Insomnia and Associated Social Factors among Medical Support Staff during the Covid-19 Pandemic.

The pandemic Covid-19 not only caused great public health problems but also caused enormous distress, especially for medical staff. The cross-sectional study aimed to investigate the prevalence rate of insomnia and to confirm the social factors among medical support staff in hospitals during the Covid-19 pandemic from 1st July 2020 to December 31st 2020. This study was conducted at Dhaka Medical College and Hospital (DMCH), Kurmitola General Hospital (KGH), Kuwait Bangladesh Friendship Government Hospital and Mugda Medical College and Hospital located at Dhaka and Tungipara UHC from Tungipara, Gopalganj, Bangladesh.

Healthcare workers' knowledge and attitudes regarding artificial intelligence adoption in healthcare: A cross-sectional study.

Background: The convergence of healthcare and artificial intelligence (AI) introduces a transformative era in medical practice. However, the knowledge and attitudes of healthcare workers concerning the adoption of artificial intelligence in healthcare are currently unknown.

Aims: The primary objective was to investigate the knowledge and attitudes of healthcare professionals in Dhaka city, Bangladesh, regarding the adoption of AI in healthcare.

Cytokine Storm among Bangladeshi adults with COVID-19: A prospective cohort study.

Objective: In COVID-19, cytokine storms (CS) result in higher mortality and morbidity. Our study evaluated the rate of cytokine storms among COVID-positive Bangladeshi adults.

Methods: From October 2020 to March 2022, this cohort study enrolled both COVID-positive and COVID-negative healthy adults.

Dataset on developing climate-smart transplanted rice variety BRRI dhan98 suitable for partially irrigated ecosystem in Bangladesh.

This dataset provides an in-depth analysis of rice yield and grain quality attributes in four successive four years across 27 diverse environments in Bangladesh. The analysis emphasizes assessing the performance of studied genotypes (GEN), environments (ENV), and their interrelations (GEI). The research aim is to detect a stable and adaptive rice cultivar that not only displays high yield, and better grain quality but also has molecular data to know favorable alleles and biotic and abiotic stress-related traits.