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Childhood cancer is the leading disease-related cause of death among under 15 year olds in Europe. Since primary preventive measures are lacking, improving survival probabilities and long-term well-being remain primary goals. With this report, we provide the first long-term assessment and interpretation of patterns in childhood cancer survival in Germany, covering a period of 30 years. Using data from the German Childhood Cancer Registry, we assessed temporal patterns of cancer survival among children (0-14 years) diagnosed in Germany from 1991 to 2016, by cancer type, age at diagnosis and sex. We calculated overall survival (OS) and average annual percentage changes of the respective 5-year OS estimates. OS improved across all cancer types, age groups as well as for boys and girls over time. Five-year OS for all childhood cancers combined increased from 77.8% in 1991-1995 to 86.5% in 2011-2016, with stronger improvements during the early 1990s. The most pronounced survival improvement was seen for acute myeloid leukaemia, at 2% annually and 5-year OS recently reaching 81.5%. Survival improvements for some diagnoses such as neuroblastoma, renal tumours and bone tumours have flattened out. Tremendous enhancements in diagnostics, treatment and supportive care have affected average survival improvements for most cancer types. Recently, survival improvements have decelerated overall and for some cancer types, it plateaued at an unsatisfactory level. As not all children benefited equally from the survival improvements, personal factors (eg, socioeconomic circumstances, health literacy, access to care) likely affect individual prognosis and warrant further investigation.  相似文献   
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Intratumor heterogeneity is a main cause of the dismal prognosis of glioblastoma (GBM). Yet, there remains a lack of a uniform assessment of the degree of heterogeneity. With a multiscale approach, we addressed the hypothesis that intratumor heterogeneity exists on different levels comprising traditional regional analyses, but also innovative methods including computer-assisted analysis of tumor morphology combined with epigenomic data. With this aim, 157 biopsies of 37 patients with therapy-naive IDH-wildtype GBM were analyzed regarding the intratumor variance of protein expression of glial marker GFAP, microglia marker Iba1 and proliferation marker Mib1. Hematoxylin and eosin stained slides were evaluated for tumor vascularization. For the estimation of pixel intensity and nuclear profiling, automated analysis was used. Additionally, DNA methylation profiling was conducted separately for the single biopsies. Scoring systems were established to integrate several parameters into one score for the four examined modalities of heterogeneity (regional, cellular, pixel-level and epigenomic). As a result, we could show that heterogeneity was detected in all four modalities. Furthermore, for the regional, cellular and epigenomic level, we confirmed the results of earlier studies stating that a higher degree of heterogeneity is associated with poorer overall survival. To integrate all modalities into one score, we designed a predictor of longer survival, which showed a highly significant separation regarding the OS. In conclusion, multiscale intratumor heterogeneity exists in glioblastoma and its degree has an impact on overall survival. In future studies, the implementation of a broadly feasible heterogeneity index should be considered.  相似文献   
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Genome-scale screening experiments in cancer produce long lists of candidate genes that require extensive interpretation for biological insight and prioritization for follow-up studies. Interrogation of gene lists frequently represents a significant and time-consuming undertaking, in which experimental biologists typically combine results from a variety of bioinformatics resources in an attempt to portray and understand cancer relevance. As a means to simplify and strengthen the support for this endeavor, we have developed oncoEnrichR, a flexible bioinformatics tool that allows cancer researchers to comprehensively interrogate a given gene list along multiple facets of cancer relevance. oncoEnrichR differs from general gene set analysis frameworks through the integration of an extensive set of prior knowledge specifically relevant for cancer, including ranked gene-tumor type associations, literature-supported proto-oncogene and tumor suppressor gene annotations, target druggability data, regulatory interactions, synthetic lethality predictions, as well as prognostic associations, gene aberrations and co-expression patterns across tumor types. The software produces a structured and user-friendly analysis report as its main output, where versions of all underlying data resources are explicitly logged, the latter being a critical component for reproducible science. We demonstrate the usefulness of oncoEnrichR through interrogation of two candidate lists from proteomic and CRISPR screens. oncoEnrichR is freely available as a web-based service hosted by the Galaxy platform ( https://oncotools.elixir.no ), and can also be accessed as a stand-alone R package ( https://github.com/sigven/oncoEnrichR ).  相似文献   
