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931.
《Medical image analysis》2015,21(1):61-75
We propose a new approach to register the subject image with the template by leveraging a set of intermediate images that are pre-aligned to the template. We argue that, if points in the subject and the intermediate images share similar local appearances, they may have common correspondence in the template. In this way, we learn the sparse representation of a certain subject point to reveal several similar candidate points in the intermediate images. Each selected intermediate candidate can bridge the correspondence from the subject point to the template space, thus predicting the transformation associated with the subject point at the confidence level that relates to the learned sparse coefficient. Following this strategy, we first predict transformations at selected key points, and retain multiple predictions on each key point, instead of allowing only a single correspondence. Then, by utilizing all key points and their predictions with varying confidences, we adaptively reconstruct the dense transformation field that warps the subject to the template. We further embed the prediction–reconstruction protocol above into a multi-resolution hierarchy. In the final, we refine our estimated transformation field via existing registration method in effective manners. We apply our method to registering brain MR images, and conclude that the proposed framework is competent to improve registration performances substantially. 相似文献
932.
933.
IntroductionFalls severely affect lives of Parkinson's disease (PD) patients. Cognitive impairment including dual-tasking deficits contribute to fall risk in PD. However, types of dual-tasking deficits preceding falls in PD are still unclear.MethodsWalking velocities during box-checking and subtracting serial 7s were assessed twice a year in 40 PD patients over 2.8 ± 1.0 years. Fourteen patients reported a fall within this period (4 excluded fallers already reported falls at baseline). Their dual-task costs (DTC; mean ± standard deviation) 4.2 ± 2.2 months before the first fall were compared with 22 patients never reporting falls. ROC analyses and logistic regressions accounting for DTC, UPDRS-III and disease duration were used for faller classification and prediction.ResultsOnly walking/box-checking predicted fallers. Fallers showed higher DTC for walking while box-checking, p = 0.029, but not for box-checking while walking, p = 0.178 (combined motor DTC, p = 0.022), than non-fallers. Combined motor DTC classified fallers and non-fallers (area under curve: 0.75; 95% confidence interval, CI: 0.60–0.91) with 71.4% sensitivity (95%CI: 41.9%–91.6%) and 77.3% specificity (54.6%–92.2%), and significantly predicted future fallers (p = 0.023). Here, 20.4%-points higher combined motor DTC (i.e. the mean difference between fallers and non-fallers) was associated with a 2.6 (1.1–6.0) times higher odds to be a future faller.ConclusionMotor dual-tasking is a potentially valuable predictor of falls in PD, suggesting that avoiding dual task situations as well as specific motor dual-task training might help to prevent falls in PD. These findings and their therapeutic relevance need to be further validated in PD patients without fall history, in early PD stages, and with various motor-motor dual-task challenges. 相似文献
934.
Predict Blood Pressure by Photoplethysmogram with the Fluid-Structure Interaction Modeling 下载免费PDF全文
Jianhong Chen Wenrui Hao Pengtao Sun & Lian Zhang 《Communications In Computational Physics》2022,31(4):1114-1133
Blood pressure (BP) has been identified as one of the main factors in cardiovascular disease and other related diseases. Then how to accurately and conveniently
measure BP is important to monitor BP and to prevent hypertension. This paper proposes an efficient BP measurement model by integrating a fluid-structure interaction
model with the photoplethysmogram (PPG) signal and developing a data-driven computational approach to fit two optimization parameters in the proposed model for each
individual. The developed BP model has been validated on a public BP dataset and has
shown that the average prediction errors among the root mean square error (RMSE),
the mean absolute error (MAE), the systolic blood pressure (SBP) error, and the diastolic blood pressure (DBP) error are all below 5 mmHg for normal BP, stage I, and stage
II hypertension groups, and, prediction accuracies of the SBP and the DBP are around
96% among those three groups. 相似文献
935.
936.
Ya-Hsuan Chang Yung-Li Yang Chung-Ming Chen Hsuan-Yu Chen 《American journal of cancer research》2015,5(5):1844-1853
The most common cancer in children is acute lymphoblastic leukemia (ALL) and it had high cure rate, especially for B-precursor ALL. However, relapse due to drug resistance and overdose treatment reach the limitations in patient managements. In this study, integration of gene expression microarray data, logistic regression, analysis of microarray (SAM) method, and gene set analysis were performed to discover treatment response associated pathway-based signatures in the original cohort. Results showed that 3772 probes were significantly associated with treatment response. After pathway analysis, only apoptosis pathway had significant association with treatment response. Apoptosis pathway signature (APS) derived from 15 significantly expressed genes had 88% accuracy for treatment response prediction. The APS was further validated in two independent cohorts. Results also showed that APS was significantly associated with induction failure time (adjusted hazard ratio [HR] = 1.60, 95% confidence interval [CI] = [1.13, 2.27]) in the first cohort and significantly associated with event-free survival (adjusted HR = 1.56, 95% CI = [1.13, 2.16]) or overall survival in the second cohort (adjusted HR = 1.74, 95% CI = [1.24, 2.45]). APS not only can predict clinical outcome, but also provide molecular guidance of patient management. 相似文献
937.
