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Background With the rapid spread of electronic medical records and the arrival of medical big data era, the application of natural language processing technology in biomedicine has become a hot research topic. Methods In this paper, firstly, BiLSTM-CRF model is applied to medical named entity recognition on Chinese electronic medical record. According to the characteristics of Chinese electronic medical records, obtain the low-dimensional word vector of each word in units of sentences. And then input the word vector to BiLSTM to realize automatic extraction of sentence features. And then CRF performs sentence-level word tagging. Secondly, attention mechanism is added between the BiLSTM and the CRF to construct Attention-BiLSTM-CRF model, which can leverage document-level information to alleviate tagging inconsistency. In addition, this paper proposes an entity auto-correct algorithm to rectify entities according to historical entity information. At last, a drug dictionary and post-processing rules are well-built to rectify entities, to further improve performance. Results The final F1 scores of the BiLSTM-CRF and Attention-BiLSTM-CRF model on given test dataset are 90.15 and 90.82% respectively, both of which are higher than 89.26%, which is the best F1 score on the test dataset except ours. Conclusion Our approach can be used to recognize medical named entity on Chinese electronic medical records and achieves the state-of-the-art performance on the given test dataset.

This chapter describes the main features of medical dictionary for regulatory activities (MedDRA) and world health organization drug dictionary (WHO‐DD). It discusses the principal terminologies used for coding medical conditions and medicines in the context of pharmacovigilance. The aim of coding is to impose order on the large number of ways in which medical conditions may be described and on the huge number of medicines to which patients may be exposed. The structures of these terminologies are quite complex, and their correct use is not always intuitive, but this reflects the extreme complexity of the diagnosis and treatment of disease in humans. Whilst there are traps for the unwary, familiarity with these terminologies, an understanding of their architecture and conventions, and thoughtful usage will result in accurate and consistent recording, retrieval, analysis, and presentation of data.

This second edition reflects the increasing importance of this science and the changing regulatory environment - in particular in research and development as well as in clinical trials, marketing authorization and safety issues including pharmacovigilance.

Here we review the features and applications of some dictionaries used for classifying medicines, adverse reactions, and medical conditions, and briefly explore the concept of the anatomical–therapeutic–chemical classification of drugs, the structure of the World Health Organization's drug dictionary, and the EudraVigilance Medicinal Product Dictionary. We present the structure and hierarchy of the WHO Adverse Reaction Terminology, as well as the elements of the International Classifications of Diseases (ICD 9, ICD 9‐CM, and ICD 10). We also briefly cover the SNOMED Disease Nomenclature. These adverse reactions dictionaries and disease classifications have been widely used in the pharmacovigilance environment in the past, but following the adoption of the Medical Dictionary for Regulatory Activities (MedDRA®) as an international standard in many organizations, the use of some of them in this context has declined. We present the regulatory requirements for the use of MedDRA, with information about the maintenance of the dictionary and how new terms are added and other changes effected. MedDRA is a large hierarchical multi‐axial terminology that includes terms for medical diagnoses, signs and symptoms, syndromes, qualitative investigation findings, medical and surgical procedures, and social circumstances. We present details of the structure and principal conventions used in MedDRA, together with an outline of how term selection is performed. We briefly consider various approaches to database searches and data retrieval, with an outline of some of the problems relating to data analysis and tabulation. We also discuss the CIOMS initiative on Standardised MedDRA Queries and describe the work of CIOMS in producing standard definitions for adverse reactions terms.

Drug name entity recognition (NER) is an important foundation of information extraction, automatic question answering, machine translation and information retrieval and other natural language processing technology based on the medical literature. This paper presents a method combined a constructed dictionary and conditional random field model to identify the drug entity. The proposed method has good performance in DDIExtraction 2013 evaluation corpus. //

The study of Pharmaceutical Dosage Forms has many connections to biological and medical sciences including physiology, biochemistry, pharmacology, pharmacotherapy, therapeutics, pharmacodynamics, pharmacokinetics and pharmacognosy. The Dictionary of Pharmaceutical Dosage Forms is a collection of terms and definitions prepared to assist healthcare practitioners and students as a companion or reference resource when reading notes and completing routine care. It can also provide reference material for hospital and medical staff, consultants, nursing instructors and pharmaceutical science students. This first edition classifies and organizes the forms in an easily readable format, so readers will find it a quick and simple reference.