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Health systems around world are increasingly adopting cost-effectiveness (CE) analysis to inform decisions about access and reimbursement. We study how CE thresholds imposed by a health plan for granting reimbursement affect drug producers’ pricing incentives and patients’ access to new drugs. Analysing a sequential pricing game between an incumbent drug producer and a potential entrant with a new drug, we show that CE thresholds may have adverse effects for payers and patients. A stricter CE threshold may induce the incumbent to switch pricing strategy from entry accommodation to entry deterrence, limiting patients’ access to the new drug. Otherwise, irrespective of whether entry is deterred or accommodated, a stricter CE threshold is never pro-competitive and may in fact facilitate a collusive outcome with higher prices of both drugs. Compared to a laissez-faire policy, the use of CE thresholds when an incumbent monopolist is challenged by therapeutic substitutes can only increase the surplus of a health plan if it leads to entry deterrence. In this case the price reduction by the incumbent necessary to deter entry outweighs the health loss to patients who do not get access to the new drug.  相似文献   
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IntroductionThe main objective of this work is to carry out the clinical validation of the trial with the AMR Direct Flow Chip® starting from either nasal swabs, rectal swabs directly or from isolated strains to detect antibiotic resistance genes.MethodsWe developed the preclinical validation of the assay with 104 known bacterial isolates. A total of 210 nasal or rectal swab samples were analyzed. The AMR assay is based on multiplex PCR followed by reverse dot blot hybridization on DNA arrays fully automated by using the HS24 platform. The completion time of the full analysis is 3 hours.ResultsBoth the sensitivity and specificity of the preclinical assay were 100%, with the 104 samples correctly identified. In the clinical validation, the sensitivity was 100% and the specificity was between 100% in rectal swabs and 97% in nasal swabs.ConclusionsThe AMR Direct Flow Chip® is a rapid and effective assay for the detection of multidrug-resistant microorganisms from nasal and rectal swab samples.  相似文献   
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Background and aimsCurrent strategies to reduce cardiovascular disease (CVD) risk in young adults are largely limited to those at extremes of risk. In cohort studies we have shown cluster analysis identified a large sub-group of adolescents with multiple risk factors. This study examined if individuals classified at ‘high-risk’ by cluster analysis could also be identified by their Framingham risk scores.Methods and resultsRaine Study data at 17- (n = 1048) and 20-years (n = 1120) identified high- and low-risk groups by cluster analysis using continuous measures of systolic BP, BMI, triglycerides and insulin resistance. We assessed:- CVD risk at 20-years using the Framingham 30 yr-risk-score in the high- and low-risk clusters, and cluster stability from adolescence to adulthood.Cluster analysis at 17- and 20-years identified a high-risk group comprising, 17.9% and 21.3%, respectively of the cohort. In contrast, only 1.2% and 3.4%, respectively, met the metabolic syndrome criteria, all of whom were within the high-risk cluster. Compared with the low-risk cluster, Framingham scores of the high-risk cluster were elevated in males (9.4%; 99%CI 8.3, 10.6 vs 6.0%; 99%CI 5.7, 6.2) and females (4.9%; 99%CI 4.4, 5.4 vs 3.2%; 99%CI 3.0, 3.3) (both P < 0.0001). A score >8 for males and >4 for females identified those at high CVD risk with 99% confidence.ConclusionCluster analysis using multiple risk factors identified ~20% of young adults at high CVD risk. Application of our Framingham 30 yr-risk cut-offs to individuals allows identification of more young people with multiple risk factors for CVD than conventional metabolic syndrome criteria.  相似文献   
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