Диафаноскопическая диагностика дистрофических изменений переднего глаза

ГЛАУКОМАРАДУЖКАУВЕАЛЬНОГО ТРАКТА БОЛЕЗН

Open Source Software Low Cost Alternatives for Healthcare

Healthcare is the worlds second largest and also the fastest growing service sector. A well-managed and low cost healthcare system is of great importance to a country where large population with diverse social, educational and economical background is to be served. With health care being a government sector service, most of the hospitals are providing services with limited resources thus lacking the best services at time. ICT can play an important role in improving the services by managing the resources optimally and efficiently as ICT based tools can be used for resource management, patient record keeping, sharing the information, faster processing of data, managing the people at hospital etc. The development of an exhaustive healthcare system involves complex issues like finance, performance, security, scalability, and adherence to standards. Further, open source software solutions can help the hospitals to achieve the required services at lower cost. The paper presents the justifications to use open source solutions for hospitals and at the end will discus a case study about customization of the existing open source Hospital information system CARE2X, to fit into the workflow requirements of an Indian hospital with the advice of doctors. Customized CARE2X is implemented in Pathology department of client hospital

Design, synthesis and biological activities of 5Hdibenzo[ b,f]azepine-5-carboxamide derivatives; Targeted hippocampal trypsin inhibition as a novel approach to treat epileptogenesis

Purpose: To synthesize anticonvulsant drug derivatives that target protease-activated receptor generated epileptic seizures.Method: Varieties of carbamazepine-based Schiff bases were designed with different aldehydes and ketones, and evaluated for in silico computer-aided drug design prediction of absorption, distribution, metabolism and excretion (ADME), and potential drug targets. The resultant compounds were synthesized and characterized by various spectroscopic techniques, including FTIR, 1H-NMR and 13CNMR, analysis. Thereafter, they were screened for antimicrobial, antioxidant and anticonvulsant potential.Results: Prominent anti-protease potential was shown by C7 and C3 compounds and the order of activity was C7 > C3 > C5 > C2 > C6 > C4 > C2 > C1 (p < 0.05). The anticonvulsant activity of C7 and C5 was comparable with the standard drug; C3, C4, C6 and C8 had mild activity while C1 and C4 showed the least activity. The synthesized compounds exhibited significant (p < 0.05) antioxidant potential (rank order: C3 > C4 > C5 > C7 > C8 > C6 > C1 > C2) and antimicrobial activity against S.aureus and B. bronchiseptica (rank order: C5 > C2 > C8 > C1 > C4 > C3 > C7).Conclusion: Synthesized derivatives retained their potential for anticonvulsant and antitrypsin activity, unlike their mother moiety, i.e., carbamazepine. The additional antibacterial activity effectively treats neurological disorders associated with bacterial infections

Response of Gaussian-modulated guided wave in aluminum: An analytical, numerical, and experimental study

The application of guided-wave ultrasonic testing in structural health monitoring has been widely accepted. Comprehensive experimental works have been performed in the past but their validation with possible analytical and numerical solutions still requires serious efforts. In this paper, behavior and detection of the Gaussian-modulated sinusoidal guided-wave pulse traveling in an aluminum plate are presented. An analytical solution is derived for sensing guided wave at a given distance from the actuator. This solution can predict the primary wave modes separately. Numerical analysis is also carried out in COMSOL® Multiphysics software. An experimental setup comprising piezoelectric transducers is used for the validation. Comparison of experimental results with those obtained from analytical and numerical solutions shows close agreement

NGO Activism and Anti-corruption Disclosures : An Empirical Study of Emerging Economy Multinational Companies

Peer reviewe

Discussing the Role of Classification Algorithms in Clinical Predictions with help of Case Studies

This paper discuss about the important role of classification algorithms in clinical predictions , two case studies one for breast cancer and other for heart disease prediction with help of classification data mining techniques is presented in this paper. Online freely accessible data is used for the said case studies. Used data is publicly available data on internet consisting of 909 records for heart disease and 699 for breast cancer. C4.5 and the C5.0 Two well-known decision tree algorithms used to get the rules for predictions, and these rules used for improving the quality of an open source Pathology Management System based on Care2x.Performances of these algorithms are also compared. This Paper will further discuss about the importance of open source software in healthcare as well as how a pathology management system can adopt Evidence Based Medicine (EBM). EBM is a new and important approach which can greatly improve decision making in health care. EBM's task is to prevent, diagnose and medicate diseases using medical evidence [5].Clinical decisions must be based on scientific evidence that demonstrates effectiveness. This paper is basically extension of our previous work ‘A Prototype of Cancer/Heart Disease Prediction Model Using Data Mining’

Predicting mental illness at workplace using machine learning

Mental illness (MI) is a leading cause of workplace absenteeism that often goes unrecognized and untreated. This paper presents a machine learning algorithm for predicting MI at workplace. The dataset consisted of responses from 1259 subjects collected through an online survey using a self-assessed questionnaire on the workplace environment. The responses were used as features for training a support vector machine to predict MI. Statistical analysis using the Guttmann correlation and the analysis of variance was done to determine feature significance. Results using 10-fold cross-validation showed that the model predicted MI with good accuracy. Findings support the feasibility of this approach for MI monitoring at the workplace as it offers an advantage over other technologies e.g., MRI scans, and EEG analysis, previously developed for the objective assessment of MI

Comparison of Different Scores in Predicting Mortality in Patients with Acute on Chronic Liver Failure Admitted to the Intensive Care Unit of a Tertiary Care Hospital

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