Survey dataset on mental health in tech professionals from open sourcing mental health surveys (2017-2021).

The dataset presented here was created by combining surveys conducted by Open Sourcing Mental Illness, a non-profit organization, from 2017 to 2021. The primary objective of the surveys was to assess the prevalence of mental health concerns among individuals employed in the technology sector and to gauge their attitudes toward mental health in the workplace. The dataset is filtered to include only those respondents with a primary tech role, and descriptive questions are removed, ensuring data consistency and validity of survey responses for effective analysis. The proposed dataset provides a valuable resource for researchers and practitioners to gain insights into the mental health concerns and attitudes of individuals employed in the technology sector, thus aiding the development of evidence-based interventions and policies to improve the well-being of employees.

Artificial intelligence for breast cancer analysis: Trends & directions.

Breast cancer is one of the leading causes of death among women. Early detection of breast cancer can significantly improve the lives of millions of women across the globe. Given importance of finding solution/framework for early detection and diagnosis, recently many AI researchers are focusing to automate this task. The other reasons for surge in research activities in this direction are advent of robust AI algorithms (deep learning), availability of hardware that can run/train those robust and complex AI algorithms and accessibility of large enough dataset required for training AI algorithms. Different imaging modalities that have been exploited by researchers to automate the task of breast cancer detection are mammograms, ultrasound, magnetic resonance imaging, histopathological images or any combination of them. This article analyzes these imaging modalities and presents their strengths and limitations. It also enlists resources from where their datasets can be accessed for research purpose. This article then summarizes AI and computer vision based state-of-the-art methods proposed in the last decade to detect breast cancer using various imaging modalities. Primarily, in this article we have focused on reviewing frameworks that have reported results using mammograms as it is the most widely used breast imaging modality that serves as the first test that medical practitioners usually prescribe for the detection of breast cancer. Another reason for focusing on mammogram imaging modalities is the availability of its labelled datasets. Datasets availability is one of the most important aspects for the development of AI based frameworks as such algorithms are data hungry and generally quality of dataset affects performance of AI based algorithms. In a nutshell, this research article will act as a primary resource for the research community working in the field of automated breast imaging analysis.

Role of nebulized epinephrine in moderate bronchiolitis: a quasi-randomized trial.

BACKGROUND/AIMS: Bronchiolitis is the most common lower respiratory illness that characteristically affects the children below 2 years of age accounting about 2-3% of patients admitted to hospital each year [1-4]. We compared the effect of racemic epinephrine (RE) and 3% hypertonic saline (HS) nebulization on the length of stay (LOS) in the hospital. METHODS: We looked at the infants with moderate bronchiolitis, from October 2013 to March 2014. Out of eighty cases, 16 in HS and 18 in RE groups were enrolled. At the time of admission, 0.2 ml of RE added to 1.8 ml of distilled water was nebulized to RE group, as compared with 2 ml of 3% HS in nebulized form. RE was re-administered if needed on 6 h in comparison with 3% HS at the frequency of 1 to 4 h. RESULTS: One infant from RE group and three infants from HS group were excluded due to progression towards severe bronchiolitis. The LOS in RE group ranged between 18 and 160 h (mean 45 h), while in HS group, LOS was 18.50-206 h (mean 74.3 h). The LOS was significantly short in RE group (p value 0.015) which was statistically significant. CONCLUSION: Racemic epinephrine nebulization as first-line medication may significantly reduce the length of hospital stay in infants with moderate bronchiolitis in comparison with nebulized HS.