The Uppsala Monitoring Centre (UMC) is the operational center of the WHO Programme for International Drug Monitoring, which currently includes a network of national pharmacovigilance centers in approximately 150 countries, representing 95% of the global population. In October 2015 more than 11.2 million individual case safety reports had been submitted to the WHO database, VigiBase®. Pharmacovigilance has expanded rapidly in terms of stakeholders involved and problem areas covered, now including all kinds of medicine related patient harm. The UMC mission is to build pharmacovigilance capacity globally with VigiBase as a joint resource for the WHO network. UMC provides technical support, data management tools and training to countries, engages in signal analysis of new medicine-related problems, provides dictionaries to partners in both public and private sectors, develops IT solutions, and undertakes methodological research to further pharmacovigilance as a science.

Bendamustine plus rituximab is a standard of care for the management of patients with relapsed or refractory chronic lymphocytic leukaemia. New therapies are needed to improve clinically relevant outcomes in these patients. We assessed the efficacy and safety of adding idelalisib, a first-in-class targeted phosphoinositide-3-kinase δ inhibitor, to bendamustine plus rituximab in this population. For this international, multicentre, double-blind, placebo-controlled trial, adult patients (≥18 years) with relapsed or refractory chronic lymphocytic leukaemia requiring treatment who had measurable lymphadenopathy by CT or MRI and disease progression within 36 months since their last previous therapy were enrolled. Patients were randomly assigned (1:1) by a central interactive web response system to receive bendamustine plus rituximab for a maximum of six cycles (bendamustine: 70 mg/m2 intravenously on days 1 and 2 for six 28-day cycles; rituximab: 375 mg/m2 on day 1 of cycle 1, and 500 mg/m2 on day 1 of cycles 2–6) in addition to either twice-daily oral idelalisib (150 mg) or placebo until disease progression or intolerable study drug-related toxicity. Randomisation was stratified by high-risk features (IGHV, del[17p], or TP53 mutation) and refractory versus relapsed disease. The primary endpoint was progression-free survival assessed by an independent review committee in the intention-to-treat population. This trial is ongoing and is registered with ClinicalTrials.gov, number NCT01569295. Between June 26, 2012, and Aug 21, 2014, 416 patients were enrolled and randomly assigned to the idelalisib (n=207) and placebo (n=209) groups. At a median follow-up of 14 months (IQR 7–18), median progression-free survival was 20·8 months (95% CI 16·6–26·4) in the idelalisib group and 11·1 months (8·9–11·1) in the placebo group (hazard ratio [HR] 0·33, 95% CI 0·25–0·44; p<0·0001). The most frequent grade 3 or worse adverse events in the idelalisib group were neutropenia (124 [60%] of 207 patients) and febrile neutropenia (48 [23%]), whereas in the placebo group they were neutropenia (99 [47%] of 209) and thrombocytopenia (27 [13%]). An increased risk of infection was reported in the idelalisib group compared with the placebo group (grade ≥3 infections and infestations: 80 [39%] of 207 vs 52 [25%] of 209). Serious adverse events, including febrile neutropenia, pneumonia, and pyrexia, were more common in the idelalisib group (140 [68%] of 207 patients) than in the placebo group (92 [44%] of 209). Treatment-emergent adverse events leading to death occurred in 23 (11%) patients in the idelalisib group and 15 (7%) in the placebo group, including six deaths from infections in the idelalisib group and three from infections in the placebo group. Idelalisib in combination with bendamustine plus rituximab improved progression-free survival compared with bendamustine plus rituximab alone in patients with relapsed or refractory chronic lymphocytic leukaemia. However, careful attention needs to be paid to management of serious adverse events and infections associated with this regimen during treatment selection. Gilead Sciences Inc.

