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Articles by Syed A. Sulaiman
Total Records ( 2 ) for Syed A. Sulaiman
  Muaed J. Alomar , Anas A. Hourani and Syed A. Sulaiman
  Information technology, which uses the computer for data processing and decision-making, has invaded all kinds of sciences. Health informatics is one of these important areas. The Objective of this study is to develop a mathematical model that calculates the percentage of ADR occurrence using the data available from primary literature for a specific medication. A mathematical model was developed to calculate the percentage of adverse drug reaction occurrence for a specific patient, using specific patient factors. The expected effect is that these different patient factors will produce different adverse drug reactions in different percentages. The adverse drug reaction prediction model is developed using Microsoft access, forms are built and ready for the data to be collected and utilized from primary literature. Pharmacists and other medical specialists should give information technology more concern in order to develop a comprehensive decision support systems able to predict medication errors before they actually happen.
  Muaed J. Alomar , Anas A. Hourani , Syed A. Sulaiman and Claire C. Strauch
  Primary literature is a basic tool for medical knowledge and for future research. Every researcher relies at some point on the information available in published literature. Also, primary literature is utilized to develop guidelines for the medical use of medications in all kinds of diseases, accuracy is a must in this regard. To evaluate essential information regarding patients, drugs and diseases omitted from efficacy literature on antihypertensive drug safety. Data on antihypertensive adverse drug reactions we retrospectively collected from 219 medical articles using search engines IDIS Iowa Drug Information Services, ScienceDirect, Medscape, Pubmed, Ebscohost, Inside web, Proquest, Emerald and Medline. The data for the study was collected from primary literature carried out on antihypertensive medications in previous years. All of the available information regarding patients (patient’s factors) and drugs was collected in order to evaluate the percentage of the omitted data. 219 primary journal articles were collected, 640 medications from these articles were analyzed. Some of the 640 medications are the same but in different articles. Out of 640 medications collected, 15718 data entries were used which represent patient’s factors and drug factors, age, gender, type of job, renal conditions, alcohol consumption, use of other medications, other diseases, drug dose, drug frequency, dosage form. All these factors were evaluated for the effect on developing adverse drug reactions. The omitted data was classified into four different categories. Age, gender, race, smoking, health status, medication use and any other information related to the patients is basic information which needs to be available in all literature, not just to be mentioned in the methodology and sampling, but to be specified carefully and fully in the results.
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