Postoperative delirium (POD) is a significant clinical problem in neurosurgical patients after intracranial surgery. Identification of high-risk patients may optimize perioperative management, but an adequate risk model for use at early phase after operation has not been developed. In the secondary analysis of a prospective cohort study, 800 adult patients admitted to the ICU after elective intracranial surgeries were included. The POD was diagnosed as Confusion Assessment Method for the ICU positive on postoperative day 1 to 3. Multivariate logistic regression analysis was used to develop early prediction model (E-PREPOD-NS) and the final model was validated with 200 bootstrap samples. The incidence of POD in this cohort was19.6%. We identified nine variables independently associated with POD in the final model: advanced age (OR 3.336, CI 1.765–6.305, 1 point), low education level (OR 2.528, 1.446–4.419, 1), smoking history (OR 2.582, 1.611–4.140, 1), diabetes (OR 2.541, 1.201–5.377, 1), supra-tentorial lesions (OR 3.424, 2.021–5.802, 1), anesthesia duration > 360 min (OR 1.686, 1.062–2.674, 0.5), GCS < 9 at ICU admission (OR 6.059, 3.789–9.690, 1.5), metabolic acidosis (OR 13.903, 6.248–30.938, 2.5), and neurosurgical drainage tube (OR 1.924, 1.132–3.269, 0.5). The area under the receiver operator curve (AUROC) of the risk score for prediction of POD was 0.865 (95% CI 0.835–0.895). The AUROC was 0.851 after internal validation (95% CI 0.791–0.912). The model showed good calibration. The E-PREPOD-NS model can predict POD in patients admitted to the ICU after elective intracranial surgery with good accuracy. External validation is needed in the future. 相似文献
938.
Sumaiya Z.
Sande Jialiang Li Ralph D'Agostino Tien Yin Wong Ching-Yu Cheng 《Statistics in medicine》2020,39(22):2980-3002
Statistical learning methods are widely used in medical literature for the purpose of diagnosis or prediction. Conventional accuracy assessment via sensitivity, specificity, and ROC curves does not fully account for clinical utility of a specific model. Decision curve analysis (DCA) becomes a novel complement as it incorporates a clinical judgment of the relative value of benefits (treating a true positive case) and harms (treating a false positive case) associated with prediction models. The preference of a patient or a policy-maker is formulated statistically as the underlying threshold probability, above which the patient would choose to be treated. Net benefit is then calculated for possible threshold probability, which places benefits and harms on the same scale. We consider the inference problems for DCA in this paper. Interval estimation procedure and inference methodology are provided after we derive the relevant asymptotic properties. Our formulation can accommodate the classification problems with multiple categories. We carry out numerical studies to assess the performance of the proposed methods. An eye disease dataset is analyzed to illustrate our proposals. 相似文献
939.
Andrea Raballo Michele Poletti Antonio Preti 《Journal of child psychology and psychiatry, and allied disciplines》2022,63(2):241-244
Research on Clinical High-Risk for Psychosis (CHR-P) has led to a vigorous change in the field of early detection in psychiatry and is gradually expanding its focus toward early development. The Annual Research Review on psychosis risk in adolescents (Journal of Child Psychology and Psychiatry, 62, 2020 and 657) offers a wide-angle meta-analytical picture of such emerging trends in all areas relevant to CHR-P Research, that is, detection, prognosis, and intervention. This editorial perspective is meant to expand the clinical and conceptual reach of these meta-analytic findings in relation to (a) the influence of age on transition rate and scalability of the early detection model across the child–adolescent vs adult periods; (b) potential latent heterogeneity of the pathogenetic trajectories leading to CHR-P as suggested by comorbid psychopathologies; (c) controversial (or at least problematic) prognostic significance of antipsychotic exposure in CHR-P subjects, especially in children and adolescents. 相似文献
940.
ABSTRACT Introduction: Turning was reported as one of the activities that most frequently leads to falling among stroke patients. This study investigated whether the duration and steps of a 180° turn while walking can distinguish retrospective fallers from non-fallers and predict future falls in a 1-year period in patients with poststroke hemiplegia. Methods: Thirty stroke patients were recruited. They were instructed to get up from a chair, walk straight 3 m, turn around, and return to seated position to assess the 180° walking-turn task. Turning performance was measured by two inertial sensor units of Physilog. Turn duration and steps were recorded for analysis. The numbers of retrospective and prospective falls were also obtained. Results: No significant difference was observed between retrospective stroke fallers and non-fallers in turn duration and steps. Turn duration and steps were significantly greater in prospective stroke fallers than in non-fallers. The cutoff turn duration of 4 s (area under the curve 0.75, 95% CI: 0.56–0.93, sensitivity 67%, specificity 80%, p =.04) and turn step of 7 steps (area under the curve 0.73, 95% CI: 0.51–0.94, sensitivity 56%, specificity 85%, p =.05) were found to most accurately predict prospective stroke fallers from non-fallers. Conclusions: Turn duration and steps were unable to discriminate between retrospective fallers and non-fallers but could predict prospective falls in patients with stroke. More than 4 s or 7 steps to complete a 180° turn while walking can be a predictor for patients with stroke at an increased risk of falling. 相似文献