COVID-19 vaccine hesitancy linked to increased internet search queries for side effects on fertility potential in the initial rollout phase following Emergency Use Authorization.

The Emergency Use Authorization (EUA) of the COVID-19 vaccine on December 11, 2020 has been met with hesitancy for uptake with some citing potential impacts on future fertility. We hypothesised that irrespective of sex, fertility-related queries would markedly increase during the 48 days following EUA of the coronavirus vaccine. We sought to objectively identify trends in internet search queries on public concerns regarding COVID-19 vaccine side effects on fertility that might impact vaccine uptake. We used Google Trends to investigate queries in Google's Search Engine relating to the coronavirus vaccine and fertility between 10/24/2020 and 1/27/2021. The five most queried terms were identified as: 'COVID Vaccine Fertility', 'COVID Vaccine and Infertility', 'COVID Vaccine Infertility', 'COVID Vaccine Fertility CDC', and 'COVID 19 Vaccine Infertility' with an increase of 710.47%, 207.56%, 264.35%, 2,943.7%, and 529.26%, respectively, all p < .001. This study indicates that there was an increase in online COVID-19 vaccine-related queries regarding fertility side effects coinciding with the Emergency Use Authorization (EUA) on December 11, 2020. Our results objectively evidence the increased concern regarding the vaccine and likely demonstrate a major cause for hesitancy in vaccine uptake. Future studies and counselling with patients should be undertaken to help mitigate these concerns.

A Systematic Review of Artificial Intelligence in Prostate Cancer.

The diagnosis and management of prostate cancer involves the interpretation of data from multiple modalities to aid in decision making. Tools like PSA levels, MRI guided biopsies, genomic biomarkers, and Gleason grading are used to diagnose, risk stratify, and then monitor patients during respective follow-ups. Nevertheless, diagnosis tracking and subsequent risk stratification often lend itself to significant subjectivity. Artificial intelligence (AI) can allow clinicians to recognize difficult relationships and manage enormous data sets, which is a task that is both extraordinarily difficult and time consuming for humans. By using AI algorithms and reducing the level of subjectivity, it is possible to use fewer resources while improving the overall efficiency and accuracy in prostate cancer diagnosis and management. Thus, this systematic review focuses on analyzing advancements in AI-based artificial neural networks (ANN) and their current role in prostate cancer diagnosis and management.