A cross-sectional study to assess the knowledge, attitude and practice of contraceptive implants at tertiary care hospital in Ahmedabad, Gujarat

Background: The aim of our study was to evaluate the knowledge, attitude and practice regarding contraceptive implants methods, the acceptance of implants and to find association between the various socio-demographic factors and the awareness about implants. Methods: A questionnaire based cross-sectional study was conducted among the female client coming to the Family Planning Out-Patient Department (OPD) of Obstetrics and Gynaecology department of a tertiary care-Medical college hospital in Ahmedabad. Sample size came out to be 200 based on time bound systemic sampling method. Results: Mean age of client is 27.14 years. Out of the 200 respondents, only 62.5% were aware about one of contraceptive method and about 17% had heard about contraceptive implants. 58% women believe that contraception should be used by every woman. 15% women felt that implants were safe and should be promoted. Only about 50 % (half) of the sample population used some form of contraception. 12 participants in our study used implants and 4 of them experienced irregular menstrual cycle. Religion, education and gravidity are significantly associated with the awareness of contraceptive implants. Conclusions: To conclude, significant improvement needs to be brought by Govt. of India and state Govt., in the awareness by information, education and communication (IEC material) and acceptance of contraception in general and implants in specific. Specific regional loopholes must be searched and identify and targeted to improve the overall acceptance and improving reproductive health of women

AYURVEDIC MANAGEMENT OF SHWITRA (VITILIGO)- A CASE STUDY.

The Sanskrit term Shweta, which meaning "white patch," is the root of the name Shwitra. Shwitra (Vitiligo) is a condition that is referenced in the classic Kushta Roga Chikitsa and affects a significant section of the pediatric population as a result of poor dietary and lifestyle choices. Shwitra "Shweta Bhava Michanti Shwitram" is what the Kashyapa Samhita says. Kilasa, Daruna, Aruna, and Shweta Kushta are some more names for it. In contemporary medicine, vitiligo is referred to as an auto immune illness and manifests as a white patch on the skin. A widespread, progressive, chronic skin illness called vitiligo is characterized by patches of skin with sharp, frequently hyperpigmented edges caused by a lack of melanin pigments. Approximately 1% of people worldwide suffer from this illness. This condition is included under the general topic of Shwitra in Ayurveda. Every Acharya has the same opinion that the two primary therapeutic modalities mentioned in the classics—Samshodhan Karma and Samshaman Karma—should be used to treat Shwitra or Kushtha first. In their various Samhitas, Acharyas have specified a variety of internal and external uses, as well as sun exposure, for Shaman Chikitsa in the Shwitra Roga. Samhitas discuss a wide range of single and combination medications; among them, Shwitrahar Kashaya and lepa are mentioned in detail. One of them is chosen and shown to be useful for the investigation

Active mutual conjoint estimation of multiple contrast sensitivity functions

Recent advances in nonparametric contrast sensitivity function (CSF) estimation have yielded a new tradeoff between accuracy and efficiency not available to classical parametric estimators. An additional advantage of this new framework is the ability to independently tune multiple aspects of the estimator to seek further improvements. Machine learning CSF estimation with Gaussian processes allows for design optimization in the kernel, acquisition function, and underlying task representation, to name a few. This article describes a novel kernel for CSF estimation that is more flexible than a kernel based on strictly functional forms. Despite being more flexible, it can result in a more efficient estimator. Further, trial selection for data acquisition that is generalized beyond pure information gain can also improve estimator quality. Finally, introducing latent variable representations underlying general CSF shapes can enable simultaneous estimation of multiple CSFs, such as from different eyes, eccentricities, or luminances. The conditions under which the new procedures perform better than previous nonparametric estimation procedures are presented and quantified

Contrast response function estimation with nonparametric Bayesian active learning

Multidimensional psychometric functions can typically be estimated nonparametrically for greater accuracy or parametrically for greater efficiency. By recasting the estimation problem from regression to classification, however, powerful machine learning tools can be leveraged to provide an adjustable balance between accuracy and efficiency. Contrast sensitivity functions (CSFs) are behaviorally estimated curves that provide insight into both peripheral and central visual function. Because estimation can be impractically long, current clinical workflows must make compromises such as limited sampling across spatial frequency or strong assumptions on CSF shape. This article describes the development of the machine learning contrast response function (MLCRF) estimator, which quantifies the expected probability of success in performing a contrast detection or discrimination task. A machine learning CSF can then be derived from the MLCRF. Using simulated eyes created from canonical CSF curves and actual human contrast response data, the accuracy and efficiency of the machine learning contrast sensitivity function (MLCSF) was evaluated to determine its potential utility for research and clinical applications. With stimuli selected randomly, the MLCSF estimator converged slowly toward ground truth. With optimal stimulus selection via Bayesian active learning, convergence was nearly an order of magnitude faster, requiring only tens of stimuli to achieve reasonable estimates. Inclusion of an informative prior provided no consistent advantage to the estimator as configured. MLCSF achieved efficiencies on par with quickCSF, a conventional parametric estimator, but with systematically higher accuracy. Because MLCSF design allows accuracy to be traded off against efficiency, it should be explored further to uncover its full potential