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1.
Forensic pathologists often encounter autopsies that require an assessment of antemortem general conditions (e.g., infection, metabolic disorders). To establish evaluation clues for such cases, we quantitatively examined macrophages and the general pathology of bone marrow in samples from 180 forensic autopsy cases of decedents with various conditions. Hematoxylin-eosin staining, Berlin blue staining, and immunostainings for CD163, CD138, and CD61 were performed. We determined the numbers per field (density) of total macrophages, swollen macrophages, macrophages with hemophagocytosis, and hemosiderin-laden macrophages. Each density was standardized by identifying its ratio to the total number of macrophages. The decedents' background data (cause of death, other pathological findings, postmortem interval, antemortem symptoms, and presence of resuscitation) were extracted. No correlations were found between the postmortem interval and the other decedent data, indicating that these data are not affected by postmortem changes. In the group in which inflammatory disease was the cause of death, there were significant elevations in the ratio of the swollen macrophage density to total macrophages. Significantly higher ratios of the density of swollen and hemophagocytic macrophages were observed in the group in which conditions with a prolonged agonal period were the cause of death. The group with a return of spontaneous circulation to resuscitation showed a significantly higher ratio of macrophage density with hemophagocytosis. This study provides the first statistical analysis focused on bone marrow histopathology in forensic autopsies. The results will be useful for elucidating causes of death and agonal-period conditions.  相似文献   
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背景 致密性骨炎(OCI)和其他疾病有时难以鉴别,探讨血清骨转换生化标志物可为OCI的鉴别诊断提供依据。 目的 探索女性OCI患者的血清骨转换生化标志物的水平变化及临床意义。 方法 回顾性选取2013年6月至2022年2月在北京积水潭医院门诊及住院诊断为OCI的61例女性患者作为观察组,年龄15~50岁,平均(33.8±6.6)岁,病程2周~15年。选择同期61例女性体检健康者作为对照组,年龄15~48岁,平均(35.6±7.6)岁。比较两组一般临床资料和血清骨转换生化标志物水平,并对血清骨转换生化标志物与病情相关指标进行相关性分析。 结果 观察组血清白蛋白(45.4±2.9)g/L低于对照组(46.5±2.8)g/L(t=2.190,P<0.05)。血清骨转换生化标志物比较结果显示,观察组血清1型胶原羧基末端肽β特殊序列(β-CTX)〔0.28(0.23,0.37)μg/L〕、N-端骨钙素(OC)〔13.1(11.2,16.2)μg/L〕、25-羟维生素D3〔25-(OH)VD3〕〔(14.1±5.1)μg/L〕低于对照组〔0.36(0.29,0.48)μg/L,15.6(13.7,17.3)μg/L,(17.5±6.6)μg/L〕(Z=-2.983、-3.255,t=3.081,P<0.05)。长病程亚组OC水平〔14.6(12.4,18.5)μg/L〕高于短病程亚组〔11.7(10.2,14.0)μg/L〕(Z=-2.407,P<0.05)。多孕亚组β-CTX〔0.25(0.22,0.32)μg/L〕、OC水平〔12.2(10.3,15.0)μg/L〕低于非多孕亚组〔0.33(0.26,0.44)μg/L、13.4(12.0,18.8)μg/L〕(Z=-2.486、-1.897,P<0.05)。相关性分析显示,观察组血清1型前胶原氨基端延长肽(tP1NP)与妊娠次数、生产次数均呈负相关(rs=-0.276、-0.298,P<0.05),OC与体质指数(BMI)、视觉模拟评分法(VAS)评分、妊娠次数均呈负相关(rs=-0.284、-0.374、-0.360,P<0.05),25-(OH)VD3水平与BMI呈正相关(rs=0.275,P<0.05)。 结论 女性OCI患者血清OC、β-CTX水平明显降低,可为鉴别其他疾病提供依据;血清OC水平可以反映OCI患者的严重程度,同时OC水平与患者妊娠次数相关;tP1NP与妊娠次数、生产次数相关。  相似文献   
3.