Over the past decades, oncology treatment paradigms have developed significantly. Yet, the often unstructured nature of substance-related documentation in medical records presents a time-consuming challenge for analyzing treatment patterns and outcomes. To advance oncological research further, clinical data science must offer solutions that facilitate research and analysis with real-world data (RWD). The present contribution introduces a user-friendly R-tool designed to transform free-text medication entries into the structured Anatomical Therapeutic Chemical (ATC) Classification System by applying a dictionary-based approach. The resulting output is a structured data frame containing columns for antineoplastic medication, other medications, and supplementary information. For accuracy validation, 561 data entries from an evaluation data set were reviewed, consisting of 935 tokens. 88.5% of these tokens were successfully transformed into their respective ATC codes. Additional information was extracted from 129 data entries (23%), while 23 entries (4.1%) presented no usable information. All tokens underwent a manual review; 8.9% (84 tokens) failed transformations. This approach improves the standardization and analysis of systemic anti-cancer treatment data in German-speaking regions by optimizing efficiency while maintaining relevant accuracy.

Resistant hypertension is associated with increased cardiovascular risk. The endothelin pathway has been implicated in the pathogenesis of hypertension, but it is currently not targeted therapeutically, thereby leaving this relevant pathophysiological pathway unopposed with currently available drugs. The aim of the study was to assess the blood pressure lowering efficacy of the dual endothelin antagonist aprocitentan in patients with resistant hypertension. PRECISION was a multicentre, blinded, randomised, parallel-group, phase 3 study, which was done in hospitals or research centres in Europe, North America, Asia, and Australia. Patients were eligible for randomisation if their sitting systolic blood pressure was 140 mm Hg or higher despite taking standardised background therapy consisting of three antihypertensive drugs, including a diuretic. The study consisted of three sequential parts: part 1 was the 4-week double-blind, randomised, and placebo-controlled part, in which patients received aprocitentan 12·5 mg, aprocitentan 25 mg, or placebo in a 1:1:1 ratio; part 2 was a 32-week single (patient)-blind part, in which all patients received aprocitentan 25 mg; and part 3 was a 12-week double-blind, randomised, and placebo-controlled withdrawal part, in which patients were re-randomised to aprocitentan 25 mg or placebo in a 1:1 ratio. The primary and key secondary endpoints were changes in unattended office systolic blood pressure from baseline to week 4 and from withdrawal baseline to week 40, respectively. Secondary endpoints included 24-h ambulatory blood pressure changes. The study is registered on ClinicalTrials.gov, NCT03541174. The PRECISION study was done from June 18, 2018, to April 25, 2022. 1965 individuals were screened and 730 were randomly assigned. Of these 730 patients, 704 (96%) completed part 1 of the study; of these, 613 (87%) completed part 2 and, of these, 577 (94%) completed part 3 of the study. The least square mean (SE) change in office systolic blood pressure at 4 weeks was –15·3 (SE 0·9) mm Hg for aprocitentan 12·5 mg, –15·2 (0·9) mm Hg for aprocitentan 25 mg, and –11·5 (0·9) mm Hg for placebo, for a difference versus placebo of –3·8 (1·3) mm Hg (97·5% CI –6·8 to –0·8, p=0·0042) and –3·7 (1·3) mm Hg (–6·7 to –0·8; p=0·0046), respectively. The respective difference for 24 h ambulatory systolic blood pressure was –4·2 mm Hg (95% CI –6·2 to –2·1) and –5·9 mm Hg (–7·9 to –3·8). After 4 weeks of withdrawal, office systolic blood pressure significantly increased with placebo versus aprocitentan (5·8 mm Hg, 95% CI 3·7 to 7·9, p<0·0001). The most frequent adverse event was mild-to-moderate oedema or fluid retention, occurring in 9%, 18%, and 2% for patients receiving aprocitentan 12·5 mg, 25 mg, and placebo, during the 4-week double-blind part, respectively. This event led to discontinuation in seven patients treated with aprocitentan. During the trial, a total of 11 treatment-emergent deaths occurred, none of which were regarded by the investigators to be related to study treatment. In patients with resistant hypertension, aprocitentan was well tolerated and superior to placebo in lowering blood pressure at week 4 with a sustained effect at week 40. Idorsia Pharmaceuticals and Janssen Biotech.