the reliability of syndromic diagnostic criteria between different clinicians and in a variety of MST settings.

关键词： electronic medical records Epidemiology Global Health Experience medical Missions medical Service Trip Primary Care

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