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| 1 | Matrix effect in a view of lc-ms/ms: an overview 显示文摘 | DHARMENDRA PATEL | 2011 | International Journal of Pharma and Bio Sciences2011，1，1： | 1 |
| 2 | An atomic force microscopy investigation of bioadhesive polymer adsorption onto human buccal cells显示文摘 | James R Simth Andrew W Smith | 2000 | Int J Pharm2000，200，2： | 1 |
| 3 | An atomic force microscopy investigation of bioadhesive polymer adsorption onto human buccal cells显示文摘 | Dharmendra Patel James R Smith Andrew W Smith Nigel Grist Paul Barnett John D Smart | 2000 | International Journal of Pharmaceutics2000，，2： | 1 |
| 4 | Response to Ticagrelor in Clopidogrel Nonresponders and Responders and Effect of Switching Therapies: The RESPOND Study显示文摘 | Paul A. Gurbel Kevin P. Bliden Kathleen Butler Mark J. Antonino Cheryl Wei Renli Teng Lars Rasmussen Robert F. Storey Tonny Nielsen John W. Eikelboom Georges Sabe-Affaki Steen Husted Dean J. Kereiakes David Henderson Dharmendra V. Patel Udaya S. Tantry | 2010 | Circulation2010，，10： | 1 |
| 5 | Response to Ticagrelor in Clopidogrel Nonresponders and Responders and Effect of Switching Therapies: The RESPOND Study显示文摘 | Paul A. Gurbel Kevin P. Bliden Kathleen Butler Mark J. Antonino Cheryl Wei Renli Teng Lars Rasmussen Robert F. Storey Tonny Nielsen John W. Eikelboom Georges Sabe-Affaki Steen Husted Dean J. Kereiakes David Henderson Dharmendra V. Patel Udaya S. Tantry | 2010 | Circulation2010，，10： | 1 |
| 6 | A New Fuzzy Adaptive Algorithm to Classify Imbalanced Data显示文摘Classification of imbalanced data is a well explored issue in the data mining and machine learning community where one class representation is overwhelmed by other classes.The Imbalanced distribution of data is a natural occurrence in real world datasets,so needed to be dealt with carefully to get important insights.In case of imbalance in data sets,traditional classifiers have to sacrifice their performances,therefore lead to misclassifications.This paper suggests a weighted nearest neighbor approach in a fuzzy manner to deal with this issue.We have adapted the‘existing algorithm modification solution’to learn from imbalanced datasets that classify data without manipulating the natural distribution of data unlike the other popular data balancing methods.The K nearest neighbor is a non-parametric classification method that is mostly used in machine learning problems.Fuzzy classification with the nearest neighbor clears the belonging of an instance to classes and optimal weights with improved nearest neighbor concept helping to correctly classify imbalanced data.The proposed hybrid approach takes care of imbalance nature of data and reduces the inaccuracies appear in applications of original and traditional classifiers.Results show that it performs well over the existing fuzzy nearest neighbor and weighted neighbor strategies for imbalanced learning. | Harshita Patel Dharmendra Singh Rajput Ovidiu Petru Stan Liviu Cristian Miclea | 2022 | Computers, Materials & Continua2022，，1： | 0 |
| 7 | Azeotropic mixture used for development and validation of Lornoxicam in bulk and its tablet dosage form by spectrophotometric method显示文摘A novel, safe, economic and sensitive method of spectrophotometric estimation has been developed using Azeoptropic mixture (water:methanol: 60:40, v/v) for the quantitative determination of Lornoxicam, a practically water-insoluble drug. Hence, Lornoxicam stock solution was prepared in Azeoptropic mixture. Lornoxicam showed maximum absorbance at 383 nm. Beer's law was obeyed in the concentration range 4-24 mg/mL with regression coefficient of 0.999. The method was validated in terms of linearity (R 2 0.999), precision (CV for intra-day and inter-day was 0.280.68 and 0.12-0.92, respectively), accuracy (98.03-100.59% w/w) and specificity. This method is simple, precise, accurate, sensitive and reproducible and can be used for the routine quality control testing of the marketed formulations. | Prajesh Prajapati Vipul Vaghela Deepak Rawtani Harshad Patel Jasmin Kubavat Dharmendra Baraiya | 2012 | Journal of Pharmaceutical Analysis2012，2，4： | 0 |
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