Bone mineral density (BMD) is a highly heritable predictor of osteoporotic fracture. GWAS have identified hundreds of loci influencing BMD, but few have been functionally analyzed. In this study, we show that SNPs within a BMD locus on chromosome 14q32.32 alter splicing and expression of PAR-1a/microtubule affinity regulating kinase 3 (MARK3), a conserved serine/threonine kinase known to regulate bioenergetics, cell division, and polarity. Mice lacking Mark3 either globally or selectively in osteoblasts have increased bone mass at maturity. RNA profiling from Mark3-deficient osteoblasts suggested changes in the expression of components of the Notch signaling pathway. Mark3-deficient osteoblasts exhibited greater matrix mineralization compared with controls that was accompanied by reduced Jag1/Hes1 expression and diminished downstream JNK signaling. Overexpression of Jag1 in Mark3-deficient osteoblasts both in vitro and in vivo normalized mineralization capacity and bone mass, respectively. Together, these findings reveal a mechanism whereby genetically regulated alterations in Mark3 expression perturb cell signaling in osteoblasts to influence bone mass.  相似文献   
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Particle size analysis in the pharmaceutical industry has long been a source of debate regarding how best to define measurement accuracy; the degree to which the result of a measurement or calculation conforms to the true value. Defining a “true” value for the size of a particle can be challenging as the output of its measurement will differ because of variations in measurement approaches, instrumental differences and calculation methods. Consequently, for “real” particles, a universal “true” value does not exist and accuracy is therefore not a definable characteristic. Accordingly, precision is then a measure of the ability to reproducibly achieve a measurement of unknown relevance.This article proposes, in place of accuracy, a means to define the “appropriateness” of a measurement in line with the critical quality attributes (CQA) of the material being characterized. The decision as to whether the measurement is correct should involve a link to the CQA; that is, correlation should be demonstrated, without which the measured particle size cannot be defined as a critical material attribute.Correspondingly, methods should also be able to provide sufficient precision to demonstrate discrimination relating to variation in the CQA. The benefits and challenges of this approach are discussed.  相似文献   
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Breast carcinoma is a major cause of morbidity and mortality in women. The study of bone pathologies presents considerable potential in anthropology, paleopathology, forensic science and medicine. In this paper, we present and discuss metastatic lesions found in the skeletons of known individuals from the CAL Milano Cemetery Skeletal Collection, clinically diagnosed with breast cancer during life. Fourteen skeletons from a contemporary and identified collection were macroscopically studied and metastases were identified by comparison with clinical literature. As a result, bone metastases were observed in 43% of the study sample. They were located most commonly on the ribs (28.1%), pelvic girdle (19.8%), vertebrae (15.6%), skull (15.6%), scapulae (10.2%) as well as proximal segment of the femora (8.4%) and humeri (2.4%) respectively, favoring sites of high vascularization. The majority of the lesions were osteolytic, although osteoblastic and mixed metastases did occur. Osteolytic metastases appear as coalescent porosity or round to oval perforating lesions on bones with denticulated margins and pitted surrounding bone, whereas osteoblastic metastases thickened the existing trabecula (spongiosclerosis). Mixed metastases were perforating lytic lesions exposing the osteoblastic activity in the underlying trabecular bone. These results, consistent with the data from the literature, strengthen the diagnostic criteria for metastases and illustrate the aspect of bone metastases in breast carcinoma.  相似文献   
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IntroductionPredicting pathological complete response (pCR) for patients receiving neoadjuvant chemotherapy (NAC) is crucial in establishing individualized treatment. Whole-slide images (WSIs) of tumor tissues reflect the histopathologic information of the tumor, which is important for therapeutic response effectiveness. In this study, we aimed to investigate whether predictive information for pCR could be detected from WSIs.Materials and methodsWe retrospectively collected data from four cohorts of 874 patients diagnosed with biopsy-proven breast cancer. A deep learning pathological model (DLPM) was constructed to predict pCR using biopsy WSIs in the primary cohort, and it was then validated in three external cohorts. The DLPM could generate a deep learning pathological score (DLPs) for each patient; stromal tumor-infiltrating lymphocytes (TILs) were selected for comparison with DLPs.ResultsThe WSI feature-based DLPM showed good predictive performance with the highest area under the curve (AUC) of 0.72 among the cohorts. Alternatively, the combination of the DLPM and clinical characteristics offered a better prediction performance (AUC >0.70) in all cohorts. We also evaluated the performance of DLPM in three different breast subtypes with the best prediction for the triple-negative breast cancer (TNBC) subtype (AUC: 0.73). Moreover, DLPM combined with clinical characteristics and stromal TILs achieved the highest AUC in the primary cohort (AUC: 0.82) and validation cohort 1 (AUC: 0.80).ConclusionOur study suggested that WSIs integrated with deep learning could potentially predict pCR to NAC in breast cancer. The predictive performance will be improved by combining clinical characteristics. DLPs from DLPM can provide more information compared to stromal TILs for pCR prediction.  相似文献   
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