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61.
PurposeHigh resolution spectral domain optical coherence tomography (SD-OCT) was used to assess the anterior segment structure parameters in healthy South Asian children.Methods108 eyes of 54 healthy children ≤ 16 years were recruited after a thorough eye exam. The anterior segment analysis was be done by Optopol Revo 80 high resolution SD-OCT. Central corneal thickness (CCT), Angle opening distance (AOD), Anterior chamber (AC) angle, Trabecular iris space area (TISA), Trabecular iris angle (TIA), iris thickness at 2 mm, internal AC diameter and lens vault were evaluated.ResultsMean age was 11.38 years. Mean IOP was 13.63 mmHg, mean axial length, 22.82 mm, mean spherical equivalent, -0.14 D, mean CCT, 532.6 µm and mean CDR was 0.31. The mean internal AC diameter was 11609.15 µm. The nasal and temporal AC angles was 53.54° and 50.37°, respectively [P = .033]. The nasal and temporal AOD500 were 0.9 mm and 0.85 mm, respectively [P = .629]. The nasal and temporal AOD750 were 1.21 mm and 1.06 mm, respectively [P = .583]. The nasal TIA was 41.75°; the temporal TIA; 40.24° [P = .325]. The nasal TISA500 was 0.33 mm2; the temporal TISA500, 0.31 mm2 [P = .012]. The nasal TISA750 was 0. 59 mm2; the temporal TISA750, 0.56 mm2 [P = .746]. The nasal iris thickness at 2 mm was 483.54 µm; the temporal iris thickness, 505.8 µm [P = .273]. The mean lens vault was -519.58 µm.ConclusionsOur study data depicts the normal anterior segment parameters in healthy Pakistani children.  相似文献   
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《Australian critical care》2016,29(2):104-109
Effective team decision making has the potential to improve the quality of health care outcomes. Medical Emergency Teams (METs), a specific type of team led by either critical care nurses or physicians, must respond to and improve the outcomes of deteriorating patients. METs routinely make decisions under conditions of uncertainty and suboptimal care outcomes still occur. In response, the development and use of Shared Mental Models (SMMs), which have been shown to promote higher team performance under stress, may enhance patient outcomes. This discussion paper specifically focuses on the development and use of SMMs in the context of METs. Within this process, the psychological mechanisms promoting enhanced team performance are examined and the utility of this model is discussed through the narrative of six habits applied to MET interactions.A two stage, reciprocal model of both nonanalytic decision making within the acute care environment and analytic decision making during reflective action learning was developed. These habits are explored within the context of a MET, illustrating how applying SMMs and action learning processes may enhance team-based problem solving under stress. Based on this model, we make recommendations to enhance MET decision making under stress. It is suggested that the corresponding habits embedded within this model could be imparted to MET members and tested by health care researchers to assess the efficacy of this integrated decision making approach in respect to enhanced team performance and patient outcomes.  相似文献   
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In recent years, deep learning as a state-of-the-art machine learning technique has made great success in histopathological image classification. However, most of deep learning approaches rely heavily on the substantial task-specific annotations, which require experienced pathologists’ manual labelling. As a result, they are laborious and time-consuming, and many unlabeled pathological images are difficult to use without experts’ annotations. To mitigate the requirement for data annotation, we propose a self-supervised Deep Adaptive Regularized Clustering (DARC) framework to pre-train a neural network. DARC iteratively clusters the learned representations and utilizes the cluster assignments as pseudo-labels to learn the parameters of the network. To learn feasible representations and encourage the representations to become more discriminative, we design an objective function combining a network loss with a clustering loss using an adaptive regularization function, which is updated adaptively throughout the training process to learn feasible representations. The proposed DARC is evaluated on three public datasets, including NCT-CRC-HE-100K, PCam and LC25000. Compared to the strategy of training from scratch, fine-tuning using the pre-trained weights of DARC can obviously boost the accuracy of neural networks on histopathological classification. The accuracy of using the network trained using DARC pre-trained weights with only 10% labeled data is already comparable to the network trained from scratch with 100% training data. The network using DARC pre-trained weights achieves the fastest convergence speed on the downstream classification task. Moreover, visualization through t-distributed stochastic neighbor embedding (t-SNE) shows that the learned representations are generalizable and discriminative.  相似文献   
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BackgroundMultiple sclerosis (MS) is a demyelinating disorder of the central nervous system with heterogeneous symptoms. Persons with MS (PwMS) show reduced walking capacity with changes in their gait pattern. It is unknown to which extent coordination deficits are present in PwMS, which can be measured by seated lower leg interlimb coordination tasks, and to which extent they are related to motor and cognitive function.Research questionHow is the control of interlimb coordination of the lower limbs characterized in PwMS compared to healthy controls (HC) during a seated rhythmical coordination task and what is the relationship between interlimb coordination, motor or cognitive function?MethodsRhythmical interlimb coordination was assessed during a single session in 38 PwMS and 13 HC, using a seated rhythmical coordination task, comprising of antiphase flexion-extension of the lower limbs, to metronomes at 0.75 Hz, 1.00 Hz, 1.50 Hz. Outcomes were phase coordination index (PCI), movement amplitude and movement frequency. Correlations between interlimb coordination, motor, and cognitive function were examined.ResultsPwMS showed impaired walking capacity but preserved cognitive function. Mixed model analysis revealed a significant effect of group and metronome frequency for PCI, attenuated by the variability in generating knee (antiphase flexion-extension) movements. Movement amplitude was highest at metronome frequency 1.00 Hz. In PwMS significant correlations were found between PCI and cognitive function when performing the task at metronome frequencies 0.75 Hz and 1.50 Hz, as well as motor function at 1.50 Hz.SignificancePwMS had a higher variability in interlimb coordination compared to HC. The most stable interlimb antiphase coordination mode was performed at 1.00 Hz. Significant correlations support the existence of a relationship between information processing speed, as well as walking impairment, with interlimb coordination. While cognitive and motor control are always needed for interlimb coordination movements, associations are strongest in the deviant higher and lower metronome rhythms.  相似文献   
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BackgroundAchieving negative margins for melanoma in situ, lentigo maligna type can be challenging, particularly on cosmetically sensitive areas.ObjectiveTo assess the utility of intraoperative frozen section margin assessment using a teledermatopathology system in the treatment of head and neck lentigo maligna.Methods and materialsOver a 6 year period, 96 patients with lentigo maligna had surgical excisions. The margins were assessed intraoperatively with frozen sections prepared in the manner used in Mohs surgery. The surgeon guided the frozen section slides around the margin while a dermatopathologist assessed the margin remotely.ResultsIn 2/96 (2.1%) cases, the safety margin was positive (frozen sections were false negative). In 1 further case (1%) there was a recurrence of the melanoma 13 months following the excision.ConclusionThe described method is effective in treating melanoma in situ, lentigo maligna type with clearance rates similar to previous studies for Mohs surgery.  相似文献   
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